 Good morning. Good afternoon. Good evening everyone depending from where you are connecting So it's a great pleasure for us to have you today with us To discuss this important topic related to animal breeding and one hell in Africa, which is the issue of data and their Exploitation the capacity on the continent to Be able to use the power or the potential of data to make meaningful decisions and that's why this consortium was able to come together to Be able to gather us all of us today and discuss or start a discussion on The matter of synergy of data science by formatics and capacity building addressing multi-country challenges For animal breeding and one health. This is of course in Africa. So just before we start Just few housekeeping note The first thing is that the presentation will be recorded and shared so we don't have to worry about that and Also to inform people that what we'll be discussing would be publicly available and plays When we are not talking is when possible. Let's keep our mic at least Off same as our cameras just to allow those who are in challenging areas to not to be Having difficulties in connecting and also please when possible You can be texting your question typing of your questions on the text and your comment as well Of course at the end we will have a Q&A session where we Exploit all the text and also have the oral questions at there on that station So this presentation will be on three main parts The first one should be just to take a few minutes to share with you Another view of the station which are partnering today to make this presentation And the second part will be Really a presentation on the synergy of data science and bioformatics and the web GIS Platform to be able to trust trick to map Animal breed Activities or breeding movements one hell activities, etc. And the last session will be the Q&A. So our first presenter today is Professor Eric Shakawa So just allow me to introduce him and I hope his camera is also on so that people should be able to see who we are talking about so Prof Eric Shakawa is the Network manager of the African Union Development Agency Southern African Network for bioscience Which is some bio? Which is also a shared research platform and innovation research and innovation platform For collaborative research in health and nutrition in Africa So he provides the overall leadership of running the network and he also manages administer and further divisions of And mission and objective or design ball network and scaling successful Bio project in 14 countries in Africa including DSE in southern Africa including DSE and Madagascar so today a proof Eric will be mentioning or Presenting about El Dane pad and some bio Initiative please prof Eric you have the floor Thank you so much Christian and and greetings to all the colleagues and researchers and Everyone involved and so We we are quite pleased and based in Pretoria in South Africa, but just to physically but we also Travel across the continent and collaborate with different partners So this is Sunbio is and is one of the networks under a UD and a part Which also include the sister network to Becca Becca Yuri have so we are quite pleased to be Working together with all the partners including Yuri and and all and and in in in in context to what We work on in biosciences. It's been is meant to compliment what Becca is already is doing So we are looking at the health and nutrition, but I'll get back to that But this is part of a bigger program under the AUD and a part looking at technology innovation And then of course there's some aspect of for industrialization as well And then cross-cutting is knowledge management So I think that's that slide kind of summarizes So you have a lot of cross-cutting issues that we deal with in the networks as we kind of look at innovation in the In on the ground in the member states in the continent next slide, please Okay, so just a bit about Sunbio, which is what So we we are a collaborative platform for scaling up innovations There is and and the thinking in in this aspect is there is a lot of work that's happening On the ground in the continent and there's some very interesting and successful projects That have worked in one or two countries, but some of them have not been scaled to make impact across the continent so And and in terms of knowledge generation as a continent who are not doing that badly We are doing Relatively well, we generate knowledge Sometimes we recycle a bit the knowledge but the translation aspects of the knowledge into useful products that can help the people that are on the ground is sometimes lacking and So we are not so we have decided as a network that we are not looking at research per se but we are looking at innovation which is looking at Invention plus reaching the market Because at the end of the day we want our products to get to the user whoever the user is Maybe the user is someone who is taking reagents next door or always in like in in terms of animal It might be taking the vaccine next door or it might be using the cement That's coming from your research platform or things like that. So we need to get move, you know, new innovations or new inventions from one point to to the next way it's where it's supposed to be used and We are also looking at health and nutrition This is where and these two are in that one the best on the agenda 2063 and this is you can't talk of health without talking of nutrition and Health we look at it in the broader sense, which is the one health But on the nutrition side, I'm just explaining what we the logic behind what we do We have deliberately not put it as agriculture because there is a lot of players in the production side of Things but there are very few that are playing in the space where we are looking at Getting some of whatever has been produced to contribute to the well-being of the people of the citizens of this continent That's why we are looking at in in nutrition for example in the in animal in animal in human health for example, you would know that we have iron deficiencies in in pregnant women in In teenagers and all that and this has been a big problem all along We have problems with We have been doing feeding programs across the continent forever, but still my nutrition is a problem So maybe we thought maybe someone has to bridge the gap between the production and the nutrition next slide, please So that's what Sunbio is about. So it's a platform where all these players can come in but geographically we were covering most of the southern part of the region and Baker was covering eastern central Africa then you also had other sister networks that were operating in in in North Africa, but and also in in West Africa It would struggle to the they didn't survive that long And these are some of the countries but the idea is if we want to if we want to Innovation and to thrive and to to translate Whatever knowledge we need We need infrastructure, but the infrastructure is is is not evenly distributed across our countries So we needed to have a state of the art infrastructure that we can share like the platform You would have at your at Yuri or the CSR in South Africa or other places across So can we say that infrastructure so that we don't keep on investing on things that we already have in another part of the region Then we also have to pull resources together to do in impact research. So this is problems that need The more than one country to solve for example foot and mouth is one of those or the sort of work that Yuri is doing or Malaria for example if it's a You know in human health things like that or some other zoonotic diseases then we need to scale up innovations And and this is what we are looking at So can we Bring the little money that we have from all over and then scale up so that it's a bit bigger Then we can actually do something that is significant because there's very little projects happening everywhere We need to pull those to get to get better impact next slide, which might be my last slide or second last so some of the Just to look at some of the priorities nutrition so we're looking at Alternative sources of protein and carbohydrate and all that value addition very important You know that our most of our food Especially packaging in the continent. It's not fit for papers We lose a lot of a lot of food or a lot of nutrition because of poor packaging The packaging is not meant for the our environment then one health and The way we are also looking at just highlighted looking at capacity building and research and innovation and also surveillance of diseases and all that And then the modern tools Including your digital tools the AI and the ethics that come with it next slide, please We also looking at entrepreneurship and industrialization especially looking at inclusivity The we have some members of our society that are not participating in the In the economy is fully youth and women and things like that Or even people with