Contrastive Models for Case-Control Changes in Sequencing - Models, Inference and Algorithms
Explore contrastive latent variable models for analyzing differential expression in sequencing data, enhancing case-control comparisons in transcriptomics with novel approaches to capture condition-specific variations.
GRN-Guided Simulation of Single-Cell RNA-Seq and Primer on Causal GANs
Explore GRouNdGAN for simulating single-cell RNA-seq data and learn about CausalGANs for gene regulatory network analysis and in-silico perturbation experiments.
Building a Mind for Cancer
Explore innovative approaches to understanding cancer through AI and machine learning with Trey Ideker's insightful presentation on building a computational mind for cancer research.
Foundation Models for Therapeutic Design and Treatment Prediction
Explore foundation models for therapeutic design and treatment prediction, focusing on novel insights in biomedical research and machine learning advancements.
Deep Learning for Genomic Discovery
Explore deep learning techniques for genomic discovery, focusing on high-resolution assays, footprint shapes, and bias correction methods in neural networks.
Inferring Single Cell Profiles from Histology and Generating Omics Data from Images
Explore cutting-edge machine learning techniques for inferring single-cell profiles from histology images and generating omics data from various imaging modalities, bridging the gap between imaging and genomics.
Machine Learning-Based Protein Engineering - Some Thoughts
Explore machine learning applications in protein engineering with Jennifer Listgarten. Gain insights into cutting-edge techniques and their impact on biomedical research.
Deep Learning Models for Genomes and Beyond
Explore deep learning models for genomic analysis and their applications beyond, presented by Olga Troyanskaya in this Broad Institute colloquium on AI in biomedicine.
Multimodal Protein Language Models for Deciphering Protein Function
Explore multimodal protein language models integrating sequences, structures, and textual descriptions to bridge structural and functional understanding of proteins for biomedical research.
Scalable Single-Cell Models for eQTL Mapping - Primer and Main Talk
Explore scalable single-cell models for robust cell-state-dependent eQTL mapping. Learn about statistical challenges, computational solutions, and applications in identifying autoimmune disease risk loci in memory T cells.
Decoding Cell Fates through Single Cell Genomics, Imaging, and Machine Learning
Explore decoding cell fates using single-cell genomics, imaging, and machine learning techniques in this cutting-edge symposium presentation by Dr. Jian Shu.
Protein Dynamics and the Brain
Explore protein dynamics and their impact on brain function with insights from renowned expert Peter Wolynes of Rice University.
Uncovering Association Mechanisms and Functional Mechanisms of Intrinsically Disordered Proteins - Symposium Talks
Explore intrinsically flexible proteins and their association mechanisms, and unravel functional mechanisms of intrinsically disordered proteins through energy landscape visualization.
Simulating Life Processes and RNA Structural Dynamics
Explore cutting-edge molecular biophysics research on simulating life processes and RNA structural dynamics through expert presentations at the ICTP-SAIFR symposium.
Protein Structure with Transformers - Lecture 9
Explore protein structure prediction using transformer models, uncovering advanced techniques for understanding and analyzing protein folding and interactions.
Protein Design Using Deep Learning
Dive into protein design using deep learning with David Baker. Explore cutting-edge techniques and insights at the intersection of AI and biomedical research.
Neural Optimal Transport for Inferring Single-Cell Responses to Perturbations
Explore neural optimal transport methods for predicting single-cell responses to perturbations, uncovering insights into molecular processes and treatment outcomes at unprecedented resolution.
High-Throughput In Silico Genetic Screen for 3D Genome Organization - Models, Inference and Algorithms
Explore cutting-edge approaches in 3D genome organization research, including in silico genetic screening and graph representation learning for analyzing multiscale chromatin structure.
Learning Differentiation Dynamics from Lineage Tracing Datasets
Uncover robust computational approaches for inferring cell dynamics from single-cell transcriptomics integrated with lineage tracing, focusing on the CoSpar method and its applications in hematopoiesis and reprogramming.
Biomedical Science and Machine Learning - A Two-Way Street (2023)
Explore the convergence of biomedical science and machine learning, discovering how these fields synergize to address modern biological questions and drive innovations in data analysis.
Machine Learning in Drug Discovery - Lightning Talks
Explore cutting-edge ML applications in drug discovery through lightning talks on antibody optimization, PROTAC design, small molecule binders, and protein-fragment interactions.