 And next up we have Laurent Falcaire, who will present the Innovative Resource Award. Okay, thank you all for being here, and I would like first to thank the other member of the jury and to say that we had a nice time discussing the different applications and that we all agreed on the ranking that we decided. And following this ranking, we are delighted to attribute the CIB Innovative Resource Award 2023 for his outstanding Open Genome Browser to Thomas Roder. Okay, before he will tell you more about Open Genome Browser, I will first have to define a bit more what is the Innovative Resource Award according to the SIB. So the Innovative Resource Award seeks to recognize an outstanding contribution in the field of bioinformatics, specifically in the development of innovative resources that significantly advance the capabilities and reach of our scientific community. This resource, database, infrastructure, code base, analysis framework, visualization tool, breaking new conceptual and or technical ground and compasses original methodological contribution as well as innovative in-silico analysis of biological sequence structure or processes. Sounds a bit abstract, but let's imagine you are a bioinformatics core facility manager and a user comes to your office with hundreds if not thousands of bacterial genomes to organize to query to visualize and for example for common pathways and even more. You would probably freeze in front of such a challenge. Well, fortunately for you, Open Genome Browser would be the perfect tool to help you in such a situation. As Thomas Roder will show you in a moment, he developed a tool that provides you with an intuitive and versatile and open source platform allowing for visualization and comparative analysis of complex genomic data. This is typically the kind of innovative resource we like at SIB because it is not only technically sound, but it is essential to provide support to non-bioinformatics and let them explore their own data easily thanks to a user-friendly interface. Why it looks simple? However, the complexity lies in the details. Ask Thomas how to highlight a selected cake pathway on a graphical map combining 1,000 genomes. Thomas developed his resources during his PhD thesis in the group of Dr. Remy Brugman at University of Barron and he's committed to maintain and further develop it over the next years. As he will stay in the group. He also developed other tools like Scori2. But despite his huge work during his PhD, he hasn't lost his well-known appetite as he can still eat two deserts at every lunch. Finally, he doesn't leave his Bernie's route behind because he recently became CEO of a startup called Abrinca named after the R.A. River. His company aims at securing funding via licensing his open source browser to commercial companies. Thomas, the floor is yours. Thank you very much, Laurent, for this lovely introduction. And thanks a lot to the SIP for giving me this great award. It's a very great honor. Thanks also to the committee, especially those that voted for me. I was a bit surprised to get an award for my software because I was slightly afraid during the work on it that it doesn't really include a new algorithm or new biological findings. And these are often preconditions for getting published and recognized. I was considering myself to be developing something like a public infrastructure. Yeah, so I'm really thankful to the SIP for having this award to honor maybe less traditional research projects like resources like Open Genome Browser. Right, so since my software only was released in December of last year, I assumed that most of you haven't heard of it, and you don't understand what it actually does, so let's change that. Open Genome Browser is a comparative genomic software for simpler genomes like bacteria, fungi, and archaea. There are huge amounts of data available for these organisms because nowadays it can be produced very cheaply, but the major bottleneck has become storing, organizing, accessing, exploring, comparing, and sharing this data. This was really frustrating for me at the start of my PhD, and I found this really cumbersome. So this is a semi-fictional exchange with between a belogist and a bioinformatician. So the belogist might be interested in a certain bacterium, and she wonders whether it can produce folate. And the bioinformatician then maybe uploads the genome to the CEC servers in Japan and maybe waits a few hours or a day until the data gets back, and then he checks whether all of the genes are there, and he finds that one of them is missing, and so he says, no, it can probably not produce this compound. The belogist is then not very happy because she was searching for a bacterium that can do this, so which of my bacteria in my database can produce folate, and then the bioinformatician has to do a bit more work maybe, and let's say it's all of the genomes with eggnog and creates these maps automatically using pathway, let's say, and he sends the data back, and the belogist then performs some experiments, and maybe she finds that one of the bacteria, even though the maps indicate it has all of the necessary genes, it cannot produce folate anyway, and then asks the bioinformatician to find an explanation, and the bioinformatician maybe compares the relevant genes and maybe finds a mutation that correlates with the phenotype, and then you might think that both of them are really happy because they learned something and they came to a result. However, this