 Thank you very much everyone for coming, this is the second session and I'm really, really happy to have my hand here. Myel, who stands by now an old friend, we have shared accommodations in San Sebastian, San Paolo and several places at various conferences and I think it's really hard to present Myel because when you're talking about doing interdisciplinary research I think the one who gets closer to the definition is a mathematician, a theoretical biologist, a philosopher and works on many different tables at the same time and so it's really a big pleasure to have him here. The publication, if I had to give an account of the publication I would have to give a talk myself about that so I'm not going to do it but I'm just going to mention a very nice book with Giuseppe Longo who's also a very interesting polymath on organisms. A paper with Matteo Moscio has been here a couple of years ago on the Journal of Theoretical Biology that I've been talking to Stuart Kaufman during the summer school a couple of years ago and he was absolutely raving about that paper and actually in the first or second page of this new book is raving. The last book by Stuart Kaufman opens up with him saying well these two guys are awesome, they understood everything we should do that and another paper with Kaufman and Giuseppe Longo on enablement and entailment that I personally like very much so but without further ado please you have a floor. Thank you so today what I'm planning to do is to give a bit of an overview of what I'm working on with respect to Theoretical Biology which is why I call the talk some strategic perspective because Theoretical Biology is not really a field it doesn't really exist institutionally, there are a few journals but no read departments and so on but I will give my own spin to what it means to do Theoretical Biology and in a sense it's relevant it's questions that are relevant also for physics so let's start. I am currently editing a special issue in a new journal called Philosophy World Democracy on what I called the Dusk of Theoretical Controversies in Current Sciences my point is that theory as such is declining in most sciences so for biology I argue about it myself but I lean on physicists and mathematicians for the physics side and that's the topic of the special issue and there are reasons that are both internal to sciences and external due to so external ones are for example the reorganization of academia which can be seen as a disorganization for example Peter Higgs in physics said to a journal I think it was a gradient that he would not have been fit in current academia so that's why this organization is a disorganization in a sense there is also a short priority on technological developments and this is the case especially in biology with the development of omics techniques but without the sound theoretical background for them and there is also the reductionism that comes with it that is to say for example in physics Jean-Marc Lévi-Leblanc said that the scientific revolution came with a speculative side to it and a technological side to it and the two things interfaced and that was the scientific revolution but today the speculative side is declining and in a sense there is a lot of subcontracting of theorization to philosophers which is a problem because philosophers have also their own stakes, purposes and so on so that's a bit the overall situation specifically in this special issue I argued that what is dominating so especially in biology is something that could be called computational empiricism it's not a doctrine by itself it's more an episteme that is to say computational empiricism aims to describe what most scientists will say is science is scientific research so it's not a doctrine that is set in stone somewhere so in a sense it's more what I'm doing in the paper is more an attempt to describe what scientists consider as science nowadays and this computational empiricism it's so strange, it's inconsistent, id inconsistent it's a strange amalgam between a form of empiricism and more specifically of induction based reasoning and it's actually inscribed in the structure, in the very structure of scientific articles the structure is called femurad for introduction, methods, results and discussion so the idea is to go from a neutral view on observation towards more quantitative results so it's an inductive structure at the same time in experimental biology for example statistical tests are always used to tell whether results are significant or not that's to say whether they come from chance alone or not and the statistical tests build on a kind of empiricism that is to say the classification of a new hypothesis but it's a computational one so it's not a real empiricism of course there is a sharp contradiction between the two things an inductive structure and some barbarian structure where hypothesis comes first so it's a mess to write a scientific paper because I wrote also a few empirical papers so I know that first time too and it's a headache to put your thought straight in this kind of mould and last I will say that nowadays there is also a kind of computationalism that is contrast the ideas that science will deal on logic with logical empiricism or mathematics which is a long tradition in physics and by which I mean effective modernisation that is the same modernisation that you can run on a computer and with the idea also that some things that you could compute with a computer or values that a mathematical model where you can derive theorems so it's a bit of an overview but the point is that in all of this and what is systematically neglected are works that aim to sanitise observations sanitise ideas possibly sanitising them by bringing a new view on things so for example Einstein's special relativity is a way to address facts and theories but by shaping them in a new way but in a sense it's synthetic and it has an epistemological aspect to it the principle of relativity which is about reference frame and the idea that there is ultimately no centre to the universe and so on but those works are systematically neglected the only part in the scientific literature that systematically do a bit of that are the review articles they aim to sanitise mostly facts sometimes a bit of ideas but without being considered original research which brings me back to my point that is to say theory is neglected and the overall result is that so now I will talk more specifically about biology is that the previous frameworks such as the one of molecular biology with the central dogma and so on are in a sense damaged by the observations at the element and the contradictions accumulate without new perspectives shaping things theoretically different and so it's a situation where the biological discourse is weakened and highly inconsistent for example to give an example that is current let's say in the case of vaccine overall the discourse is that you present an antigen and then there is a response because the thing is foreign to the body and then you have an acquired immune response that's the classical theory, the thing is that it's insufficient and actually you need to put, here I'm talking about classical vaccines you need to put some things that is an irritant, some things that begs the body in a sense and the net-juvents and the anti-vax so I'm not talking about COVID but the classical anti-vax there are buzzards or the builds on these adjuvants that are required because the antigen by itself is not sufficient to trigger an immune response so there is a weakness in the theory there are some alternatives to the mainstream theory but they are not good enough so the anti-vax builds on the weaknesses of theories and the inconsistencies that build up in this case in immunology and that's just one part of the problem, of the overall problem so there is a lack of theorization, especially in biology and especially when studying basically life cycles there is a bit more in evolution even though there are also huge contradictions in evolution so what I mean specifically by theory is something that is very different for example from mathematical modelling because mathematical modelling is about looking at a specific situation for example when you look at the earth and the sun you build a model of the solar system, that's the model a theory is more at the level of universal gravitation although it doesn't need to be universal in general so it's a different way to reason as I said the characteristic of theories is to aim to be synthetic to bring together a whole lot of considerations both empirical, mathematical, epistemological, philosophical coming from interfaces with other fields for example the interface between biology and physics or biology and chemistry is very relevant and sometimes applications also can be significant for the way you want to develop a theory for example it's not the same thing to approach biological systems in order to let's say sell drugs which is what pharmaceutical industry lean on even though some try to have a new model because it doesn't work well whereas trying to theorise in biology in order to take care let's say of ecosystems of living humans and so on it's a different approach or starting point and last I give a specific role to mathematics in physics theorisation comes with mathematics since Galileo on Newton in biology it's not the case for example Darwin doesn't use much mathematics even though there are some mathematical reasons that are critical for Darwin's rationale so for me the role of mathematics is somewhat optional and if there is a role of mathematics it also needs to be thought again when we are talking about biology that's for sure and it would be the case also for social sciences so let's now dig in the matter of the theorisation of biological organisations and what I'm going to do is to introduce some ideas