Kansikuva näyttelystä Machine Learning in Computational Biology: Daily Digest

Machine Learning in Computational Biology: Daily Digest

Podcast by Carlos Oliver

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Lisää Machine Learning in Computational Biology: Daily Digest

Daily summaries of preprints in machine learning and computational biology. Source code: https://github.com/OliverLaboratory/arxivreader

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48 jaksot

jakson 08.01.2026: Knowledge Distillation, Deep Learning for Cancer Subtyping, and Protein Function Reasoning kansikuva

08.01.2026: Knowledge Distillation, Deep Learning for Cancer Subtyping, and Protein Function Reasoning

This podcast is brought to you by the Oliver Laboratory at Vanderbilt University. ---------------------------------------- 0:00 Inferring Clinically Relevant Molecular Subtypes of Pancreatic Cancer from Routine Histopathology Using Deep Learning (https://arxiv.org/pdf/2601.03410.pdf) 4:21 Interleaved Tool-Call Reasoning for Protein Function Understanding (https://arxiv.org/pdf/2601.03604.pdf) 8:50 Investigating Knowledge Distillation Through Neural Networks for Protein Binding Affinity Prediction (https://arxiv.org/pdf/2601.03704.pdf) ---------------------------------------- Source code: https://github.com/OliverLaboratory/arxivreader Contact: oliverlaboratory.com Source code: https://github.com/OliverLaboratory/arxivreader

8. tammi 2026 - 12 min
jakson 06.01.2026: Equivariant Models, Protein and RNA Structure Prediction, and Large Language Models for Molecular Applications kansikuva

06.01.2026: Equivariant Models, Protein and RNA Structure Prediction, and Large Language Models for Molecular Applications

This podcast is brought to you by the Oliver Laboratory at Vanderbilt University. ---------------------------------------- 0:00 Deep Learning Framework for RNA Inverse Folding with Geometric Structure Potentials (https://arxiv.org/pdf/2601.00895.pdf) 4:56 MDAgent2: Large Language Model for Code Generation and Knowledge Q&A in Molecular Dynamics (https://arxiv.org/pdf/2601.02075.pdf) 10:05 Edge-aware GAT-based protein binding site prediction (https://arxiv.org/pdf/2601.02138.pdf) 14:23 Quantized SO(3)-Equivariant Graph Neural Networks for Efficient Molecular Property Prediction (https://arxiv.org/pdf/2601.02213.pdf) ---------------------------------------- Source code: https://github.com/OliverLaboratory/arxivreader Contact: oliverlaboratory.com Source code: https://github.com/OliverLaboratory/arxivreader

6. tammi 2026 - 18 min
jakson 05.01.2026: Uncertainty Quantification, Protein Energy Alignment, and Quantum Simulation in Molecular Modeling kansikuva

05.01.2026: Uncertainty Quantification, Protein Energy Alignment, and Quantum Simulation in Molecular Modeling

This podcast is brought to you by the Oliver Laboratory at Vanderbilt University. ---------------------------------------- 0:00 Rule-Based Approaches to Atomic Sentence Extraction (https://arxiv.org/pdf/2601.00506.pdf) 3:44 Quantifying the uncertainty of molecular dynamics simulations : Good-Turing statistics revisited (https://arxiv.org/pdf/2601.00618.pdf) 8:23 Physio-DPO: Aligning Large Language Models with the Protein Energy Landscape to Eliminate Structural Hallucinations (https://arxiv.org/pdf/2601.00647.pdf) 13:03 Quantum Simulation of Protein Fragment Electronic Structure Using Moment-based Adaptive Variational Quantum Algorithms (https://arxiv.org/pdf/2601.00656.pdf) ---------------------------------------- Source code: https://github.com/OliverLaboratory/arxivreader Contact: oliverlaboratory.com Source code: https://github.com/OliverLaboratory/arxivreader

5. tammi 2026 - 17 min
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