Join us this April 14 at 4:30pm to listen to Dr Emmanuel Noutahi bioinformatician, ML scientist and head of Platform at Valence Discovery.
Title: Bag of Features: A Multi-Instance Perspective on QSAR modelling and computational biology
Modern QSAR approaches regularly take advantage of recent advances in machine learning to improve molecular property prediction models used for predicting bioactivity computationally prior to experimental testing.
However, despite improvements in methodology, a major bottleneck of recent methods remains the representational power of the molecule featurizer, which often either lacks faithfulness to the true molecular structure and/or relevancy to the predictive task of interest. To address these shortcomings, while also mitigating the impact of representation choice on predictive performance, we propose to formulate the task of predicting biological properties of molecules as a multi-instance learning problem in which a single label is assigned to a bag of descriptors all derived from the same 2D structure. The proposed approach relies on the hypothesis that the QSAR is better captured through several molecular representation perspectives instead of only a single perspective.
In this talk, we will discuss various architectures of the proposed multi-instance learning framework, including an attention-based aggregator that helps provide insight into the contribution of each representation (instance) in the bag towards the measured properties, then discuss potential application to predictive tasks in computational biology.
Research area : https://scholar.google.ca/citations?user=JcuwpbQAAAAJ&hl=fr
Two ways to join the meeting :
via jitsi (link available on RSVP)
via YouTube Live: https://youtu.be/a6wK08fvgxs
See you soon!
PS: If you want to present in a future event, contact us via Meetup or by email at info[AT]monbug.ca