that I think are strategic for building a theory of organisms so in biology there is a theory of evolution with its shortcomings but there are some debates but maybe they lack a bit of efficacy for example the alternatives to the modern synthesis which is a dominant view in evolution is called an extended synthesis but it builds on the same concept so it's just an addendum to the classical theory it's not really a new one but I won't focus on that I will focus on organisms themselves so as a level of organisms molecular biology has focused on molecules and molecular interactions as explainants and what is noteworthy is that this view is more reductionist that reductionism itself in Cartesian reductionism you decompose your objects you understand the part and then you put them together and then you understand the wall let's say the machine or whatever in molecular biology you decompose you look at a few interacting parts and then you say you understood so it's not genuine reductionism it's reductionism of molecular biology but as a result there is no theory of biological organization that you could have maybe I don't think it would work but you could have maybe addressed it from a reductionist viewpoint but then you have to be serious about it you decompose, you recompose and then when you recompose you fall back on some things that would be like an organization but since this work has not been done there is no such theory of biological organization that I'm trying to contribute to but now methodologically I think it's critical to address the relationship between what could be a theory of organisms and physics so this relationship this interface between physics and biology can take multiple forms one are let's say a very concrete interface for example when there is motion inside an organism for example cells that move inside or outside you need forces from the point of view of classical mechanics so that's a very concrete interface second come analogies analogies between models so for example statistical physicists work on systems that are not they are classical systems they work for example on schools of fishes flocks of birds and things like that and sometimes it's not presented in a very compelling way theoretically that is to say they claim that it's just physics whereas they take as elementary units birds or fishes which are somewhat different from molecules and have more complex behaviors and moreover they come from a natural history so analogies like that can be very useful because it enables fast mobilization of biological situation but they need to be criticized systematically I think and last come some things that is more at the level of what I'm talking about it's to say the comparison of how you build a theory so it's at the same time methodological and epistemological and with that comes the question of mathematics the role that is given to mathematics and how it's used is justified theoretically and in this way to theorize and to build models too and the main problem I think with respect to biology is that physics understand changes on the basis of invariance so invariant mathematical structures equations that do not change but describe how change will take place more specifically physics understand primarily changes as a motion in a predeterminate space and this space and this motion are structured by symmetries and invariance and this is not very convenient for biology because here Darwinian evolution evolution theory possess the primacy of history for the understanding of living things so it's variation in a sense that comes first and so I do it very very fast but then the point is that we should not organize our theory in biology like physicists do because we don't have the means for that and the means will be invariance and symmetries and a small remark is that in physics the way to conceive the objects is based on what is called and we just pay a long call generic objects that is to say for example when you define the length the length unit, so the meter you use the speed of a light ray in the vacuum and it's a light ray any kind of light ray will do so the way to define objects is really generic and it's supposed to apply to many things at the same time and reciprocally in a sense to do the mathematics you have to be able to consider a whole lot of situations as somewhat equivalent so for example when something is falling in free fall you have actually you are using generic mass m let's say position x and so on so you are not stipulating a specific situation and the idea is that the wall of the free fall can be subsumed with for example one equation or couple equations or whatever few equations and so without the specification of an individual situation as it will be anyway uncountable and so on so you have to do and to work with this kind of generic objects and these generic objects are typically historical and are also decontextualizable that is to say you can remove them from their context and the light ray can be anywhere in the vacuum that you want for example and that comes from the mathematical writing actually because if you think you can capture what is happening causally the system on a sheet of paper in a sense that means that you can really decontextualize your object by abstracting it so it's deep in the structure of our physicist reason and it's a deep problem for biology and so the point is that if we take historicity seriously in biology then we should not consider objects as generic and we have to work with something that we have called a specific object and with that comes the rethinking of the role of mathematics and so to begin a little bit on that the idea is then to state that variation and historicity come first in biology something that we have called the principle of variation and that stability comes second the point is that there is no stability but stability comes second and we have called stable elements so the elements that are stable for example for a time and for a given set of organisms we call them constraints and the point is that they have a causal role but then the stability of these constraints has to be explained because it's a stringent so the relative stability has to be explained when it is postuated in physics for example the stability of the it's an old term but the physical laws or you could say the fundamental symmetries for example they are postulated so they need not an explanation maybe I will skip that so there are two explanations stability in biology and they are complementary and maybe there could be others but it's interesting to read things under these starting points one is natural selection natural selection by itself is not about the emergence of something new I'm just talking about the principle itself it's about as Darwin put it the preservation of favored races so you have first a variation and then natural selection preserves some of these variations it doesn't generate novelty by itself so natural selection can be seen as something that justifies that some things are conserved over time and the second justification for stability is what we call in the organized tradition organization that is to say the mutual maintenance of the parts of an organism so the way to do the short history of that is for example Kant and in modern times, Rosen Varela with the utopiasis and the paper that you mentioned which is really in this tradition and I will go fast on that but these two ways to discuss stability in biology, to justify it are also two ways, two philosophical ways to interpret biological functions there is a natural interpretation of biological functions as something, basically something is functional when it has been selected due to its effects and something is functional from the organizational viewpoint when it is in an organization so that it maintains some things that maintains some things and maintains itself so that it's here due to its consequences in a sense so that's two interpretations of function I think it's interesting to have that in mind and here we also have an interface with the principles of physics that is to say biological systems are far from equilibrium systems it's interesting to say that in Belgium because the compagny is not too far was not too far and the biological systems, biological organisms have to last far from equilibrium but it's not that they are just far from equilibrium they are also in a non spontaneous configuration far from equilibrium and then this need for justification for how things last over time and biology really makes sense from the perspective of physics but go beyond physics because of historicity well I'll skip that but just that's just a schematic of the closure of constraints so how constraints can mutually maintain each other by acting on processes of transformation and the point here is the circularity of the drawing so now if we sum things up we have with this very very short sketch of what a theory of organisms could be we have constraints and that's the thing that is the most classical in a sense because it's closer to physics, it can be used to do mathematics mathematical model and so on in a traditional sense but at the same time these constraints are part or are related to something that we could object that is to say objects that cannot be defined just by constraints that is to say by causal relationships instead they are determined at the same time by historicity, context and random events now I will give three more specific leads on how to move forward once we have this in mind so the first one is, sorry I didn't present that the first one is the question of measurement I will define more specifically what that means the second is how to work with this kind of changes that are not the same kind of changes let's say that the one that takes place in physics, that is to say the one that are subsumed by invariance and