Deep Learning for Genetics, Genomics and Metagenomics: Latest developments and New Directions (22w5085)

Organizers

(Columbia University)

(McGill University)

(Lady Davis Institute)

(University of Pennsylvania)

Description

The Banff International Research Station will host the "Deep Learning for Genetics, Genomics and Metagenomics: Latest developments and New Directions" workshop at the UBC Okanagan campus in Kelowna, B.C., from June 5 - June 10, 2022.


Deep learning is one of the most active areas in machine learning, and has led to great improvements in many applications. Historically, deep learning has been extremely successful in applications to image and speech recognition. New deep learning methods have been developed in the last several years and have gained great attention in biomedical research, including research in imaging data analysis, digital phenotyping, analysis of electronic health record (EHR) data etc. Furthermore, these new methods have shown impressive results across many problems in biology. Such deep learning methods have been applied to the analysis of large-scale genetics, genomics and metagenomics data, including genotyping, analysis of single cell RNA-seq data, annotation of non-coding variants, analysis of metagenomic data, analysis of data from gene editing and regulatory genomics.

We propose to organize a workshop entitled “Deep Learning for Genetics, Genomics and Metagenomics: Latest developments and New Directions”. The goal of this proposed workshop is to bring together leading experts and junior researchers who are working at the interface between deep learning methods and genetics, genomics and metagenomics to discuss what has been done, what are the frontier research topics, what are the data sources for applying deep learning methods in genomics and metagenomics, and what are the unique challenges in developing deep learning methods and applying them in genetics and genomics research.


The Banff International Research Station for Mathematical Innovation and Discovery (BIRS) is a collaborative Canada-US-Mexico venture that provides an environment for creative interaction as well as the exchange of ideas, knowledge, and methods within the Mathematical Sciences, with related disciplines and with industry. BIRS is supported by Canada's Natural Science and Engineering Research Council (NSERC), the U.S. National Science Foundation (NSF), Alberta's Advanced Education and Technology, and Mexico's Consejo Nacional de Ciencia y Tecnología (CONACYT).