Image credit: Biodata Developers Network
Science and AI fans, get ready for October 2024 – the Wellcome Sanger Institute is hosting the first-ever Explainable AI in Biology Conference at the Wellcome Genome Campus. Here we review a snapshot of some of the planned talks from AI experts about integrating AI into biological research.
The Explainable AI in Biology Conference (#XAIB24) will showcase the latest techniques for applying explainable and responsible artificial intelligence (AI) to genomics and biology. Explainable AI (XAI) is a collection of processes and methods that make AI more understandable and trustworthy for its users1.
As AI and machine learning (ML) become commonplace in our everyday lives, from generative AI such as ChatGPT to pattern recognition and self-driving cars, these AI and ML tools will also make significant advancements in genomics and drug discovery. As a result, there is a growing need to reveal the underlying logic behind AI models to make them easier to comprehend, and for the tools to provide meaningful insights into ways we can improve science and ultimately people’s lives and wellbeing.
Register now to secure your place at this unique event. Organised by our Biodata Developers’ (BioDev) Network, the conference will promote open, accessible and responsible AI. With support from the Wellcome Sanger Institute, this hybrid event is free to attend, ensuring accessibility for everyone interested in the applications of AI to biological research.
Join us to hear from over 30 leading academic and industry experts, who will explore cutting-edge topics and innovations in applying AI to Biology. Read on as we explore talks from three of these speakers.
“We are thrilled to provide this opportunity to connect a diverse group of experts and enthusiasts in AI, computational science and biology. The BioDev Network has worked tirelessly to create this unique conference programme, and we’re looking forward to more AI/ML events that we’ve planned for next year. Watch this space and keep an eye on the BioDev Network’s website."
Dr Priyanka Surana,
BioDev Network Lead, Wellcome Sanger Institute
Discover how AI enhances social good
Working at the leading edge of AI innovation, Alpan brings a wealth of experience from his background in theoretical physics, computational biology, and AI research at prestigious institutions including D. E. Shaw Research, Amazon, and LinkedIn. Now, he focuses on using AI to overcome vital issues in underserved communities across low-to-middle-income countries as part of the independent non-profit Wadhwani AI.
At the Explainable AI in Biology Conference, Alpan will share his team’s approach to developing AI applications for integrated pest management in cotton farms to help reduce crop losses in rural communities in underserved countries. Learn about how these AI solutions impact lives and livelihoods, the data challenges they address, and the innovative techniques needed when working with limited resources.
Alpan will also detail how they use AI in the same communities to create screening technologies for infectious diseases, including tuberculosis (TB). His team will create automated technology that can assess cough sounds to screen for TB. They have also created computer vision technology to assess the results of Line Probe Assays. These tests are approved by the World Health Organization for detecting resistance to TB drugs. Another automated tool will help clinicians provide different interventions for TB patients based on how likely they are to follow their treatment programme.
Alpan Raval,
Chief Scientist, Wadhwani AI
Discover how AI enhances social good
Alpan Raval,
Chief Scientist, Wadhwani AI
Working at the leading edge of AI innovation, Alpan brings a wealth of experience from his background in theoretical physics, computational biology, and AI research at prestigious institutions including D. E. Shaw Research, Amazon, and LinkedIn. Now, he focuses on using AI to overcome vital issues in underserved communities across low-to-middle-income countries as part of the independent non-profit Wadhwani AI.
At the Explainable AI in Biology Conference, Alpan will share his team’s approach to developing AI applications for integrated pest management in cotton farms to help reduce crop losses in rural communities in underserved countries. Learn about how these AI solutions impact lives and livelihoods, the data challenges they address, and the innovative techniques needed when working with limited resources.
Alpan will also detail how they use AI in the same communities to create screening technologies for infectious diseases, including tuberculosis (TB). His team will create automated technology that can assess cough sounds to screen for TB. They have also created computer vision technology to assess the results of Line Probe Assays. These tests are approved by the World Health Organization for detecting resistance to TB drugs. Another automated tool will help clinicians provide different interventions for TB patients based on how likely they are to follow their treatment programme.
Darlington Akogo,
Founder and CEO of minoHealth AI Labs
Darlington Akogo is the Founder and CEO of multiple AI-driven companies, including minoHealth AI Labs, karaAgro AI, Runmila AI Institute, and Gudra AI Studio. His work applies AI across various domains including healthcare, agriculture, and energy. Darlington is a world leader in AI and was named one of the Global Top 100 Most Influential People of African Descent (MIPAD) in Healthcare.
In his talk, Darlington will explore how Moremi AI, his team's cutting-edge generative AI system, supports research and innovation in biology, biochemistry and drug discovery. Moremi AI is trained with diverse biomedical data from several continents, making it an essential tool for advancing global research. This advanced large language model can support various biomedical research tasks, including: molecule captioning; exploring the structure, function, and interactions of proteins and molecules; protein-protein interaction prediction; text-based molecule generation; molecule property and drug-target binding prediction; preclinical and clinical trial predictions; and more.
Moremi AI also serves as a general-purpose medical assistant to general practitioners, specialists, and other health workers. It can interpret diverse medical images, write medical reports, perform differential diagnoses, prescribe treatments, plan treatments, educate patients, and even aid drug discovery. The system can support many clinical areas, from radiology and pathology, through to nutrition/dietetics, veterinary health, and more.