disabilities and all that so we think we need to also start looking at those so that they can They can add value and then of course because of the challenges that we recently Faced with your coffee then all that but also when you look at the climate change and all that We need to really understand using the modern tools look at The movement of person and in pathogens, which are really some of the important things then another area that we think is Important and we have started to work a lot on that is looking at adding value and using indigenous knowledge systems Even in animal health, we have done some a very interesting work in Zambia looking at for people that cannot use for example Akari sides, you know to manage a no Person and in animals. What could they use? Based on the indigenous knowledge, so this is what Sun Bio is and I think I thank you I hand over back to you Christian. Thank you Christian Yeah, okay. Sorry. Sorry. I was muted. Thank you. Thank you so much for and That's wonderful and it's important for us to understand that to make Significant impact to the agenda 2063 of the Africa Union. We need to move from research to industrializations and Product development, etc. And that is something that cannot be achieved by one country It is in synergy most of us and it is really important to understand that entrepreneurship and Technologies are fully to be involved. So we can see here from Sun bio napad From some bio that they already position For Southern Africa and also to support all the regions of Africa to achieve this objective through the activities They are doing in nutrition and health. So the second presenter should be from Baker. Ilry. Hope, which is Catherine Ziyomo. Catherine. Are you there? Catherine Yes, I'm here. Hello everyone. So just for me to introduce to you Catherine Ziyomo, which is a senior scientist and the leading Bioscience is an essential Africa program at Ilry International Astor Research Institute She's a plant breeder with a bold experience in the maze molecular breeding from extending from the Donald down for plant science in the U.S. DuPont pioneer in Africa was her effort really Contributed a lot in the development of drought and early maturing maze And only 120 days and she also let the integrated genomic service and support platform at Baker area help and aiming to facilitate the molecular breeding in Africa by offering high quality high density snitch notarping services and allied breeding and statistical support that are needed by farmers crop and livestock So Catherine will be sharing with us the vision Aligning to what is coming also from Southern Africa the new vision on how do we use The technology platform at Baker to transform agriculture and achieve the SDG goal Catherine you have the floor Thank you Christian. Good afternoon everyone. Good morning to others who are not on this continent I'm going to tell a brief story about Baker in where we are in launching Baker 2.0 Baker has achieved Quite a lot in the past 15 years in terms of capacity building for African researchers in modern biosciences. There's been a hub that has seen more than 500 scientists come through The scientists or researchers came through either as individuals or in groups and for short term skills Enhancement force and also for longer term like through the ABCL fellowships But upon reflection and also seeing looking at those achievements We see that there's a need to take those innovations further to take the research and really translated into possible solutions for For for Africa or for the continent contribute significant digital security So what we are looking at in Baker 2.0 It's going to create an ecosystem that to support scientists or researchers that's still mental scientists That's two mentors researchers but now take it a step further and Catalyze and incubate and coordinate and empower that research in order to reach product development So Baker 1.0 was anchored on three pillars of research technology platforms and capacity building But we see now we still doing the same things But leading to a product We've done a lot of research and a lot of publications came through Baker Publications either for master students for graduate students, but we now want to take Another dimension of product development So we are looking still at the innovative technology platforms that we have and how do we create this hub in the Centralize the facilities, but still have regional nodes in different countries We want to leverage on the alumni who are in different countries out to create communities or nodes in the different countries and we're not only focusing on The 18 countries that are in Eastern Central Africa, but we have expanded to all of Africa As we have already been doing this, but this change is really to officiate that Arrangement of those engagements. We have had trainings in Nigeria Trainings in Southern Africa and trainings in other countries that were not initially in the 18 countries So we want now to expand that and really identify those Innovations which are now closer to the market which need a different set of trade a different set of training a Different set of skills to be able to get to the market So our technology platforms still provide what we have been doing and we see an opportunity in strengthening In strengthening the genomics the sequencing And using modern tools to be able to carry the research that we do So still this still remains a hub where people can come or fellows now can come and be trained But they take it back to their countries and it's still the research has to align with the national priorities original priorities for example in Maze we see that The Maze lethal necrotic virus disease is Transboundary it is caused to have open East Africa and moving even to Southern Africa So how do we still identify people that can champion that research in the different countries and also align that research to national priorities So we are looking at also business development and professional development So still this if you look at this it's still capacity building But we're not doing capacity building in a different way Rather than have a fellow come and spend six to nine months in Nairobi Towards the PhD or towards the masters. We want to get another dimension of business development So they will learn the skills of entrepreneurship the skills of developing a product That can be marketed that can still scale and also be sold in different countries So we're strengthening the business development and professional development Angle so with these changes it also requires a different state of stakeholders a different set of partners in addition to what we have been working with We still have or still work with the conventional donors of the traditional donors That helped actually create beta and we also want to strengthen our partnership or engagements with a you Neapad and with sandbio and it From our pro ferrets presentation. It's very clear that Our goals or vision are still aligned or somehow they need we still want to find or advance technologies or spines How we can get technologies or increase access to modern technologies in Africa and where we see Biosciences holding promise it could be in the agriculture is what they guys trying to do and in health is what sandbio is doing But how do we come together and tackle those challenges and address those challenges? So that's where we are and In Baker 2.0. We're still looking at the conventional donors traditional donors But also trying to link more or strengthen the linkages with private sector in the private companies The good thing about private sector is when you talk about business development or professional development They do have the resources. They do have the capacity to be able to help us be able to do that So I will stop here and hand over back to Christian. Thank you. Okay. Thank you Thank you so much Catherine and here We call the son perfectly the synergy between son bio and Baker in the hub and their capacity on riding on the past successes and Connection with the mass to be able to move research to product development and impact at the ground level and this time Making sure that we catalyze we incubate coordinate and empower Scientists embedded into national priorities across Africa and for that we also need then Multistakeholder platform to be able to achieve these objectives and to really do that in matter of livestock the next presenter will be talking about Abnet African animal breeding network is dr. Isidore waga Isidore. You are there Yes, thank you. Thank you. Is it also easy though is a researcher and the Royal Society Newton International fellow based for the at the center for tropical last-of-genetic and health and Highland lab at the in Scotland at the University of Edinburgh. So his current research involved connections and application of animal breeding tools to last-of-genetic programs in Africa through Different activities in which he's really