exchange might have been very frustrating for both of them, for the belogist because each of these simple questions may have taken hours or even days to get an answer for, and for the bioinformatician it might have been really tedious and boring work. So this brings us to the ideas behind Open Genome Browser. The main idea is that the bioinformatician focuses on pre-processing the data and loading it into the software, and the belogist can then answer posts, at least some of our questions, directly to the software and get immediate results, and this would then both of them be happy. And so these are the main features of my software. It can create phylogenetic trees. It can create pathway maps. You can use it to compare genes and search for annotations. It can produce dot plots, which help you identify structural differences between assemblies, as well as flower plots, which help users to find genes or ortho genes that are shared by a set of genomes, or that are unique to certain genomes. And it also has a gene-trade matching feature, so if some of your bacteria have a certain trend and some don't, it will propose some candidate ortho genes that correlate with the phenotype, and that could be causally causing the phenotype, so you might want to then perform an experiment to confirm it. And without further ado, I'd like to demonstrate two of my favorite features of the software, the pathways and the gene comparison tools. I hope I need the help of our practitioner. I think she's ready. Yes. So let's open genomebrowser.bineformatics.unibi.ch. This is the demo server of the software. Please pause. And it contains about 60 lactic acid bacteria. Most of them, oh, shit. That's all right. I have to push on the laser button, not the other one. Yeah, most of them are propione bacterium for adenarache, as you can see here. Continue, please. Yeah, so 67 and 44 for adenarache. Now let's go to the pathways tool like this. And here we can enter the name of a pathway map, for example glycolysis, and below that we can enter a genome, for example this one, just randomly, and then click on the submit button. Pause, please. And here what we see is which enzymatic steps on the pathway are covered by the genome. Please continue. But we can also do more complicated inputs. All right, add tags, actinobacteria. Pause, please. And then we see not just red shapes, but also yellow ones. And the color represents the fraction of the genomes that have the required genes to perform this step. So all of the actinobacteria have the genes for this step, but only some have the genes for this one. Continue, please. You can click on add groups, and then you can compare the first group of genomes to a second group like this. So, for example, comparing actinobacteria with firmicutas. Pause, please, again. Thank you. And here now you see that the shapes are split into two parts, for example this one here. On the left side it's yellow, which indicates that only some of the firmicutas have the required genes, on the right side it's red, meaning that all of the... No, the other way around. All of the firmicutas have it, but only some of the actinobacteria. Continue, please. And you can click on these shapes like this. Yes. And then you see which of the genomes are positive and which ones are negative. And you can click on the annotations that are covered and go to the compare the genes tool. So here are the genes of interest that we saw in the pathway map, basically. Pause, please. And with one click we can calculate the protein sequence alignment, and if we went to the settings over here, we could also compute nucleotide sequence alignment with different alignment algorithms and so on. And below that we have a gene locus plot. Continue, please. Pause. What we see here is each of these plots is an excerpt of a genome assembly and the bars, these are the genes. So the green ones, the gray ones in the middle are the genes of interest. And we see... and they're colored according to their auto group. So in this genome here, lactococcus cremoris and in this genome, lactococcus lactis, we see that our gene of interest is flanked with the same genes. So this is in certain contexts relevant information. For example, if you have a hypothetical gene, you might be able to get an idea with what it does by looking at its neighbors. Continue, please. You can zoom in and out. And you can click on these genes as well to get information about them. For example, this is a fruit toss by phosphatase and its neighbor is an oxyureductase. And of course the one that is green in the other plot as well has the same description. Yes. If you want to play around with the software, you could go to opengenomebrowser.binformatics.unibi.ch yourself. And if you want to learn how the tools work and how to use them, go to opengenomebrowser.github.io where I have also documentation and tutorials on how to install the software and so on and also the tutorials about the tools. So why opengenomebrowser surely similar tools already existed before, but I think one of my main innovations is that it's a reusable and dataset-independent software. So many other tools have been made specifically in the context of a certain sequencing project and very little, if not, was made to make the software easy to recycle or reinstall for your own data. And I think this is what makes it sustainable because theoretically lots of people can use my software, but only one code base has to be developed and maintained. Moreover, opengenomebrowser