Hosted by the Eric and Wendy Schmidt Center, the MIA Initiative (Models, Inference & Algorithms) supports learning and collaboration across the interface of biology and medicine with mathematics, statistics, machine learning, and computer science. We bring together scientists every Wednesday in Acadia (Broad Institute – 75 Ames St., M1) and virtually. A primer with breakfast starts at 9:00 am, followed by a seminar and discussion at 10:00 and 10:50 am, respectively.

** Join our mailing list: bit.ly/MIACast  
** Watch previous talks: broad.io/MIAPlaylist 
** Learn more: broad.io/MIA
** Questions: mia-team@broadinstitute.org

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 Fall 2024 Schedule 

 October 23: Noah A. Trebesch

University of Illinois at Urbana-Champaign

Primer: Using Advanced Molecular Dynamics Simulation Techniques to Characterize Large-Scale Conformational Transitions in Membrane Transporters

Ashkan Fakharzadeh Ghaan

University of Illinois at Urbana-Champaign

Talk: Large-scale conformational transition in membrane transporters

 October 30: Neriman Tokcan

UMass Boston

Tensor factorization methods for analyzing single-cell transcriptomic data

 November 6: Marnix Medema

Wageningen University

Primer: Deciphering the Chemical Language of Microbiomes

Victoria Pascal Andreu

Germans Trias i Pujol Research Institute (IGTP)

Talk: Algorithms for metabolic pathway discovery and analysis in the human microbiome

 November 20: Abraham Gihawi

University of East Anglia

Primer: Separating Fact from Fiction - Microbial DNA in Tumors

Steven Salzberg

Johns Hopkins University

Talk title TBD

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Past fall talks (to be posted on our playlist):

 September 25: Lightning Talks

Randy Ellis, Postdoctoral Fellow at Harvard Medical School

Machine learning approaches to predicting dementia using human biobank data

Henry Kilgore, Postdoctoral Fellow at the Whitehead Institute

Protein codes promote selective subcellular compartmentalization

Vidhi Lalchand, Eric and Wendy Schmidt Center Postdoctoral Fellow at the Broad Institute of MIT and Harvard

Bayesian optimization and its uses in the latent space of generative models

Bowen Jing, PhD candidate at MIT

AlphaFold meets flow matching for generating protein ensembles

Hannes Stark, PhD candidate at MIT

Dirichlet Flow Matching for DNA Sequence Generation

Andreas Luttens, Postdoctoral fellow at MIT

Deep learning to navigate vast chemical space

 October 2: Community Day

 October 9: Brian Cleary

Boston University

Primer: Flux Balance Analysis and shadow prices in constrained optimization

Aedan Brown

Boston University

Seminar: Modeling genotype to phenotype: a search for the right variables and the “natural” objects of selection

 October 16: Syed Rizvi

Yale University

Primer: Large Language Models and Biological Foundation Models

David van Dijk

Yale University

Talk: Single-Cell Analysis in the Age of Large Language Models