symmetries and the last one is a way to write or to precise the schematic to do some kind of formal work in a new sense of the word so the first thing that I will discuss on its longest discussion here is the question of measurement and I take measurement in a very precise way because the question of measurement is very broad here I am taking it in a restrictive sense the sense of the structure of the theories and the idea is that in physics at the level of theoretical principle there is a definition of how observation and theoretical description are related, I will give two examples the first one is in classical mechanics the idea in classical mechanics is that the state of the system is a point in the possibility space, in the free space but this point cannot be measured with infinite precision it can only be measured with limited precision and this leads to the notion of deterministic chaos or deterministic predictability because even if you have a very narrow very precise measurement, the trajectory can diverge very fast it's related to the principles in this sense that it comes from the measurement the unpredictability the second one that maybe you probably all know a little bit is the question of the quantum measurement it could say that it comes from the articulation of a macroscopic object, at the end of the day it's a person that measures and a macroscopic object the quantum system and in this case the measurement is more structured it's more complicated, it can yield different results with probabilities and most importantly it changes the state of the object, when you measure you always cannot change your state so that's two kinds of theoretical notion of measurement that comes from physics and in biology there is no such notion which is a probable reason why is that molecular biologists could focus on discrete structures like for example the sequences of DNA and so on so there is a lot of mathematics to discuss whether the right sequence is obtained in a specific device and so on but in principle a discrete structure you can measure it exactly, it's not like a continuous position for example if there is a text here you can read it exactly, the structure of the text you can work over each letter and what is neglected here is the rest of the biological system to say the organism and the point is that the organism has to be addressed when measuring the biological system but I will come back to that from a more theoretical perspective what is going on is that in physics we have these invariance, these symmetries, these equations and the outcome of the situation is that measurements only need to address quantities, at the end of the day the experimental physicists obtain quantities about this system and ultimately it's the state of the object that is defined as the position in a possibility space in biology since the constraints change, since the nature of the object changes over time the measurement has to address quantities true, like in physics, but also changes of constraints, changes of relationship between constraints and also the uncertainties that result from that so this is the uncertainty, it's something that is very practical for example back to the Covid vaccines when or more generally in clinical trials the challenge always is that you are testing a drug on a small sample of the situation and you know that the rest of the population will have qualitatively different features not the whole rest of the population but some people in the rest of the population will have qualitatively different features and will possibly exhibit side effects like of potency or whatever so that's something that is known there are some processes that are organised on the basis of this knowledge but it's not really theorised as such so that's in a sense the aim of this part of my talk is the glimpse of how it can be theorised so as I said, the point is that the measurement does not refer only to a part it must accommodate organisation in their context if you have this scheme of our biological objects work and the physics like measurement is only about the observable constraints and so if you only go with this concept then you are neglecting all what is below and so to address this part of what is below that is to say the specific object I've introduced the notion of symmetrisation so symmetrisation would be to make equivalent objects that are not genuinely equivalent and that can be made on the basis of their history those are past on the basis of their context and also on the observation of some properties and well it can be very concrete in a sense by transforming the objects or it can be only at the level of the description of the objects so it can be both concrete or theoretical so let's give some more practical aspect to this notion of symmetrisation even biophysicists would tend to claim that biology is ultimately physics when they are doing experiments, let's say on chicken development they have to talk about chicken so the trick that I always put in debates public debates is to ask them what chicken is and usually they don't have an answer for that because the answer to this question at least in the current state of science doesn't fit at all with the epistemology of physics the answer comes from systematics, the way to classify living beings and the main method in systematics is to classify living beings on the basis of their historical origin and it's really a completely different epistemology from the one of physics and it's still a rigorous way to classify living beings and it's a very complex way to classify living beings and it's a very complex way to classify living beings and it's still a rigorous way to work with its shortcomings too but it's still a rigorous way to work what is interesting is that to do this classification it's mandatory to have specific concrete objects as a reference point for example the names in the systematics for example for Ratius Norvigicus corresponds to a specific sample color type that is kept in a university or in one of the various museums of national history and that's very different from physics again I took the example of the speed of light to measure the units of physics you refer to theoretical situations first and then you can instantiate them in for example Le Maitre Talon or whatever so in specific objects but if the specific object is destroyed so be it let's build another one and it should work because ultimately the definition of these units come from theoretical invariance and ultimately the definition of the names come from a specific object, a concrete object so it's a very different architecture, theoretical architecture and it's a way to build on the historical aspect of biological objects and without making the huge jump to say that it could be reduced to a more physics like approach by invariance, symmetries, equations and so on so well I will go fast on that but my point is not just to lean on systematics in concrete experiments with strengths and so on or with cell lines actually biologists use a lot of tricks or methods to control not what the object does but the fact that they come from a single control of origin so for example when having a clonal population of cells to do experiments on them phrasing them to stop time and prevent variation and so on so those are all tricks that enable to control both the origins the fact that it's relatively recent and so on that's again an illustration of that that's all my strengths that are used in laboratories so that's all the same species and the point is that this part on the right it's just the top here of group 4 so you have a gazillion of strengths the point is that even in laboratory conditions in animal farms biological objects never stop to change and these changes impact the results of experiments so if you want to repeat the experiment to reproduce them you need to control as much as you can the historical origin of objects so the point is that there are some things that is discussed at the theoretical level usually these historical definitions of the concrete objects you are working with in experiments because most modelers come from physics some things that has been built on in experimental practice and actually there is no other way to do things at least not for a long time so the point is that these different strengths can have dramatic consequences so for example in rats the MBA which is basically a chemical can lead to 0% of tumor among the rats to 90% of tumors among the rats depending on the strain that is used similarly underground descriptors can have various effects on the strains notably because some strains are selected to be prolific being prolific is something that has to do with the hormone system so those differences in strains can ultimately have consequences for regulations against carcinogen or underground descriptors so it's not benign I will just take two points from this slide something really to have in mind is that to repeat an experiment in a sense in biology you really need to work on two objects that have a material connection a genealogical material connection it's not the same at all than in physics where you can work on objects that you can generate completely de novo like trace for example so that's something really fundamental and that has a challenge for theorization the second point is that in this context you can see the situation as leading to different measurement strategies one strategy for example is to aim or to strive to do to get closer to physics so for example aiming to have basically to repeat experiments on organizations that are as close as possible to each other having a very strict symmetrization as strict as possible so for example when working on a clone of a population of cells when restricting to a very narrow strain of rats and so on those are all strategies to try to make the object as similar