examining and the developing Exploring genomic data and phenotype phenotypic record of Thousands of pure and cross-bred pure breed and cross-bred dairy cows in East Africa in order to develop a breeding Approach that can be used in Africa to produce Suitable cross-bred cattle with the desirable production Hell and resilience trade required for your range of tropical Dairy system and this is also what He's supporting a lot African animal breeding network and he's going to give to us an overview of How app net has evolved and what is meant to achieve? Isidore, you have the floor Uh, thank you very much, Dr. Christian. Thanks for the opportunity And I will introduce today the African animal breeding network app net the African livestock Well adapted to different environments, but they face many challenges including productivity and resilience to some disease and In the past there were many initiative To improve productivity in Africa, but these initiative were not Successful and if successful not Sustainable so there was a need to put in place a platform to promote Or to drive sustainable left of genetic improvement in Africa So to give a short background how app net started during the All African animal agriculture conference in a Kragana 2019 Many experts in animal breeding and genetics from Africa and also in the diaspora they met to discuss How they can put in place a platform to support the left of genetic improvement in Africa and After that meeting there was a design meeting at the International Lifestyle Research Institute in Nairobi in November 2019 where We review the challenges in Lifestyle production and genetic improvement across Africa all the regions and then design the Abnet and in 2021 first of June Abnet was officially launched and Hosted by the center of excellence for livestock innovation and business at EGATON University in Kenya Now I will talk about the pillars of abnet first. What is the vision of? Abnet the vision of abnet is promote a resilient sustainable efficient and profitable livestock System in Africa and this is based in four pillars So the first pillar is multi-country genetic evaluation, which is the flagship pillar of the abnet and that includes how We can support countries to carry out the national genetic evaluation and after the national genetic Evaluation they can pull data together resources together To carry out across country genetic evaluation because in Africa you have many Transboundary breeds so these breeds can be used in joint genetic evaluation Across countries and we abnet did a preliminary study to show that pulling data together increase genetic gains In dairy cows, so the second pillar is professional development And in professional under professional development Abnet is influencing curriculum development in academia for example How what to pick? University can include for sustainability of life or genetic improvement in Africa and also capacity building for early careers for example in during the first quarter of 2022 the first inaugural abnet training was Condited at EGATON University and supported 48 early career Scientists from 30 countries and the two peak cover included How to record livestock data how to estimate genetic value of genetic value of animals and how to design breeding programs for African livestock and Under pillar three advocacy and awareness business development So under this pillar abnet is promoting Communication between different stakeholders policymakers to Influence a left or genetic improvement in in Africa and also promoting Secular bioeconomic for example Promoting Emission reducing practices for example in livestock production And the last pillar is collaboration networking and partnership and under this pillar abnets is linking the public sector Industry and academia to work together for sustainable livestock genetic improvement in Africa and all this is done under the overall coordination of the Secretariat and To finish abnet is open to anyone you can join any time and If you go to the web the abnet website There is how to join and it is easy to join and Thank you very much for this opportunity Yeah, thank you. Thank you so much is it oh and It's very important to understand how abnet is connecting also to Baker yield a hub to sign bio and to a unipad Patskali by the father is also breaking bringing together all African breeders and Their friend from across the world to be able to make meaningful transformation in Africa animal breeding through the different Pillars that we can see here And we can see also the issue of Collaboration even in data networking and partnership to be able to make the transformation and it is turns to this capacity of African animal breeding network that he was requested by EU to serve as the convener for the animal seed working group for Africa in the EU Seed and by technology program So this is important to understand how this setting is coming to Booster animal breeding to boost the agriculture food security and nutrition in Africa and this will not be done without Today without the input and the sustainable use efficient use of all the technologies available. So that's why the the next component of this the next stakeholder or the Stakeholder another stakeholder or contributor in this presentation is the Center for Tropical Astro Genetic and Health Which I'm going to present just as a strategic alliance between the Rosling Institute the Scotland rural College and the international last of the search Institute and that Alliance is mostly to develop tools technologies and innovation to enhance resilience productivity efficiency and environmental sustainability of tropical astro production system particularly for small holder farmers in low and middle income countries working in Africa and Southeast Asia for now, but With the capacity to intervene and contribute to activities all over the world and you can see that Center for Tropical Astro Genetic and Health is having for now five key programs poultry genomics and genetics poultry biotechnologies Dairy cellular resource dairy genomics and the small ruminant programs. These are the programs supported by city age age and we can reach The website to be able to connect to all the pillars and the scientists Working under it to see how we can support countries in Africa Then you can see the other key pillars coming here or programs is the data and trading system Because it is very important for us as we are talking discussing today to understand that Data is key data is almost everything. We cannot improve if we don't know what we don't we have so and we need The sustainable capacity building the critical mass of expertise to use this data In different domains to be able to make meaningful decisions and to be able to make the required transformation. So this is what The Center for Tropical Astro Is contributing to it means to afford all the platform or the network in Sun bio in West Africa in Southern Africa Wherever we are to support national partners to be able to boost their productivity and for us to be able to do that We first need to understand the challenges Which are really pinning down animal breeding and one health implications in Africa as we said The first is to have the critical mass of Breeders in Africa That's why all sons of Africa's and their friends are coming to say how do we support the Breeding and sustainable development of livestock in Africa. There is also issue of low investment and You may have understood from is it not the issue of the pillar on advocacy Just to mention that it is important for all over for all donors and stakeholders national and international partners to understand the input and the contribution of livestock In food and nutrition security and the achievement of the sustainable development goal and for that We need to have long-term plan, but we can't plan if we don't have data We can't do projection. So it is very important to do that and to build the capacity to be able to improve the administrative and organizational structures and Meet some challenges try to tackle some of the Wicked Issues coming like the climate change that we have to delete whatever we want and most importantly we need access to the data from animal breeding from one health and Allysance to be able to harness all the potential that exists on the continent And that's why we also need to understand the implication of one health in that genetic improvement One health when we are dealing about sustainable intensifications of agriculture a lot of breeding in Africa And that is why we will have the next presenters Prof. Steven Opeo from Ohio State University, which will be talking about Introducing Patera, which is an organization to support us achieve the objective both or it is Peace Yes, please you are the one to take the floor, please. Sorry Thank you so much Christian So my name is Peace Abe and I am a researcher I am a biostatistician and a data scientist I work with K. Swestan Reserve University