Models, Inference and Algorithms - Lightning Talks
Explore cutting-edge research in models, inference, and algorithms through lightning talks by five postdoctoral researchers at the Broad Institute of MIT and Harvard.
MPG Primer: Understanding Single Cell ATAC-Seq Data Analysis (2024)
Explore single-cell ATAC-seq data analysis, covering key concepts, workflow, quality control, and downstream analysis techniques for epigenomic profiling at cellular resolution.
Integration of GWAS and Functional Data - MPG Primer 2024
Explore techniques for integrating genome-wide association studies with functional data, enhancing understanding of complex trait genetics and disease mechanisms.
Machine Learning in the Optimization and Discovery Loop
Explore machine learning's role in optimization and discovery with Andreas Krause. Gain insights into biomedical applications and foundational ML advances in this joint colloquium series.
Unsupervised Viral Antibody Escape Prediction for Future-Proof Vaccines - Lecture
Explore unsupervised viral antibody escape prediction for future-proof vaccines. Learn about EVEscape model integrating fitness predictions, structure-based features, and biochemical distances to quantify viral escape potential at scale.
Data Thinning to Avoid Double Dipping in Statistical Analysis - Lecture 1
Explore data thinning techniques to prevent double dipping in statistical analysis, with applications in single-cell RNA sequencing and unsupervised learning problems.
Dissecting Cell Identity via Network Inference and In Silico Gene Perturbation
Explore CellOracle, a machine learning tool for analyzing cell identity through transcription factor regulation. Learn its applications in hematopoiesis, embryogenesis, and cellular reprogramming.
Protein Design with Generative Diffusion Models
Explore generative diffusion models for protein design, covering theoretical foundations and applications in sequence and structure generation for optimized engineering and biological insights.
AI-Driven Drug Design: Optimizing Pharmacokinetics and ADME
Explore AI-driven drug design techniques for optimizing pharmacokinetics and ADME with Novartis Principal Scientist Raquel Rodríguez Pérez at the Broad Institute symposium.
Programmable Generative Protein Design - Machine Learning in Drug Discovery
Explore programmable generative protein design with Gevorg Grigoryan, CTO of Generate Biomedicines, in this symposium talk on machine learning in drug discovery.
Automating Design of Molecules via Retrieval Augmented Generative Language Models - Broad Institute Machine Learning in Drug Discovery Symposium 2023
Explore automated molecule design using retrieval-augmented generative language models in drug discovery, presented by Andrew White from the University of Rochester.
Causal Representation Learning Through Multi-Modal Data Integration
Explore causal representation learning techniques for integrating multi-modal data in this workshop by Caroline Uhler from MIT and Broad Institute.
Interpretable Clustering of Single-Cell Transcriptomes - NNFC Workshop
Explore interpretable clustering techniques for single-cell transcriptomes with Jesper Madsen, enhancing understanding of genomic mechanisms and data integration.
Interpretable Machine Learning for Model Oversight and Insight
Explore interpretable machine learning techniques for model oversight and gaining valuable insights with Finale Doshi-Velez in this colloquium on AI applications in biomedicine.
AI in Drug Discovery: What Do We Need for Being Successful?
Explore AI's role in drug discovery with Sanofi-Aventis scientist Christoph Grebner, discussing key success factors and industry insights.
Decoding Biology with Data Abundance - Machine Learning in Drug Discovery
Explore data-driven approaches to decode biology and revolutionize drug discovery with insights from Recursion's AI and Digital Sciences expert.
Machine Learning for Discovery of Translatable Targets and Biomarkers - Keynote
Explore machine learning applications in drug discovery with Daphne Koller's keynote on translatable targets and biomarkers at the Broad Institute Symposium.
Harnessing AI for Drug Discovery: From Property Prediction to Molecular Design
Explore AI's role in drug discovery, from property prediction to molecular design, with Pfizer's Head of Machine Learning Research.
PROTPARDELLE: An All-Atom Protein Generative Model - Broad Institute Machine Learning in Drug Discovery Symposium 2023
Explore PROTPARDELLE, an all-atom protein generative model, presented by Stanford's Possu Huang at the Broad Institute's Machine Learning in Drug Discovery Symposium.
Music, Medicine, and Machine Learning - May 23, 2024
Explore the intersection of music, medicine, and machine learning with Dr. Tina Tallon in this thought-provoking lecture on innovative applications and future possibilities.
Generative AI for Modeling Single-Cell Responses
Explore generative AI applications in single-cell response modeling, covering data integration, representation learning, and multiomics analysis for biomedical insights.