Implementation of an approach to exploit data from the LINCS project to characterize small molecules for drug development
Data from the LINCS L1000 project include the level of expression of approximately 1000 genes from 15 cell lines and slightly less than 300 small molecules. During her internship, Laurianne Paquette will develop an approach to characterize these small molecules, as well as these genes and cell lines, in order to use this information for drug development. This approach is based on neural networks and factorized embeddings.
Keywords: bioinformatics, machine learning, artificial neural network, transcriptomics, LINCS L1000, factorized embeddings