Macquarie University research collaboration Where we generate vast amounts of data implement various health research protocols in various diseases And also manage various databases At magma consultants international. I am the co-founder and the director and And Today we are here to strengthen the synergy or data science Bioinformatics in addressing the various challenges in animal breeding and one health So as we have seen from the previous presenters Many of the challenges that we are seeing are going to require a generation of more information More data is going to be generated if we are to be able to address the various challenges in animal breeding and one health So at magma consultants international we offer data science services We specifically pride ourselves in training In capacity building of various research scientists across Africa and beyond We have in the past trained these scientists to be able to manage their data To manage databases to visualize data, but also we train them to model the outcome of various diseases, but also to analyze and understand Genomics data To also be able to combine genomics data with phenotypic data Integrate this information and be able to address these challenges. So we do analytics We train all scientists at different levels in various types of analytics Including prescriptive analytics as well as predictive analytics. We also do contract research Both statistical Biostatistical services we offer them, but we also train At different levels so that we are able to understand the data that's being collected But also to understand the need to collect that data and be able to make sense out of that data Now aside from that we also specifically emphasize Understanding training for database creations. So in Africa we're having challenges with databases We have many animal breeders that are collecting information, but we do not have enough capacity to We do not have enough capacity to Have all the data in one place. So we emphasize we train so that we are able to have our own databases In that way, it is easier for us to be able to access the data But also to use the data for decision-making now when the data is in those databases We also train and also offer services on how to process the data So that you're able to Curate the databases in the best way possible On the other hand, we also train and offer services in data collection How to collect the data? What tools to use to collect the data and how to manage the data that's being collected So basically Our role in this and what we would do is to again emphasize capacity building It is important that when we are addressing these challenges We understand how to interpret how to manage collect govern and secure our own data and going forward we shall be Demonstrating a few of the things that we do that we've done in the past and that we hope to do With this team in regards to addressing challenges in animal breeding as well as of one health Thank you, Christian Thank you. Thank you very much this and I think I can say the best is to come during the next presentations and for those who can join also and consult the The website of Marma consultant and there is a lot a lot to benefit from these Expertise and Also as collaborator in this initiative is a particular which is represented by proof appeal proof. We are there Yeah, yes. Yes, I'm here. Can I share my screen? Yeah, I can stop sharing Okay. Thank you. Thank you. Why proof is sharing I can introduce him Ah Profo Pio is a bio-formatic research scientist at the Ohio State University in the USA and Affiliated scientists also and he has been called Sultan for a theory for many years He's also the co-founder of the particular data science and the visiting scientist at the University of Sacrecate at Gulu in Uganda So his research focuses mostly on breeding by informatics and all the omics while his patient really lies in a capacity building for African scientists researcher and Student that's why most the spot being based in the US almost every month every two months He's in Africa involved somewhere in the training and we really appreciate your support Please you have the floor to share about particular Thank you, but Christian again for that introduction. Good morning. Good evening and good afternoon where you are So I'm going to just briefly talk about particular particular space both in the US and in Uganda. So we what we do with we do genomics purposes and the genomics with that from the road data from when when a client comes we Download data from this the sequencer Then the process we go up to for example up to snips and then we follow up And we call it products. So it depends on the client They it is somebody wants to be publication. That's our product is if a student's Up to the analysis So that is what we do with genomics and then in the that one also can apply to in animal breeding You have genomics and that's shown population and diversity study also in one half You can that can also apply to Orthogen genomics another area that we work on is Protomix we protomix we work in both Gel base and also Mass spec base. So again, we start from the road data up to the products up to the the last product And then another area that of omics that to work with this meta Metabolomics, we do both targeted and then targeted and then also the last one is a meta Genomics we do both Short gun and then we also do and in on all that we do capacity building So capacity building we do what on site and also virtually so it's connected. So so We either work with the client on site or we also work with them virtually Then I think that other stuff we do is Working with all this data we now integrate this data work with client integrated data The omics the professor make the rest on the combined with the phenotypic data and in the process again We bring in capacity development in capacity building another thing that we do is so we such Databases with the client we compare those databases with alignment and do evolutionary study. So in brief, this is what The services we do in by informatics. We basically we work with all the omics data and then the process we do capacity building So from now on I'm going to proceed to the presentation Okay, so please talked about data science and I talk about by informatics So what's the what's bring these two together with the common goal by informatics and data science is discover knowledge from data So the other difference basically between the two areas is by informatics we use biological data basically DNA proteins and In the data science generalized also data science can use But the tools are almost the same you have data analysis tools software program. So basically that's why particular and and we collaborate So I want to make sure that in a layman's language show that by informatics and data science have a common goal of discovery knowledge from the data So what are the common test of by informatics I already mentioned in the previous slides that one you such we used to such in public available databases for information regarding genes protein, RNA, and so forth. So using that it help divine for competitions and then the client to do their job and then of course compare sequence alignment For example, like different genes and proteins and also integrating and creating data which already explained in the previous slide Nothing that by informatics is very important in this analysis. For example, we do analysis will work with the one health pathogen surveillance and tracking We also do GWAS and genetic diversity and also This combined both in animal breeding and well health. So these are the common tasks of what we do in by informatics Okay capacity building so we work with Baker 1.0. We did a lot of work with Baker 1.0. So this is similar condition that we did with Baker 1.0. We supported Baker in comparative genomics, for example, comparing those in my coverage analysis. We did some work with early stop in milk and pork in Tanzania and Uganda. So that was part of capacity building. I think that we did. We supported the CG as a scientist in data analysis. We also work with them in my preparation. So all these some of them were on site and some of them after working with them on the site. We make sure that we work with them until we get what we call a product. So that's our model. One of the things that we also did with them was we support the scientists from the nights. Again, we work with them with data analysis experimental design. We were also involved with reviewing applications for challenge funds. So it was part of them. So we do on site and then after that we call up. Sometimes one-on-one by Informatics support. And then every workshops in advance about Informatics were there to work with Baker 1.0. So this was the work that we did on site. Okay. So we did only not work with Baker. So in Bakira and in Maga, we also work with Africa. And during COVID, after COVID-19, we decided, okay, how can we help these