as possible and the other strategies are never exactly the same and there is always a diversity that is generated at its generation with development so that's one strategy but the strength of these strategies is that sometimes it leads to more reproducible results not always and the shortcoming is that it leads to results that are very specific to these organizations for example there has been a huge debate for no exception in mice because the mice that have been used are specifically have a very specific way to address pain and so on so the results are highly specific and when for example working in pharmacology and aiming to do drugs for humans and doing results for a very very specific strain of mouse or rats does not really correspond to the overarching aim so it's interesting now to see all these different strategies in a continuum, in a situation where anyway you have to address this historicity of biological objects and there is a way to define biological objects I don't know how much time I have 10 minutes but you could take 20 if you want ok I will go first on this part because I would like to skip to the next section one other challenge very quickly is to work with a notion of new possibilities it's a notion that in a sense comes from philosophy I'm thinking especially about Berkson and it has been reused or reinvented by several theoretical biologists including Stuart Kaufman and independently by Jose Pellongo and then I worked on it too and the idea is that there is some specific things to address if you want to make a scientific concept out of the notion of new possibilities because the possibility space in physics can very well change it's not a problem it should take the gas in this room there is some gas, some molecules that come from outside and so on so the dimension of the space that you use to present the gas in this room fluctuates that's not a problem because it's more of the same the problem in the new possibilities in biology is that this new possibility corresponds in my view to things that are qualitatively different and typically new functions so my point is that the concept of new possibility has to be specified in this way and also to address some possible contradictions but what is interesting is that having this idea in mind that basically all mathematical structures that you use in biology correspond to ultimately to constraints that can change over time it can also lead to new techniques to lead to specific or new kind of prediction these new techniques that I call them deconstructing models the idea is that if you have mathematical structures that you use to describe part of an organism then you can always look at alternatives at the level of these structures and see if they are met empirical so a very simple example is a hand made of rats and is typically described as a tree as a mathematical tree which is an acyclic and connected graph and what is interesting is that then you put the negation of each of the hypothesis describing a tree and you investigate whether it is met empirically so for example acyclic as the opposite is having a loop so there is one here there is one actually in a fair part of the sample that I have so connected, well a part that would be disconnected so it's not the right word here and there is one here actually and it's my own empirical discovery although it's not published as such but because people didn't think that it could be possible to be disconnected so here is also a close up of this disconnected part so it's really epithelium and it doesn't seem to be an artifact of any kind and then when you have a graph it's an object that is made out of nodes and edges and there is two negation of that it's the existence of things that could be a connection or could not possibly for example when you have a duct that touch but without merging so the lumens do not merge but they touch so it's an ambiguous thing but the most important one it's not in the picture, it's the case of tumor, in this case you really no longer have a node on edges, you no longer have so the point is that very simple case, very simple mathematical structure that is not properly a model because there is no causation here it's just a structure but just looking at the negation of the hypothesis that construct this mathematical structure leads to possible predictions that can be tested empirically and here I will go very fast on this but it's a recent paper that we did with Matteo where we introduced in the schematics for closure a new symbol precisely to accommodate what I was talking about for the measurement that is to say aspects of an organism that are only defined by historicity, past context and so on the elements of the objects that are not defined by constraints, by causal reactions but that are defined by the past and the idea that this symbol so written chi is a very strange beast in the sense that it's not really a formal construct like mathematical constructs and so on and I call it a symbol because it refers to a concrete object I told you for the classification for example that it was always by reference to a specific concrete specimen kept in a very specific location and so on so this symbol is a symbol precisely in this sense that to make sense it has to refer to specific objects and then one aim is to use it to enable constraints of closure to address more of the historical aspects of biological objects on one side but another aim is also to describe more specifically how biogists do their experiments because the way they do their experiments which takes planning over several generations of mice but of humans for example are manipulation of the chi aspect and only of a few constraints that is to say checking weight and so on of the animals so it's mostly by manipulating chi over time that the experiments are defined I skip that and I just say a few words on another project that is a kind of application of everything that I have said but at the same time it's a very current application so this project aims to theorize the notion of disruption in biology disruption is used a bit the world, disruption is used a bit everywhere it's used in ecology for example for plant-based networks it's used in physiology since the 90s for endocrine disruptors for development and it actually gains more and more weight in the scientific literature so here it's in ecology and the point is that it's not theorized as such as there is the notion of perturbation in ecology that is not always just one in physics because perturbation in physics corresponds to very specific mathematical techniques but there is no specification of the difference for example between perturbation in the sense of physics and disruption whereas the use seems rather specific so part of my project is to make this use more explicit to distinguish for example perturbation and disruption and at the same time to develop new, possibly new mathematical models or new theoretical insights to address this disruption under the assumption that there is some aspect that are common to all of this disruption all of these descriptions so the overall assumption is that making this notion of disruption more precise will require something like a theory of organization and that is more specifically at the same time addressing systemic aspects or organizational it's a case of organisms and at the same time historical aspects pertaining to evolution or possibly to development and once you take historicity seriously you are really no longer in the epistemology of physics so then you would have a concept of disruption that is really different from perturbation in the physics sense perturbation in the physics sense is really you have something that is at equilibrium or stable you disturb it a little bit and then you analyze what this little perturbation does so one interesting example and I think after this example I will have stuff one example is in ecology I took it as a flagship example because it's the simplest one actually so in ecology there is a study of phenology phenology are activities that are seasonal flowers that bloom in spring and insects that hatch at the same season the point is that the climate change transforms this phenology and if this transformation was the same for all species in an ecosystem then it will not change interactions everything will take place a bit earlier it will not change interactions the thing is that empirically the way this change takes place is very random for plants it's a bit more uniform to say more plants are active earlier in the year but for our planet Earth it's quite random and there is a reason for that it's somewhat clear that different species use different clues to start the activity in the year some use the photo period which does not change some use the temperature of air, of soil and so on so all of those change differently some use the snow cover and on top of that plants tend to have some kind of memory from one year to the next and really it's a mess and the result of this mess is that the different species are desynchronized and since they are desynchronized some species are in trouble so for example initially pollinators attach some plants to pollinate during its whole activity period and after a change in the year you have two periods where it has nothing to pollinate so according to members and colleagues but it's a whole field of research really this will lead to 17 to 50% of pollinators in a specific ecosystem to disappear but what is interesting here is to go towards to investigate the structure of the measurement here what matters is that the initial configuration to the left is very specific with respect to activity periods in a sense it is highly improbable because for every pollinator and every plant in an ecosystem to be in a viable situation is very unlikely then this specificity has a systemic meaning the meaning