Computational Challenges in Very Large-Scale 'Omics'

Simons Institute Summer Program on Computational Innovation and Data-Driven Biology


July 18, 2022 to July 21, 2022
9:00am to 5:00pm
Virtual Participation


Simons Institute Summer Program on Computational Innovation and Data-Driven Biology
Computational Challenges in Very Large-Scale ‘Omics’
Dates: July 18 – 21, 2022 
Location: Online and in Berkeley, CA 

BIDS Faculty Affiliate Sandrine Dudoit is a program co-chair, and she and BIDS Research Affiliate Katherine Pollard (Gladstone Institutes, UCSF) will be featured speakers, for this workshop, which is part of the Simons Institute summer program on Computational Innovation and Data-Driven Biology. Participants will review and discuss the development of novel methods and algorithms for extracting meaningful and reliable biological information from the analysis of the datasets that are ever-increasing in size and also in complexity. Participants will also discuss new ways to work with the data, applications to specific domains, as well as the ethical issues involved in generating and working with data. and how these data can be used in a nondiscriminatory fashion, and for the benefit of all.


Sandrine Dudoit

Professor and Chair, Department of Statistics, UC Berkeley

Sandrine Dudoit is professor of biostatistics and statistics and chair of the graduate group in biostatistics at the University of California, Berkeley. Professor Dudoit's methodological research interests regard high-dimensional inference and include exploratory data analysis, visualization, loss-based estimation with cross-validation (e.g., density estimation, regression, model selection), and multiple hypothesis testing. Much of her methodological work is motivated by statistical inference questions arising in biological research and, in particular, the design and analysis of high-throughput microarray and sequencing gene expression experiments, for example, mRNA-Seq for transcriptome analysis and genome annotation and ChIP-Seq for DNA-protein interaction profiling (e.g., transcription factor binding). Her contributions include exploratory data analysis, normalization and expression quantitation, differential expression analysis, class discovery, prediction, integration of biological annotation metadata (e.g., gene ontology annotation). She is also interested in statistical computing and, in particular, reproducible research. She is a founding core developer of the Bioconductor Project, an open source and open development software project for the analysis of biomedical and genomic data.

Professor Dudoit is a coauthor of the book Multiple Testing Procedures with Applications to Genomics and a coeditor of the book Bioinformatics and Computational Biology Solutions Using R and Bioconductor. She is associate editor of three journals, including The Annals of Applied Statistics and IEEE/ACM Transactions on Computational Biology and Bioinformatics. Professor Dudoit was named fellow of the American Statistical Association in 2010 and elected member of the International Statistical Institute in 2014. 

Katherine S. Pollard

Director, Gladstone Institute of Data Science & Biotechnology

Dr. Katherine S. Pollard is Director of the Gladstone Institute of Data Science & Biotechnology, Investigator at the Chan Zuckerberg Biohub, and Professor of Bioinformatics at UC San Francisco. Her lab develops statistical models and open source bioinformatics software for the analysis of massive genomic datasets. Previously, Dr. Pollard was an assistant professor in the UC Davis Genome Center and Department of Statistics. She earned her PhD in Biostatistics from UC Berkeley and was a comparative genomics postdoctoral fellow at UC Santa Cruz. She was awarded the Thomas J. Watson Fellowship, the Sloan Research Fellowship, and the Alumna of the Year from UC Berkeley. She is a Fellow of the International Society for Computational Biology and of the California Academy of Sciences.