Africans in both bioinformatics and data science? So we put out a call that we needed to have 20 participants from all over Africa. And these were the topics in bioinformatics, biological data and genomic resources. And these were the topics that we put out there. And these were the criteria that we wanted for these scientists and researchers so that we can help them virtually. So after getting that call out, we got more than 400 applicants from three countries. This blue shows the countries that applied. And the red shows that some of these Africans who are here, either students or fellows, is some of these areas. So we wanted 20, we got more than 400. So what we did, okay, this is what we can do. So we had two cohorts. We divided the two cohorts for 10 weeks. So we trained them virtually. After training them, so these are some of the output that we got. Okay, before I go to the output, so this is the areas, the background of the people who applied. You can see from agriculture, animal genetics, up to zoology. That means we need capacity building in the area of data science and bioinformatics in Africa. So we need our, because of our capacity that we had, we trained 42. In order for the two participants we trained, we got two publications. And then we had two KG students who had data for almost two years, but they could not do anything. We helped them graduate. And we are now in collaboration with some of these participants. In 2017 to train. So this is, we was an eye opener for us that we need capacity building in data science and bioinformatics in Africa. Okay, so in the same in 2021. Now this is virtual so back early. And then instead of buying technology at the University and we had a training with them. And this is our model. We started training and then in the process. One of the trainers, one of the trainees. I had her data. So we were working with with her from training up to now the product we got our first publication. And now we're working with bioinformatics, basically using the genomics. And we are getting information about density diversity. So our model is unit capacity from the top until we get the product. The product can be publication can be the process. Okay. Okay, so we did the training. And in the process we realized that we have all these areas of people working with gods. It discount around 10 countries with almost 19 researchers so all of them are going to have data. All of them are going to have data. How can we use these days. How can you make sure that this data is used properly. And also also in one health. Okay. So with that, I'm now going to go back to Christian so we can introduce somebody who's going to talk about how we can make sure we use data to help us in Africa. Thank you very much back to you Christian. Thank you. Thank you very much. And I think a piece can take the screen now to move ahead with a section of the presentation. Peace. Yeah. Thank you. Please go ahead. Okay, so let me know if you can. Yeah, maybe you can put it on the presentation mode. Yeah, I'm doing that. Okay. Thank you. Once again, Christian and Dr. Steven. So, generally, I will be talking about data science in its broad sense, but also its applicability to animal breeding and one health and also the potential areas in which we would like to train the scientists to be able to understand the data that's being generated in an effort to address the challenges in animal breeding and one health. So previously we have trained scientists in collaboration with a particular data science in trainings that are both for data science and bioinformatics. So commonly in data science. We train data exploration. Now the data that's being generated is quite a lot of data. So we need to be able to explore the data and sort of discover hidden patterns in this data. And then we need to be able to, you know, do the descriptive statistics, summarize the data and do effective visualization so we can be able to make sense of the various data that's being collected. The other thing that we emphasize in the training is also how to do inference. Okay, inference. We mean how can you use common statistics and mathematics methods to draw conclusions from the data that's being generated. So with this we emphasize things like hypothesis testing. We also emphasize, you know, prediction of various parameters. So depending on the information that you're collecting and the aim of collecting the data that you're going to be collecting, we do teach using your own data that you've generated. But also we use different data to make sure that the scientists are understanding the information that they are collecting or their understanding information that's being collected. We don't have to collect the information yourself, but can you use the information in the various databases to make decisions to understand how you can address challenges in animal breeding, as well as one health. The other important skill that we would like the scientists to have is prediction. Now, with prediction, it's important for us to be able to go into this vast amounts of data, pick relevant information and use it for prediction. So this is a skill that is largely lacking. We train and we use machine learning algorithms, various machine learning algorithms, again with the various statistical tools to be able to understand the data and do prediction, whether we are doing mathematical prediction or statistical prediction. Okay, so I move forward. Okay, so what's the main challenge? Okay, what are these country challenges, multi-country challenges in animal breeding and one health. So one big problem that we have, especially in Africa, is that we do not have unified data recording systems. So various scientists are collecting information and they are keeping it in various places and sometimes we don't even know the information that's being collected. We don't know where it is kept. Sometimes you just read about it. So it's important for us to be able to sort of have curated databases that are going to contain this kind of information. And today we will be looking at why we need to have this information in one central location. Okay, the other challenge is some of the animal breeds are transboundary. So we need to be able to perform evaluations that also cover transboundary so that we can understand how we can improve challenges. Now, some of these challenges are also transboundary. So it's important for us to be able to have information in one place regarding all the different regions, for example. Again, diseases can also be transboundary. So it's important again for us to have information in one location. And then another challenge is that there are some regions that don't have enough resources infrastructure to actually address these challenges or sort of for animal breeding. So this also needs to be addressed so that we are able to collect reliable information. So in as much as we can have skills if we do not have the information in the beginning, it may not help to address challenges relating to Africa. And then definitely we have a big skills and knowledge gap in animal breeding and one health in Africa. So we are here to bridge this gap for all people, all scientists, anyone that is interested in understanding how to manage, collect, interpret and use data in animal breeding and one health. Okay. So those challenges that we've seen, they need a good data strategy, a comprehensive data strategy to be able to address those challenges. Now, this comprehensive data strategy has certain aspects that we train you to understand, implement and use. Okay. And the first one is data collection. A good data strategy for you, you should be able to collect the relevant data that you are going to use using the correct tool as well. So it's important to be aware of that. And then the other thing is we need good data architecture and integration. So we have vast data, we have genomics data, we have phenotypic data. Largely, analysis is done in separation for phenotypic and genomics data. However, in order for us to be able to get better insights from the data that you are collecting for animal breeding, we need to be able to integrate this kind of information. It is a challenge but it can be done and it's important for the people that are generating and using this data to be able to understand how to do that. The other thing you need to be aware of is data storage and technology. So again, I said we have challenges of storing large volumes of data in Africa, but we need to be able to address that so that we can have our data stored in a central location. Now, collecting data may seem easy. The real challenge is how do we get insights and analyze this data. So again, we need the skill sets which we offer and also train. We need the skill sets for data analysis, prediction and modeling, including visualization. Now, one thing that is usually overlooked is data governance of privacy and security. It is difficult for researchers to sort