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Computational Genomics Summer Institute CGSI
Computational Insights into Cancer Immunology

Explore computational approaches in cancer immunology, focusing on RNA sequencing, tumor microenvironment analysis, and immunotherapy response prediction in non-small cell lung cancer.
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Computational Genomics Summer Institute CGSI
Why is This So Hard? It Should Be Easy - Challenges in Computational Genomics

Explore challenges in computational genomics and learn strategies to overcome complexities in data analysis and interpretation.
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Graph and Algebraic Signal Processing Basics for Computational Biology

Explore graph and algebraic signal processing fundamentals for computational biology, covering key concepts, challenges, and applications in genomic data analysis.
- YouTube
- 29 minutes
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Large Language Models for Computational Biology - A Primer

Explore large language models in computational biology, covering transformers, pretraining, and applications in genomics and single-cell analysis.
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Computational Methods to Quantify Lethal Cancer Evolution

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Inferring Parsimonious Migration Histories for Metastatic Cancers

Explore computational methods for inferring cancer metastasis patterns, focusing on parsimonious migration histories and multi-strain infections in tumor evolution.
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Valence Labs
The Continuous Language of Protein Structure

Explore a novel approach to protein structure generation using continuous autoregressive language models. Learn about innovative techniques for in silico protein design and their potential applications.
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Bogolyubov Institute for Theoretical Physics
Computational Methods of Structural Bioinformatics in Studies of Protein-Nucleic Recognition

Explore computational methods in structural bioinformatics, focusing on protein-nucleic recognition mechanisms and their applications in DNA physics through advanced analytical approaches.
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Broad Institute
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.
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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.
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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.
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Beyond Cells: The Importance of Gene Programs and Tissue Context

Explore gene programs and tissue context beyond individual cells, uncovering novel insights into pressing biomedical questions through advanced machine learning techniques.
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