is that all populations in the ecosystem are viable here through their interactions the pollinators feed on the plants the plant reproduces things through the pollinators so it's an improbable situation that has a systemic meaning and then what happens with the disruption is that this specific configuration is becoming more random more generic in a sense and as a result it is becoming less viable so the point is to have a specific kind of reasoning that builds on historicity that is distinct from physics because historicity is the key argument to explain how the specific configuration that was viable initially came about in physics it's really if you have to give specific initial conditions or specific value of the parameters to explain something then you are in trouble you have to work with generic values of the parameters or otherwise have proper justification so here the proper justification is the historicity of the system and the idea that the ecosystem builds themselves over time so it comes from a viable situation to a viable situation so you have a short schematic to be a theoretical notion of disruption in this situation that is the simplest one that is to say history and the pre-evolution lead to a situation that is very specific, very unlikely and of course it's an answer to a situation of viability through the property of the system and with a disruption you have a more random situation with a loss of viability so I will skip on this but when I said improbable here it's something like 2 power 1 over 10 power 500 so those are the random configurations that you can get the idea of all species will be the zero that is on the top left let's skip that that's just I will mention another case which is OK for the grand descriptor so here the schematic is a bit more complicated because you have to introduce a developmental time into the picture but what is going on with the grand descriptor is that one part of the organism which is the Hohmann system regulates the development and is becoming more random due to this chemical that alter its effects and as a result development is altered and there is a loss of functionality so a good example of that is the ethylene bestial and the S which is a chemical that was given to pregnant Hohmann as a drug and leads for example to malformation of the uterus it's called a T-shaped uterus and there is basically no space for baby to grow so you have an ectopic pregnancy the baby grows outside of the uterus which is extremely dangerous but you can also have typically cancers the tissues are a bit disorganized and so on and that's what I mean by random it's not random in the sense of quantum randomness or whatever it's becoming more generic so it corresponds very well to the Boltzmann scheme for example they don't develop that but it's becoming more generic with respect to an initial specific situation and last because I don't want to skip these parts is that so what I've talked about for now for description is what could be called first order description there are also second order description first order description is in a sense losing a part of what history brought to organisms to their ability to live and so on second order description is the loss of their capacity to produce new possibilities to bring a novelties that contribute to their variability and a good example of that is the description of the contribution of evolution by natural selection to viability by habitat fragmentation so what happens is that I said that the elementary notion of evolution by natural selection is only about conservation but if you take dynamics then it can contribute to the emergence of novelties so there is a need of having a genetic diversity you need a diverse population and then this population can respond with different fitness to a given context and so on the point is that with habitat fragmentation you can have a huge population that does not collapse but that is cut in small parts where gene flows are no longer possible and then each of these parts evolves as an independent unit and the thing is that with a small population genetic drift take over and there is a spontaneous uniformization of the population then no longer diversity and then natural selection can only play any kind of positive role in evolution so it's really the description of the capacity of living being to produce functional novelties here through the evolution by natural selection but there is another case which is interesting is that so here at the interface with psychology is that in the relationship between parents and their baby there is a very interactive relationship where the parent accommodates the emotions of the baby to create kind of pseudo-narratives that prepare long ways that prepare real narratives later on so here I am talking about very young babies and when they are old for example and so this improvisation of the parents is critical for the emergence of language afterwards and the emergence of narratives afterwards and when smartphones or tablets are used to display movies even to display little songs to you to use little songs and so on this interactive part is no longer here because the program or the videos do not accommodate the state of the child at a specific moment so there is a description of this interaction and the fact is that the overuse of digital media for very young children is formed upon by pediatricians and it leads to long-wage retardation difficulty in attention and difficulty in relationship between with other people so that's another description it is more at this dynamic level thank you for your attention general question you said it was very different from physics especially because we cannot find in biology symmetries and invariants but I wonder if the argument will apply to all fields of biology the same way for instance if you are considering spices, evolution or maybe sense of my food biology or climate it seems to be a different framework at least for me as an unexperienced in biology so I wonder if we can see biology as a number of theories in which we will find different strategies or does it make sense to consider biology as a limited science and with the common grounding for epistemology I just wonder and specifically the argument of symmetries and invariants maybe it will be applied differently in microbiology and spices I would say what enables to put all of biology but in a sense also human sciences here is the notion that historicity is central so if you start from that then it is a commonality between all fields of biology but it is also the case it is safe for economics so this part of the analysis is very generic then for example here is the notion of organization it is primarily for organisms so that would work for cells too but for ecosystems it is something that is under discussion in the literature but some aspects really some aspects of my talks are very generic precisely because I am working on the architecture of the theory and how you can use mathematics or what difficulties there is in using mathematics but other in a sense more specifically constructive parts like for example the classification of living beings that is for species for organisms for ecosystems it would work differently but the problem is that and I don't know I think it is a problem for ecologies too how to define ecosystems but the problem is there because it comes from these general considerations that would be my answer but the idea that possibly there will be invariance in some subfields of biology I am doubtful there are some things that are some constraints that are shared for a longer time that are more stable but ultimately there are always cases that exist for example there was in the 2000s a lot of claims about a new law of nature being the allometry of living beings allometry is how in this case it is our metabolism related to size specifically the mass oxygen consumption and the idea is that there is a regularity that spans a lot of order of magnitude for example in plants from the unicevillard to the baoba but at the same time you have a lot of exceptions and the exceptions in this regularity it comes from a specific evolution like mass and so on it is not an invariance that you can use like in physics so I ask this question because when I was in engineering we had some classes called applied biology and there was absolutely everything everything related to equation so for instance we had all the teach people they said you can use equations to modulate every possible biology and for instance we had population theorization differential equations and in these equations it is easy to find some kind of invariant once you have a differential equation you look for it so I agree with you it seems very naive to say that equations are a biology but I think in the mind of people some fields of biology can be reduced to equations so maybe it is too hard to see it's true another example was the eye it was a model I had a complete class about modelizing eyes movement saccade which are micro movements and so it is related to what you call empiricism computational all was about feedback loop to explain this eye movement but that was called biology so I just wonder is that biology or is that something else is there a different way to look at biology I don't know I didn't specify that in my talk but in a sense one of my aim is to have a more general and consistent view on biology in which mathematical models can make sense but can make more theoretically precise sense so with the notion of constraints the aim is really to accommodate the classical models but to reinterpret them I have in mind our quantum physicists reused the classical potentials in their equation but giving them a completely different meaning but still reusing them because we don't work from scratch so in a sense things that work in a way you have to make justice