of put their data in a central location if they are not sure of how private and secure this data is. So it is important to have data governance policies in place and stipulate clearly how you are going to protect the data, how secure the data is. That is one way in which we will be encouraging different researchers to actually collect the data and put it in one central location. Going forward. Okay, so we have seen that we need a good data strategy and we need to be able to analyze the data. Now, the other thing that is important is visualization of the data. Okay, so in this quest to address challenges in animal breeding and one health, we have also looked at the synergy of data science and bioinformatics capacity building, which we have seen up to until now, and WebGIS in addressing these multi-country challenges. Now, the WebGIS, we use it to create dashboards and it is important because for the multi-countries, they are having, you know, different data collection strategies. That means there could be various databases that are capturing the information. How do we integrate the data from these various databases and have them in one platform in which you can be able to view the data in a snapshot and be able to understand which challenges are being faced in the different countries in a snapshot. Okay, so the WebGIS platform will be specifically helpful in understanding challenges of animal breeding as well as challenges of one health. So, specifically, it will enable us in the integration of these diverse sources, as I said, including environmental, the genomics, as well as the phenotypes, but it also facilitates the modeling. It combines, you know, again, bioinformatics and data science, as well as capacity development. Now, it should be noted that bioinformatics generates a lot of data. So it's very important to have skill sets in data science so that you can actually navigate and understand the bioinformatics, you know, data itself. And then in addressing challenges of one health, again, we need to be able to integrate data from health, animal, environment, because the interplay of this poses a challenge. So we need a way of having all data collected from these different elements in one place where we can be able to understand how this plays out. Okay, so at Magma Consultants in conjunction with Pateria, we have come up with prototypes of WebGIS dashboards that could help. We also have used real data to sort of understand how we can have all this information from various databases in one place in order to help us to address these challenges. Okay, so the first prototype of the dashboard that we have is one that is used for tracing and tracking zoonotic pathogens associated with animal acids dissemination. Okay, so this particular prototype for the dashboard uses simulated data. And we are using simulated data from Kenya at different regions. So the dashboard in itself contains information, animal breeding, you know, livestock, the seeds, the pathogens, and the source of the pathogen. So we can take a look at how this looks like. Okay, so this is a snapshot of how the dashboard looks like. So we have information from different counties. We have the different livestock. You can also understand the seeds that are associated with these and then the breed. You can also visualize the zoonotic pathogen associated with the livestock in that particular county as well as the source of the pathogen. You can also just check out the distribution of these in the different counties. Now this dashboard here, all these dashboards here, we have links to the dashboard you can explore the dashboard. So I'll demonstrate just one and then for the rest to save time we shall just move. So I'm going to sort of stop. Let me see if you can. Can you see the Google? Yes, yes we can. Okay, so we have links to the dashboards we can sort of go in there. It's loading. Hopefully the internet. It's fast enough. Okay. Thank you. Okay, so you can navigate the dashboard. You can navigate the dashboard. For example, for one county. Okay. And then sort of try to understand among the cattle. Okay. Maybe with this animal seed, which pathogen is associated with this. Okay, for example, here we are seeing the protozoa. The protozoa coming from the animal. So, so we can also on this side, I'm trying to remove the zoom screen here. Okay, we can also be able to check which breed. Okay. For which breed, whichever breed you want to see, what is the livestock, what are the seeds data about the seed, the source of the pathogen, etc. So basically, this is how the prototype works for this particular dashboard here. So I will go back to my presentation. Okay. So, again, this is just to demonstrate that you can use this same platform to either visualize information from whichever county. So even if this information from the different counties, for example, is coming from different databases, the web dashboard can help you to connect all the databases and be able to visualize that information in one platform and a very simple platform. Again, we also created a dashboard. Now using antimicrobial resistance data. Okay, so this one here used, we used real data. Okay. So this is real data from Vivlai. Now Vivlai is a global research data sharing platform. There are different companies that put the data inside there. And we got access to this data in a challenge that we went through and actually created a dashboard that can be used to sort of view antimicrobial resistance. Now, since there are many organizations, companies here that submit data to Vivlai, we chose one for this particular prototype. We chose Pfizer and we chose Pfizer because Pfizer had the most consistent information across different years, but also across different countries. So just to understand how the data that looks like the data set that we used has 17 years of data from 83 countries with 345 pathogens drug species with over 800,000 isolates. Okay, so I will. So in a snapshot. This is how the data looks like it's in spreadsheets, but you see it's quite difficult for us to understand data in spreadsheets to summarize visualize understand it in a snapshot, but also in the easiest way possible. So that's why we created the visualization. Okay, so this is also an interactive dashboard. It's also an interactive dashboard. But I may not demonstrate if you would like to demonstrate we can always share the link. Okay, so basically the information in the databases can be visualized. Okay. So in this particular case, we have this information was collected from different regions, Africa, Asia, Europe, etc. And also we have the, you know, the number of countries. Okay, so how much information was collected in which period of time in which country and the region where the country is. Okay, so you can also visualize the first challenge that we have here in Africa is that we have the least information in the databases. Okay, so again, this is a challenge. One of the biggest challenges is that we lack data on the continent. Okay, compared to others. So we can see that Africa sort of has maybe not the least, but yeah, the data is still not as much as in Europe. So this is a challenge that we may need to address on the continent for us to be able to address more challenges. Again, if we look at Kenya. Okay, in particular now, we chose just one country in Kenya in particular, you can see that information was collected in 2013 2014, then 2021. So again, we are not consistent in collecting information, but it's very, very important to be consistent. If you compare Kenya, for example, in the UK, you can clearly see that information here 2004 straight up to 2021. So they are consistent in collecting information. Okay, so as a continent, we need to be able to address this challenge, but we can also we can only address this challenge. If we understand the need and why we need to have data in place. Okay, so again, they, we have another prototype for this same dashboard where we can actually visualize the resistance for the pathogen to the different antibiotics that we have. We can check whether a given pathogen is resistant to a given antibiotic like imipinem, seftriaxone, and priceline etc. Okay, so this interactive dashboard, if you go inside there can help you to understand the sort of resistance. Okay, this one. We just created it for Kenya and Uganda, just to show so you can always understand the resistance of the pathogen in Kenya, and then understand the resistance of the pathogen in Uganda. And consequently, we can still add many other countries so you're able to navigate and understand maybe variations in resistance to different antibiotics in the different countries. Again, this is just a demonstration that you can actually just check out one pathogen and be able to understand whether it is susceptible to whichever antibiotic or if information is actually not available for that particular antibiotic in relation to resistance from one of these pathogens. Okay, so