contains tools to help you organize the genomic data, which is very important for long-term sequencing projects, which can spend decades and involve different methods of data processing as well as read generation. And in my slightly biased opinion, I think it's more feature-rich and much more user-friendly than alternatives, and together that means it could greatly accelerate your research and save you some money. Right, so what are the... Maybe I should skip this slide. Well, there are some of the use cases of opengenomebrowser. So firstly, it's obviously useful for non-programmers because it's important that they can look at their own data. They often know the biological context, which is often super important, and it offers them new ways of doing this, which could be very significant, but it's also useful for non-binformations who either they might want to use it themselves, it also makes them faster, but also because it helps them systematically manage their data, including the metadata. And for sequencing projects, basically this was the use case for which it was developed. Large-scale sequencing projects need to have a central way of storing the data systematically, and they usually want to make it easily accessible to many different people in their institution. And it could be useful for bioinformatics providers who might want to give end-to-end services, so from the raw data that they receive from a sequencing center, all the way to assembly annotation, to opengenomebrowser, to give it to their clients in a more high value or more readily usable format. It could also be used to publish datasets, so if you sequence lots of genomes and you can make them available very neatly, simply by recycling my software. And it has also been used in education because it's quite easy to use. So I'll give you a brief idea of some institutions that use the software. So we developed it together with Acroscope for their database of 1,500 lactic acid bacteria. And by now, I think four groups are using it at the University of Bern, mostly in the field of veterinary bacteriology to study animal pathogens. But I know that some other projects are being planned, including outside of Switzerland, and there has even been some commercial interest, though I'm not allowed to disclose much more on this front yet. Right, so we're coming to the end. I'd like to thank my collaborators, Simon Oberhansley, Noam Sharmy from Acroscope, and my PhD supervisor, Remi Brugman, as well as the institutions that supported and funded my PhD program during which I wrote the software. And I'd like to mention the spin-off that I created called a Brinkage Enomics, together with Remi, my PhD supervisor, and Linda, computer scientist, with the goal to ensure long-term maintenance and support and development for the software. Yeah, this is the end of the presentation. I didn't have one minute left. Thank you for your attention, and many thanks again to the SIP for this lovely award. Yeah, I'm happy to take a few questions. If you're interested in the software, please talk to me later on. Thank you very much, Thomas. Questions for Thomas? Thank you. So as far as I understand, the software is based on bacterial genome assemblies. Is that correct? So you notice the bacterial genome assemblies, so it can be also different organisms as long as they don't have introns more or less. But you also have to pre-process the data. I think this is an important realization. You cannot force everyone to use the same pipelines. In one instance, people might be interested in, let's say, antibiotic resistance genes, and in another instance in, let's say, carbohydrate metabolism. So my software requires you to assemble your genomes and then to annotate them, for example, using eggnog or other tools, but you can define those freely yourself. You just have to follow some basic formatting instructions and then you can load this data into my software. I hope that answers your question. Right, so basically the input is an annotated genome or a set of annotated bacterial, let's say, a set of annotated genomes of organisms that do not have splicing. Yeah. Thanks. Other questions? Now it's working. Yes, Laurent, go ahead. Okay. Yeah, part of this you already answered, but I was wondering if you could potentially add other annotations like, for example, an anti-smash annotation for bacteria. Yes, I've experimented with anti-smash in particular. I think I haven't, but with Vibrant, which gives you a similar output. So it annotates a region of the genome with potential prophages. And anti-smash would annotate a certain region with as potential biochemical gene clusters, right? So this would just be a type of annotation that assigns a class like, let's say, a lipid acid or something, a gene cluster to a certain range of genes. And you could then use them in the software as a type of annotation. Any further questions for Thomas? Okay, I think we're all getting hungry as we're running a little bit over time. So please, a big round of applause again for Thomas. And then before you run off, just to thank once again all the members of the juries for undergoing this arduous task of selecting the awards for this year. Thank you very much for your attention. And yes, for the next edition, please make sure to share the call widely. And when you receive an email from us asking to serve on one of our juries, please do consider it. A round of applause for all of our laureates this year. Thank you.