to the fact that it works in a way that you have to specify the way in which it works the limitation and so and that's the most part first I would like to thank you for your talk because I often argue against my only dare that biology is the creative science and physics is not and you usually disagree but now with all the arguments you provided me I won it's finished but my question more seriously so how do you see there's some branches of physics that are more historical more specific cosmology, climatology they don't seem to have the same paradigm of modellization than biology so where do you see the convergence or the divergence between these historical part of natural science and geology more and more specific more about historical objects yes well I'm discussing mostly at the level of the structure of theories starting from that and the fact is that for example cosmology is a difficult thing for physicists themselves because it's it's not genuine yeah there is some kind of history that take place and that is very difficult to address including it comes also from technical aspects in the theories and so on and so since they don't know exactly where they are and it's not my problem in essence but I know that there are these challenges including in physics now in biology there are more specific things that we have that is to say the relation for example to the notion of function with a double sense that it can have evolution, genealogy all those are concepts that can be used to flesh things out a bit more in biology and and then there is a question of geology provided that geology can be more towards physics when it's not earth to knowledge and when it's earth there is biology involved quite a bit because a lot of earth dynamic at all time scales including rock formation from biological systems so in this case it's it's just to give you more material in climate climatologists just discovered biology recently in the model and now they include it in the climate model but they always include it as an external factor or something like that that will perturb or do something on the model because it seems that it's impossible for them to think as a a model with a genealogy in it to just think about that so you have to externalize in a certain sense the creativity of biology in the model yes so in the moment it's going there I suppose one day they will say okay to have a good model we will have to include more of the creativity in the feedback and all that of life and just putting it as a factor in the differential equation and the same can be said that the human level because there are different scenarios for example for human emissions and so on and those are in a sense initial conditions or boundary conditions in the models and so the human part of things is put as external to the understanding of what's going on while the phenomenon is one ultimately and it would be interesting to have an overarching theoretical perspective to for example address things that seem to be sure but as a human living seems as a launch and so on yeah I of course like it we can talk forever about this this is really cool so thanks the one that I wanted to start with though because I think this is probably the most provocative thing I have to say so I think you're right I think looking for symmetries and invariance in another good way to put the same point is when the nature of the ontology itself is also being molded by the biological processes at work then yeah you're not going to have some sort of symmetry coming from space so I think that's your spot on and I like a lot of the arguments but there's another source of stability and structure in physical theory that a lot of people apply in biology that I didn't see here and that's large numbers in universality and statistics so I wonder how that fits into how that fits into your story the idea that if we if we want to tell this story about particular interaction we're going to have a very hard time looking for biological laws about them but if we have enough of them we have populations composed of a large enough number of stuff well that puts us in the same kind of environment as thermodynamics that lets us start to abstract from the behavior of the individual organisms the behavior of the individual that Fisher did with genes I mean I know that's an album of it obviously good reason to not do that anymore but Fisher thought that would work with genes so I wonder what you think about that as another way in and how that kind of perspective interacts with the way that you think about what's going on here so actually large numbers by itself doesn't mean anything in my framework it will be a number with some constraint that is maintained between them and then it fits in the more general category of things that you can deduce mathematically when some constraints are there then the interface with reasoning a bit like in physics maybe more investigation would be required to check if it works well by analyzing things like that but I would phrase it like that now in practice in an organism for example large number doesn't occur that much in the sense that even numbers of molecules in a cell some molecules are in large number but a lot of them are in very small number precisely and it's a source of randomness and then what happens inside the living beings typically is that there are walls everywhere so that in a sense from the point of view of the term of the dimension of the point of view of people from the perspective of statistical physics and so on it's basically all the conditions that are there for the situation to be bad to make mathematics and in a sense it's kind of logical because it is that that enables living beings to change and so on but locally it can happen that large numbers going towards more generic situation also makes sense biologically for example in cells when proteins are produced at one in the cell it is the random motion that brings the molecule to the receptor so it's a purely entropic process but that can be functionalised in a living being so actually I thought you would have another question which is that some constraints are given for free because they come directly from physics principle that's another interesting idea that's not one that I've played with as much but that's also very cool yes and then there are those that come from combinations of constraints and deduction sure that's great, that's all the plans it's really helpful it's less a question than a comment because you're very right that most of the time when we see a change in the phase space in physics it's more of the same it's just you open the box but there is exception to that and it's a recent exception it's quantum fluids so almost all the last Nobel Prize were all for quantum fluids and in quantum fluids physicists are exactly like biologists it's very funny because they cannot do a model they just say there's a change of the political order it's a kind of bizarre thing that means nothing in it because it's regular so you pass from some kind of physics to another kind of physics but there's no reason no model nothing to say how you pass from there to there here you can modelize but not between the two and some Nobel Prize they argue this is pure creation physics finally creates something it's as never happened and nature you go a little bit out of the very framework of physics like all the potential here we can modelize them just an epistemological question now there's creation of new particles but but it's reproducible so you put the system in the same condition you will get automatically the same thing so it's like in your mapping it's a specific object in the sense that the passage is not the same it's not modelizable we don't know how how you can pass from this to this but we control the constraint because it's reproducible so there's not the historical part on the left but you have completely the center of your graph and it doesn't look like physics I have to say that when you read the papers and the journals and the physicists that discover first these quantum fluids and one Nobel Prize all of them we don't know what is happening it's completely new it's pure creation and sometimes they almost sound like that song which is not physics so I'm curious about this I should maybe take more attention to your model because in what part the historical part on the left is essential to biology I suppose yes but the creative part in the middle the type that you can pass from constraint to constraint in a non a real change of phase space the creative part it could be found outside biology outside historical science but maybe not in historicity because you connect historicity and closely let me see you said variation in historicity so in what way these two are necessary or you can imagine cases where you have variation and without historicity and it would be not biology but it would be not physics too that's a difficult question I integrate variation in historicity very tightly like an object maybe variation by itself is not sufficient to have historicity and there is a part in which we don't talk enough yet but it's a question of what could be called memory and ultimately it's not just that but it's reinterpreting DNA and its role in biological systems without the notion of program at all but looking at DNA as constraint which is reasonable and it works well as an example it works perfectly well but it's not just any constraint it's this role of constraining for example development all along the development it's a constraint that is there and enables to somewhat reproduce a complex process how much it is reproducing it's a big question but it is at here but for me this novelty without some kind of randomness or contingency it's difficult to think because if it's reproducible once you find some way to give a face space or something like that but