again, you can know whether it is resistant, susceptible to whichever antibiotic. However, of course, we need information, we need data. So this data is, it's not a lot of data, we have on a 62 samples in this particular, in the database that was used to create this dashboard. So the more data we have, the more we understand what is happening within the continent and be able to address more challenges. So yes, as I said earlier, you can always compare different countries, you can compare weather. For example, Equally is susceptible to MEP in this country in Uganda in Kenya. You can always navigate the dashboards depending on what you want to know in relation to these challenges that we have with one health and animal breeding. We also have another prototype for a dashboard which we can use to visualize information. Now a very comprehensive one where you can visualize information about traits, production systems, livestock management, disease prevalence, vet services, omics data availability, data science availability in the different regions. So we are able to do this when we have data that's being collected, albeit in various databases, but also that can be accessible and stored into maybe a central place so that we are able to have information. We have a bit of simulated information here and this particular dashboard here you can be able to to understand or view the, you know, the animal, the country, the trait of the animal, what kind of capacity building services are there. What kind of production systems are there. What type of mating, what causes the prevalent diseases there. Okay, the services available, distance to health center, etc. And most importantly, the dashboard can help you to understand the availability of information, specifically genomics, metabolomics, as we all know, this kind of information is very important in understanding these challenges or in animal breeding, but also data science services. Okay, you can generate all the omics data, but if you cannot make sense out of that data, it still doesn't help so that we can understand in a snapshot how much information is being generated. If we have bioinformatics services, if we lack data science services, and so we can fill in these gaps, but also improve the collection of data if we notice that data is missing. Okay, so here we've chosen a country, a particular breed, a particular trait, a particular production system, and we can see that we have only the proteomics data. Maybe if I went into the dashboard, I would probably live dashboard, I would check which particular information that we have, and sort of be able to understand how we can address which services do we need to offer, which services are lacking, which kind of data is lacking. And with that, I'd like to say thank you for listening, and I would like to stop my presentation here. Thank you. Thank you very much. And everyone for the wonderful presentation. I hope it is helping everyone here present to understand how deep is our need for data, data infrastructures and human resource, our capacity to be able to make sense of what we have. And now it is clear that Africa, in Africa in general, we are still lacking a lot of data, we still have a lot of effort to put in place to ensure that we have the information we need to advance with animal breeding and genetics improvement to advance with one herd and to be able to tackle some of the weaker challenges that we have in Africa in general. Thank you very much. And it's now time for the Q&A session. And I can see that there have been a few contributions from the chat. And I think one of the contribution, the first question was our information was coming from Paul. Paul, are you there? Paul from AFL. Yes, yes, I'm here. Yes, so that you have an important information to share maybe you can also share that so that people understand and share also with their respective country for CalPoint. Thank you. Okay, yes, thanks for offering me the floor. I see my, the lighting in my room is not that good you maybe can't see me too well. But yes, I just wanted to share with the group that that FAO has just, it actually was almost two months ago now had offer, had launched the, the, the chenille let's say process of preparing the report on the state of the world's animal genetic resources for food and every culture. And part of this process, let's say that one of the main parts of this process is the country reporting where, you know, there are a number of different questions actually quite a long questionnaire where country basically spawned to give an idea of the status of their infrastructure and activities with regard to managing animal genetic resources in their countries. And, as you may or may not know, each of the, you know, the FAO member countries nominates person called the national coordinator for animal the management of animal genetic resources food never culture, who is the main liaison between their community and FAO on animal genetic issues. They're usually a member of the ministry like either of the ministry, the other, the branch working with animal production in genetics, or maybe other government research institute. However, this, you know this national coordinator, it's because it's quite a long process quite a detailed questionnaire they made or it's unlikely that they will know all the answers themselves. It's the encouragement of having a very participatory approach. So, you know, my, my chat message was just to encourage people to, you know, if they're interested to contact their national coordinators and express their interest in helping to, you know, contribute in any way that could be feasible. So in the chat, I, I, all of the national partners that the list for each country is available on FAO website I gave the link there, or if you want to have additional information feel free to contact me directly I've given my, my email address as well. The deadline for providing these reports is, is the end of June this year so there is almost six there are almost six months of time to do this process but I just wanted to share that information so thank you for giving me the floor to give more detail. Thank you. Thank you very much. And it is clear to understand that we need to ensure that the national, the country for cal. points and the coordinators are having also information that we need to share with FAO, etc. And I think peace and Stephen should be able to also think and understand how particular and mama and the dashboard that we are putting in place can be contributing across country to be able to gather some of this information, not just for the state of farm animal genetics in Africa, but also even at the African Union. We have been working on the Vienna review for the cadet. And there is still a lot of challenges getting data across country to be sure that we feed effectively that we move forward with the indexes in the cadet. So, this is also an opportunity for all the stakeholders for us to come together and see how we can use the potential of human resource and capacity we have on the continent, at least to start building some of the platform based on what mama and other people are doing. If I could just add a few more details that I did not say that the reporting is actually done on a online questionnaire so that the national coordinator could eventually even share the link to the questionnaire it's. It's something like you may say click a Google Docs where people can, you know, all contribute to the document itself or they can provide it. The PDF version which then would have to be. You'll copy and paste it into the quite the online questionnaire, and then the national coordinator is the only person who can actually submit the final document but, as I said anyone can contribute to this. Also for some of the other stakeholders in this meeting in addition to reporting by the countries there is a another questionnaire that is reporting by organizations that that contribute to management of animal genetic resources. Although we have a list of some of those it is maybe not exhaustive so if any of you are representing an organization that you presumably you would not be participating if you're not dealing with animal genetic resources feel free also to send an email to me so we can add you to the list of international organizations that contribute to management of animal genetic resources. Thank you. Thank you very much for thank you. And please we have the next question coming to you. To please please how can I enroll in you about statistics and data science costs. I don't know if you have something to say that. Okay, so currently we don't have a course running we are going to have a course running soon, and we will be able to share the link with those that would be interested. However, for organizations as well. We do work with you to tailor the course to your organization. Different organizations have different biostatistics and data science needs. So we tend to tailor them. We