He will also explore how KaraAgro AI provides farmers with the tools to make informed, actionable decisions for their fields. Their systems enable precise inspection of every crop, allowing early detection and management of diseases, pests, water shortages, and nutrient deficiencies to ensure healthier yields.
Shaping the future of AI in health, agriculture, and beyond
Darlington Akogo, Founder and CEO of minoHealth AI Labs
Darlington Akogo is the Founder and CEO of multiple AI-driven companies, including minoHealth AI Labs, karaAgro AI, Runmila AI Institute, and Gudra AI Studio. His work applies AI across various domains including healthcare, agriculture, and energy. Darlington is a world leader in AI and was named one of the Global Top 100 Most Influential People of African Descent (MIPAD) in Healthcare.
In his talk, Darlington will explore how Moremi AI, his team's cutting-edge generative AI system, supports research and innovation in biology, biochemistry and drug discovery. Moremi AI is trained with diverse biomedical data from several continents, making it an essential tool for advancing global research. This advanced large language model can support various biomedical research tasks, including: molecule captioning; exploring the structure, function, and interactions of proteins and molecules; protein-protein interaction prediction; text-based molecule generation; molecule property and drug-target binding prediction; preclinical and clinical trial predictions; and more.
Moremi AI also serves as a general-purpose medical assistant to general practitioners, specialists, and other health workers. It can interpret diverse medical images, write medical reports, perform differential diagnoses, prescribe treatments, plan treatments, educate patients, and even aid drug discovery. The system can support many clinical areas, from radiology and pathology, through to nutrition/dietetics, veterinary health, and more.
He will also explore how KaraAgro AI provides farmers with the tools to make informed, actionable decisions for their fields. Their systems enable precise inspection of every crop, allowing early detection and management of diseases, pests, water shortages, and nutrient deficiencies to ensure healthier yields.
Advancing ovarian cancer prediction
Dr Mariana Boroni leads the Bioinformatics and Computational Biology Lab at the Brazilian National Cancer Institute (INCA). With a broad background in biochemistry and bioinformatics, including a postdoctoral position at Ludwig Maximilians Universität (LMU) München, her group works on data analysis and develops tools at the interface of immunity and cancer biology.
Mariana will share her work on single-cell biology and her life-changing research into ovarian cancer. Many ovarian cancer patients present with subtle symptoms, so they are more likely to be diagnosed when the cancer is already advanced, which significantly reduces their chances of responding to treatments. Moreover, early detection is vital to increase survival rates, but there are limited clinical biomarkers for detecting ovarian cancer or assessing its prognosis. Mariana will highlight her research on developing a microRNA (miRNA)-based prognostic predictor for a subtype of ovarian cancer. miRNAs are non-coding RNA molecules that regulate gene expression and are crucial in various cellular activities. Combining omics approaches with AI, Mariana’s team identified clinically effective biomarkers that could improve survival rates and quality of life for ovarian cancer patients. These miRNAs target genes associated with immune pathways and cell communication.
Mariana Boroni, Group Leader, Brazilian National Cancer Institute (INCA)
Advancing ovarian cancer prediction
Mariana Boroni, Group Leader, Brazilian National Cancer Institute (INCA)
Dr Mariana Boroni leads the Bioinformatics and Computational Biology Lab at the Brazilian National Cancer Institute (INCA). With a broad background in biochemistry and bioinformatics, including a postdoctoral position at Ludwig Maximilians Universität (LMU) München, her group works on data analysis and develops tools at the interface of immunity and cancer biology.
Mariana will share her work on single-cell biology and her life-changing research into ovarian cancer. Many ovarian cancer patients present with subtle symptoms, so they are more likely to be diagnosed when the cancer is already advanced, which significantly reduces their chances of responding to treatments. Moreover, early detection is vital to increase survival rates, but there are limited clinical biomarkers for detecting ovarian cancer or assessing its prognosis. Mariana will highlight her research on developing a microRNA (miRNA)-based prognostic predictor for a subtype of ovarian cancer. miRNAs are non-coding RNA molecules that regulate gene expression and are crucial in various cellular activities. Combining omics approaches with AI, Mariana’s team identified clinically effective biomarkers that could improve survival rates and quality of life for ovarian cancer patients. These miRNAs target genes associated with immune pathways and cell communication.
“At the Wellcome Sanger Institute, we recognise the transformative potential of AI and ML to advance genomic technologies and fast-track our biological knowledge. We're proud to host and support the Explainable AI in Biology Conference and help ignite global collaboration and innovation in the field."
Dr Julia Wilson,
Director, Strategy, Partnerships and Innovation, Wellcome Sanger Institute
Sign up for the conference
Eager to learn more? See the full schedule on the Explainable AI Conference website.
Our packed schedule also includes participatory workshops, engaging discussions, informative poster sessions, and valuable networking opportunities.
Footnote:
For a simple guide to key concepts in AI, see our article: Using artificial intelligence for genomic research on the YourGenome website.
Find out more
- Explainable AI (XAI) conference website
- Biodev Network’s website
- Recent blog on a BioDev Network event - Hacking AI for genomics
- Dr Priyanka Surana’s profile
- Dr Julia Wilson’s profile