I don't know this situation so I'm hopeful but you could what is weird is that I'm giving more information for you to have an answer what is weird is that you have a face space before you have a face space after it's under control but you have a reason that we will never find an overreaching theory you have this is why they call it topological order because it seems that it's a bit destructive something change and if it's not continuous physics is unable to treat that because there's no differential equation it's measurement that is a problem but the evolution is even a linear function so it's under control so it's the case that do not map you know a face change or things like that it's almost discontinuous but it still continues these are it's why they use the bizarre world like topological order to show that it's unpredictable but it's reproducible which is strange because it means that there should be a regularity that we should be able to model that's interesting in my paper on new possibilities I made several distinctions not to be two blocks of possibly fallacious argument which will be in Bersonyan terms a retrospective move to say projecting the future on the past which is always a way to say that nothing new happens and to do that I introduced the notion of actual possibilities which is almost a contradiction by itself but it's just these very simple notions that there is my arm here with a muscle and so on going here is an actual possibilities because everything is there for it to happen and in a sense it's mathematically generated by the constraints that are present now so this position was an actual possibilities even before it happened and the idea is precisely that new possibilities are not actual possibilities and what's your paper you wrote distinctions maybe it is based on the notion of novelty it was in Santès in 2019 I think I took a photo of that satiation I can send the slides if you want but so I'm wondering if that would correspond to the situation of the physicist because it's precisely that you could cheat maybe not maybe you could cheat by putting things that are in the end result in the original situation but things that are measurable at all so it would be cheating but you can have more contradictions than that you cannot even do that because the future state are forbidden in the laws governing the previous states so it's why physicists tried all kinds of more effective theory to make sense because it looks like pure creation it looks like biology but it cannot be because it's reproducible yes maybe biology is reproducible it's very very very complicated I don't know these are complicated things that can be reproduced but then it's more at the level of some constraints the case of for example the shape of the wolf that is in English basically you had the wolf of Australia and the wolf here that everybody knows that are roughly the same body shape but they come from different evolutionary paths so this kind of convergence constraints if you think that there can be repetition at the level of constraints what is not repeated is the bulk of the complexity of the organism that is quite different different physiology different systems and so on but at the level of some constraints there can be something that can be repeated and articulations of constraints and environmental constraints and so on repeat only two similar results the same work for the AI and it's funny because at the same time the convergence is strong and at the same time the traces of the past are also strong for example in the octopus the vascular system is below the retina whereas in your case it's in front which is not very logical that's how it is and that's the traces from the history thank you for your talk so in the beginning of the talk you made some variance between physics and biology in terms of understanding via invariance and variance so in physics the idea was that fundamental invariance needs to be explained in biology and I found that I had the feeling that you want to keep the parallel or think that invariance as constraints could also be read as fundamental and explanatory is that more or less what you yes the idea is not to get rid completely of the notion of having invariance and so on because without that there is no possibility of doing mathematical models so what I'm proposing is to reinterpret for example the invariance that I used in mathematical modeling in biology as constraints and then constraints have different properties than the invariance of physics so for example they are in an organization that sustains them and that they contribute to sustain and they are taken in this history which means that they can have a historical origin and change so they have some level of contingency in that sense so my follow-up question on this is whether you think that you want to really see that as a BFI thing as something that reflects reality or under a very crude epistemic principle in the sense that or basic level of explanations even in folk psychology to explain somebody's behavior they always seem to fall back on fixed things invariance for instance somebody's character trait in combination with varying factors with the help of which so in character traits we try to explain behavior that seems like a very crude epistemic principle while for instance in physics one has a tendency to rather reify these variance let's say laws or symmetry principles and I wonder then is the parallel between biology in physics and rather something superficial in that respect I'm not sure about the question but I will say what is clear is that in physics the invariance they are not they have a deeper meaning it's not just an ad hoc postulate with respect to a specific question they get a deeper meaning when they are embedded in a network of mathematical results empirical results and so on that gives them meaning precisely whereas even in genetics postulating for example the genetic code as an invariant in a sense it was just an ad hoc postulate that connected to the emerging information theory and so on but it was just ad hoc and actually if you look at DNA sequence protein sequence it's not just a genetic code so it's just the genetic code correspond just to part of the process of protein production so the invariant is not invariant so my the main difference between physics and biology I think would be that the invariance structure the theories in physics and because kind of works on one side and a lot of work is based on it or built on it they have a very deep meaning even in theories that are no longer let's say at the forefront of what is going on in physics I mean for example classical mechanics it's many ways but at the same time it's mathematical and theoretical structures give a lot of meaning to the invariance that are there including noether theorem for example that came relatively late with respect to classical mechanics but deepened its meaning and able to interpret some invariance yes at the level of the structure when you compare the structure of physics and biology and when you talk about causality both it's a question that I already asked you online but as was online we did not have the opportunity so to what extent causality in non-living objects are the same or different from living objects all that's a question because causality is not simple by itself already in physics it's not simple but actually there is a similar issue with respect to time I would say the situation in physics is that causalities are addressed through the mathematics or by the use of mathematics or if you want to talk in physics about causality without referring to mathematics you are in trouble right so it gives a specific spin to let's say to the causality question and in biology you don't have that and at the same time you have something that could be somewhat specific to biology which is what happens in terms of causality when other things appear and that will be a specific kind of causality relationship between the initial situation and after something appeared that will be different from what's going on in physics whatever is going on in physics so that's what we called with Joseph P. Longo on Stuart Kaufman enablement from my point of view the originality of enablement is precisely for this kind of processes where you have something you cannot at all deduce what will happen from this something because it's really something new but at the same time without the initial situation the new would not appear so there is something causal about it and the relationship to what is in one of the process but there to say that there is no entailing laws so there is no entailing law that from the year was somehow saying there is an entailing law and you are saying no it's not quite it's enablement so it means that in terms of I mean I think in a formal way how you can phrase this enablement without having entailing causation behind without having without being entailed some kind of causation I will say in practice with the simplest terms is to say that it's causation that can be seen retrospectively at least that's how evolution is doing is to say you say this bone and this environment to the emergence of whatever so retrospectively you can you can do like that now how to frame it exactly and precisely with constraints and so on it's a work in progress yeah so thanks a lot for a great talk so I'd like to so most of the talk was about the structural theories you made a very interesting point that the states of the or maybe generalizations is very different in structure of most theories in fact for example in physics and it draws an interesting parallel with the social sciences and the human sciences with the idea that history is bigger but my question is what are the consequences for the topic of scientific explanation because it's so one view is that whatever the status of of generalization