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Regression modeling on DNA encoded libraries
Ralph Ma · Gabriel Dreiman · Fiorella Ruggiu · Adam Riesselman · Bowen Liu · Mohammad M Sultan · Daphne Koller
Event URL: https://openreview.net/forum?id=rrcoPmV1XgN »

DNA encoded libraries (DELs) are pooled, combinatorial compound collections where each member is tagged with its own unique DNA barcode. DELs are used in drug discovery for early hit finding against protein targets. Recently, several groups have proposed building machine learning models with quantities derived from DEL datasets. However, DEL datasets have a low signal-to-noise ratio which makes modeling them challenging. To that end, we propose a novel graph neural network (GNN) based regression model that directly predicts enrichment scores from raw sequencing counts while accounting for multiple sources of technical variation and intrinsic assay noise. We show that our GNN regression model quantitatively outperforms standard classification approaches and can be used to find diverse sets of molecules in external virtual libraries.

Author Information

Ralph Ma (insitro)
Gabriel Dreiman (Insitro)
Fiorella Ruggiu (insitro)
Adam Riesselman
Bowen Liu (Stanford University)
Mohammad M Sultan (Insitro)
Daphne Koller (insitro)

Daphne Koller is the Rajeev Motwani Professor of Computer Science at Stanford University and the co-founder and co-CEO of Coursera, a social entrepreneurship company that works with the best universities to connect anyone around the world with the best education, for free. Coursera is the leading MOOC (Massive Open Online Course) platform, and has partnered with dozens of the world’s top universities to offer hundreds of courses in a broad range of disciplines to millions of students, spanning every country in the world. In her research life, she works in the area of machine learning and probabilistic modeling, with applications to systems biology and personalized medicine. She is the author of over 200 refereed publications in venues that span a range of disciplines, and has given over 15 keynote talks at major conferences. She is the recipient of many awards, which include the Presidential Early Career Award for Scientists and Engineers (PECASE), the MacArthur Foundation Fellowship, the ACM/Infosys award, and membership in the US National Academy of Engineering. She is also an award winning teacher, who pioneered in her Stanford class many of the ideas that underlie the Coursera user experience. She received her BSc and MSc from the Hebrew University of Jerusalem, and her PhD from Stanford in 1994.

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