can also have the broad courses. So we would make the announcement and share the link. Thank you. Thank you. The next question is coming from Raphael. Does the first one, there are two questions. The first one does a web. Platform analytical tools cover areas. Which has genomic prediction models and genomic selection. Maybe any of you can address the first question before we move to the second. I would address that possible. Thank you Raphael. I think you're working together too. So the dashboard that that piece presented. I mean present three dashboard. Two was simulated data and one was through your data. So the simulated data we worked with a lot of Christian to come with that. So to answer your question. Yes, but you have to work with you. And guide us how to put that information that you are requested in the dashboard. Okay. Okay. And the second question is there any training on data sampling and collection techniques to go and data collection to ensure data collected to have enough has enough power to make valuable inference and adequate adequately address the objective of the study. Yes, I will also answer that question again. So the presentation again we had one was real data and this real data came from five line. They're ready. We were part of the challenges. They already worked with the data and it gave us that. The simulated data of course we want to do the Christian. So to answer that question again will work with him. And we work with him go through the same process and then when we got data that have happened has enough power, then we can put in the dashboard. Okay. And I also say something. So, generally, generally in the trainings that we offer. We do offer trainings on how to know whether you are collecting enough data that has enough statistical power to generally understand differences that will help you answer your research question. So we do that broadly. But if you have your own data, we also help you to understand whether the data that you have has enough power to answer research questions. Thank you. Thank you very much. I think we also had a request coming from Dr. Azrasia from Mozambique to include Mozambique in the Goat COP. Yes, I think Elias is already working with Mozambique team on something on Goat. And we can discuss further and see how they joined the team at Baker, which was already working on the committee of practice on Goat genetics and genomics. And the team is really growing there. Then we also have a question from Dr. Olori Victor Olori to Catherine. Do you have a strategic plan for the training of the last mile technician? To allow the uptake and use of technologies, of technology, example, extra simulation, AI, embryo, transfer, etc. Is Catherine, I think, I don't know, I think the training is mostly to Catherine. Yes, thanks, Christian. So we are still to develop the framework or the mechanisms through which we're going to conduct the trainings. But definitely that is a key element under product development. So definitely have to incorporate that. So whilst we're working, we're looking at the big picture, but we definitely create the courses that we need to be carrying out under Baker 2.0. Thank you very much. Just to emphasize on that, that the vision of the next bigger 2.0 is to ensure that science and technologies are really transferred to the ground to the end users. The last mile technicians and the farmers. And this goes, of course, with training also of extension workers to be able to use the technologies on the ground and make the necessary transformation. But this is something that still need to be well crafted and embedded into specific programs like we have early farmer facing program. African and Asia, there is genetic gains. Topical policy genetic solutions in collaboration with national partners as well to be sure that we have these technologies effectively shared or transferred to farmers or to the end users. Thank you very much. We have a question from Charlotte, which all tools or software are used by MCI. This is by Marma. Will today's recording be shared with the participant? I can answer that one. Yes, we will clean it and share. But in terms of software by from Marma or skills that Marma can offer. Peace. Okay. Yes, thank you. So at Magma, we trained data science analysis using Python. We use our, we use data, use SPSS, we use Excel in training the various skills. Thank you. Thank you, peace. And I can say Alison from Zambia is really interested to know further about Magma and other activities. Then Victor is coming back. We need to discuss a strategy for our net to snag us snag us effort with Marma and Patira to allow the objective to be realized. Yes, that is exactly the objective. And that's what we have been working with Marma and Patira to make sure that this is just the beginning of our collaboration to work with them to work with Baker, CTAGH, Sanbio and AUNAPAD to ensure that we have good coordination and good strategic objective laid down and implemented. So that will be followed from here we are going to push together with peace and Catherine, Amber, Isidore and Eric, we are going to push that agenda. Yeah, that is setting all for the type questions. I don't know if anyone have their hands up. I can still raise your voice if there is something or should. Yes, I can see Alison, please go ahead. Yeah, thank you very much for the presentation, especially the issues concerning with the coordinators. We have, I think some of the coordinators in our countries, some of them are not working with the government now. And then also, possibly in other countries, so there might be need to review the coordinators because this information comes, it doesn't reach the people responsible in time. And at the end of the day, you find that FAO would have actually closed the admission of this information. So we'll try to look before it up. So we are requesting FAO to help us so that new coordinators can be appointed in these countries. Thank you. Thank you very much. Alison, I think Paul will take note of that. And unless he has something to say. No, nothing to add. Okay. Thank you. Dr. Asasia, please. The voice from Mozambique. Yeah. Yeah, thank you. Thank you, Dr. Tiambu and to all participants. I put my request in the chat. So I'd like to know whether there will be an opportunity for researchers from Mozambique to be trained on bioinformatics and on data science. Thank you. Thank you very much, Dr. and I can talk on behalf of Marma and Patina to say, yes, when, once they call a piece mentioned will be out. It will be shared widely to everybody across Africa and beyond. And we should be able to contribute and benefit from their expertise. Later on, I believe a piece will provide better information on that. Anyone else? Okay. So, if not. Yeah, okay. Please, yeah, please unmute. Yeah, thank you. I just want to thank all the organizers. This has been a very, very important eye opener to all of us. Making all of us aware of what's actually available right now in Africa. I'm an advocate of non-waste of time by different people trying to repeat the same thing that's already done. And so the information available here, especially from Patera, Professor Opio and Peace, I'm really grateful to you. And I really thank you so, though, and you, the coordinator here for Tiamble Christian, for the presentations you gave, which already pointing to what A.B.Net is trying to achieve. I think I just want to emphasize again that before we leave here, you should please device what plan we're going to use to make sure that perhaps at the next A.B.Net meeting or something, we can have people like Peace or Opio attending so that we can then make clear the plan that A.B.Net has as Isidore outlined in his short presentation. And then work with the leadership of CTLGA to see how we can synergize because we already, the question Raphael asked about data collection and genomics evaluation. We need to see how we can guide or help MCI to tailor their platform or the WebGIS towards the genomic presentation of genomic results, for example. Because that one is a continuous process so that we don't have to start to develop this WebGIS again. If you have something brilliant for diseases, for example, can we have something like that for genomic evaluation or genetic evaluation or British values? And how can we use this going ahead to encourage all farmers to have access to it? So there is a very interesting outcome that we can achieve from this meeting today. I really want to just thank all the organizers and to say thank you for putting this together and let's have a concrete plan on how to go forward. Thank you. Thank you very much. Thank you. So we'll make all effort possible. And we can assure you that we'll make to you to A.B.Net and CT age, age and elderly and other partners. Some propositions on how we can work closely with Marma and Patira. So, and we arrange with Peace and Stephen to be part of the next A.B.Net meeting as well. Thank you.