there are things that do the explanation I understand something when I can put it within the question of generalization or environs whether that environs is like for deep like in physics or it's just a local environs that is title specific like local constraint that's right for the system in a certain context it may disappear later but I understand something when I can some zoom something under a certain kind of environs and if this is so then there's not a big change in terms of how we explain things it's just that because it's still always down to 60 million different environs but if I so another view is that if I take very seriously the historicity of biological objects and phenomena it looks like environs won't explain a lot because if something changes I won't understand by just isolating environs and doing them in their environs so I guess my question is how does what you proposed it in the literature on scientific explanation so do we need to find out a new model of scientific explanation more directly to historical phenomena I know that sounds like a transfer of historiography I had a hard time trying to find in the field of physician science to ensure some good photos to explain what they are doing when they are in the historical phenomena and it strikes me that in cases of biology where explanations are no mathematical control they are many more rigorous than in three books could be a way to find some insights into this but ok how my question makes sense ok so I think so again it's the few questions there is an easy answer is that in my view you can always talk about some constraints to each other but then when you have to refer to real logical objects you have to introduce all the mess with Kai and so on but you can still have reinterpret it but still kind of classical explanation but second kind of answer would be I'm not sure understanding requires the invariance that's I'm not sure if it is so I'm in in doubt and for now I practice apok here but it's it's a very relevant question it's very close to what I'm talking about but for now I don't have a strong position and there is the issue of being able to accommodate a singular situation scientifically that is behind it it's a bit everywhere it's there in history but it's there in medicine too it's so it's a big problem and the bias towards let's say statistics for example in medicine can be also interproductive when not building on also the individuality of the patient so there is some precise things and the last part in my answer would be that sometimes I used it but sometimes I'm uncomfortable with the notion of explanation itself I prefer in French that will be understanding but in French comprehension means taking together which relates to my initial statements about synthetic work and in a sense too much focus on explanation itself goes a little bit with computational empiricism in the sense that explanation can be local very very local and uniquely local whereas understanding means taking together so it can be understanding a specific situation but with respect to evolution with respect to physics and so on so you can have the global in the local in a sense with understanding and so that's why I tend to prefer understanding and maybe that would lead to raise the question a bit differently if you don't have to explain but when it goes down maybe the problem is a bit different Ok, many things but that was great I was going to add something related to the symmetries but now I want to just add something about the last part to say because now I even get confused it seems that there are two tendencies that are pulling into opposite directions what is the idea of understanding that they want to be general to comprehend the things from a very wide viewpoint on the other hand you have the idea we have to be now specific we have to working on concrete things and all being discussed and now to say that this is something more related to knowledge or not it's not really understanding but the way you phrase the idea of understanding more or less related to what sometimes physicists do when they try to idealize a system try to come to get a very general relation that they can get so the specifics don't matter any longer because you want to get the main relations so I probably am confused how can you combine these two views specific on the one hand but on the other try to get understanding because if you want to get understanding the specifics you should just abstract away the specifics and not necessarily say that because even if you take understanding as doing something like a synthesis as a synthesis doesn't have to be general you can I don't know address something we talk about development in biology for example it seems huge at the same time it's something that appeared in evolution and usually we focus on mammals so it's even more specific and so we are actually working on specific objects and development in plants is quite different from the one of mammals for example so so this this matter of specificity is everywhere in biology but it doesn't prevent understanding in the sense of development of mammals is specific but still you have to articulate that to physical forces to morphogenesis theories and so on so I don't think you need to have general invariance to need to understand but then there is another layer to your question it's at the level of what I'm doing concretely so for example when I showed this this thing by itself it's not a model it's a sketch of things that could be more concrete but in an application Kaien would have to refer to a specific biological object a concrete one ultimately because names depend on concrete biological objects so Kaien would really be a symbol and the idea to put symbols to specific objects not to generate quads is the way I'm trying to accommodate this contradiction at the level of something that could be a formalism but not exactly because there is symbols in it so it's not genuinely a formalism but a hybrid construct um um and then um no okay same just one minor point what do you exactly mean by concrete object probably that was confused to me but at some point you said that in some part of biology we are dealing with concrete objects but you show for example with the view that the word almost happens for me almost happens it's not a concrete object it's an abstract object no it's not for me it's a kind of natural kind of whatever you want my question is for you it's a concrete object it's not at least in the standard way to define to define objects in the classification in the classification the name is attached to a specimen a single specimen so there is only one specimen with the name ratus norvegicus or homo sapiens I don't remember who it is for homo sapiens but uh I think it's clue here but I can check afterwards in Wikipedia but it's always a single specimen sometimes there are some tricks sometimes it's a drawing but basically it's a single specimen it keeps the name it's called the name bearer type and then the name is propagated to living beings that are closely related in the analysis in the fugitive analysis so it spreads from one single specimen to a group but the idea in assigning it to a single specimen is then if there is a reconsideration of the group due to some discovery and the group is split then the single specimen tells well those are the ratus norvegicus and those are one well have to be something else and that's it so it's a way to to organize the classification that justifies how it's attached to a single specimen but but for for the strains in laboratories so those strains it's not a single specimen but it's a single lab so the idea is that it's more of a group and it's the common ancestor is more of a group and it's a specific lab with an address and so on that is used in the scientific papers to report what has been done so it's always very concrete material and so on so it's when I say concrete it's in a very basic way to say it's this one and it's referred to as a catalogue and archived but the body is archived okay so we have three minutes we have to make it very quick I just want to push you on your explanation your notion of expansion I came very confused because in the talk you were very clear that the principle of sufficient reason do not act the same way so it's in physics it's change that you have to explain and not invariance it's why invariance is the base of explanation but in biology constraint has to be explained so they cannot be the base the ground of explanation so after that you said yeah but maybe the schema the sketch could be the thing that explain because that's it's more stable but now I'm confused what can be explained is the persistence of constraints so you have to explain persistence of constraint or persistence can explain something I'm confused so the persistence of constraints can be explained okay but the existence it's to an extent it can be explained or at least retraced where we fall back on the question whether retracing is explaining for historical phenomena to a part it has some contingence to it and this contingence is observable in a sense it's a diversity of living things that so so at this level there is some indeterminacy or numbness that take place and yes that is it for now so it's history to explain I don't use explain much actually I use it but what I don't like to explain is that there is an input and output whereas I'm working on the framework itself so this framework can generate input and output but just for that I aim it to be as flexible as possible but I don't have huge claim and things except these ideas that invariance and especially that persistence can be and should be explained or justified which is a big difference with physics and with thermodynamics closure of constraints that's why I say it's shown yes so it's 5 o'clock on a Friday so thank you very much everyone