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GENERATIVE AI
“LLMs possess a unique capacity to autonomously comprehend relationships within biological data. This is particularly promising in the field of genomics, where the complex nature of RNA and DNA presents formidable challenges for conventional analysis techniques.” Raphaëlle Luisier SIB Group Leader, IDIAP
Deciphering the hidden role of RNA in cancer The SIB group of Raphaëlle Luisier is teaming up with experts in Natural Language Processing at SIB and IDIAP to study RNA, molecules which carry genetic instructions and help make proteins in living cells. They are interested in parts of RNA that do not directly code for proteins, and how they affect complex human disorders, such as neurodegeneration and cancer. In melanoma, a type of skin cancer, some treatments do not work well over time, especially drugs called BRAF inhibitors, and RNA could play a role.
Conversing with complex biological databases
Fancy a chat with Expasy, the Swiss bioinformatics resource portal?
Can technologies like ChatGPT support life science researchers in exploring data they are not familiar with? This is the question our new Knowledge Representation unit investigated, through concrete examples from SIB’s leading open databases and software tools. They showed the potential of conversational AI to describe biological datasets, as well as generate and explain complex queries across them. While the benefits include leveraging the wealth of open data, authors also stressed that caution should be exercised in the process.
Expasy brings together over 160 databases and software developed by SIB Groups on a platform enabling life scientists to search, filter and get suggestions as to which tool(s) could best help them in their research. A new project to integrate LLMs into Expasy aims to make queries on specific biological questions possible in natural language for the user (e.g. “Which are the genes, expressed in the rat, corresponding to human genes associated with cancer?”), by seamlessly retrieving information from the various underlying resources. SIB’s Semantic Web focus group is working on this together with the Biodata Resource team.
DOI: 10.48550/arXiv.2304.1042