Decoding Biomolecular Languages

Admin
  • 0.0 (0)
  • LIFE SCIENCES
  • UPDATED DAILY

Daily summaries of preprints from arXiv and bioRxiv. Generated for Decoding Biomolecular Languages.

Episodes

  1. 3 DAYS AGO

    25.05.2026: Causal Intelligence, Novel Optimization Methods, and New Benchmarks for Language and Vision Models

    This podcast is brought to you by Scholar FM. ---------------------------------------- Papers included in this episode: 0:09 - Causely: A Causal Intelligence Layer for Enterprise AI A Benchmark Study on SRE and Reliability Workflows https://export.arxiv.org/pdf/2605.18327.pdf 1:12 - QSTRBench: a New Benchmark to Evaluate the Ability of Language Models to Reason with Qualitative Spatial and Temporal Calculi https://export.arxiv.org/pdf/2605.18380.pdf 2:08 - When Fireflies Cluster; Enhancing Automatic Clustering via Centroid-Guided Firefly Optimization https://export.arxiv.org/pdf/2605.18460.pdf 2:58 - OCCAM: Open-set Causal Concept explAnation and Ontology induction for black-box vision Models https://export.arxiv.org/pdf/2605.18481.pdf 3:46 - A Practical Noise2Noise Denoising Pipeline for High-Throughput Raman Spectroscopy https://export.arxiv.org/pdf/2605.18511.pdf ---------------------------------------- scholarfm.com

    5 min

  2. 18 MAY

    18.05.2026: LLM-Guided Knowledge Graphs, Model-Agnostic Protein Interaction Prediction, and Continual Learning Benchmarks

    This podcast is brought to you by Scholar FM. ---------------------------------------- Papers included in this episode: 0:10 - Evolving-RL: End-to-End Optimization of Experience-Driven Self-Evolving Capability within Agents https://export.arxiv.org/pdf/2605.10663.pdf ---------------------------------------- scholarfm.com

    1 min

  3. 11 MAY

    11.05.2026: Fine-Grained Graph Generation, Semantic Consistency in GNNs, and Causality for Trustworthy AI

    This podcast is brought to you by Scholar FM. ---------------------------------------- Papers included in this episode: 0:09 - Counterfactual Reasoning in Automated Planning https://export.arxiv.org/pdf/2605.02603.pdf 0:52 - SCGNN: Semantic Consistency enhanced Graph Neural Network Guided by Granular-ball Computing https://export.arxiv.org/pdf/2605.02617.pdf 1:45 - SCGNN: Semantic Consistency enhanced Graph Neural Network Guided by Granular-ball Computing https://export.arxiv.org/pdf/2605.02617.pdf 2:39 - Trustworthy AI Suffers from Invariance Conflicts and Causality is The Solution https://export.arxiv.org/pdf/2605.02640.pdf 3:24 - Fine-Grained Graph Generation through Latent Mixture Scheduling https://export.arxiv.org/pdf/2605.02780.pdf ---------------------------------------- scholarfm.com

    4 min

  4. 4 MAY

    04.05.2026: AI-Driven Protein Dynamics, Curvature-Aware Docking, and Multimodal Drug-Target Interaction Exploration

    This podcast is brought to you by Scholar FM. ---------------------------------------- Papers included in this episode: 0:08 - Learning Structure, Energy, and Dynamics: A Survey of Artificial Intelligence for Protein Dynamics https://export.arxiv.org/pdf/2604.25244.pdf ---------------------------------------- scholarfm.com

    1 min

  5. 27 APR

    27.04.2026: Contrastive 3D Learning, Multimodal Feature Fusion, and Automated Protein-Ligand Bioactivity Mining

    This podcast is brought to you by Scholar FM. ---------------------------------------- Papers included in this episode: 0:09 - Structure-guided molecular design with contrastive 3D protein-ligand learning https://export.arxiv.org/pdf/2604.19562.pdf 1:05 - BioMiner: A Multi-modal System for Automated Mining of Protein-Ligand Bioactivity Data from Literature https://export.arxiv.org/pdf/2604.21508.pdf ---------------------------------------- scholarfm.com

    2 min

  6. 20 APR

    20.04.2026: Thermodynamics-Driven Machine Learning, Protein-Molecule Interaction Mechanisms, and Controllable Molecular Optimization

    This podcast is brought to you by Scholar FM. ---------------------------------------- Papers included in this episode: 0:09 - TriFit: Trimodal Fusion with Protein Dynamics for Mutation Fitness Prediction https://export.arxiv.org/pdf/2604.12026.pdf 1:07 - Scaffold-Conditioned Preference Triplets for Controllable Molecular Optimization with Large Language Models https://export.arxiv.org/pdf/2604.12350.pdf 2:04 - Unraveling the Mechanism of Drug Binding to SARS-CoV-2 RNA Pseudoknot with Thermodynamics-Driven Machine Learning https://export.arxiv.org/pdf/2604.14906.pdf ---------------------------------------- scholarfm.com

    3 min

  7. 13 APR

    13.04.2026: Protein Dynamics Visualization, Controllable Design with AI, and 3D Structure-Aware Simulation

    This podcast is brought to you by Scholar FM. ---------------------------------------- Papers included in this episode: 0:10 - MAVEN: A Mesh-Aware Volumetric Encoding Network for Simulating 3D Flexible Deformation https://export.arxiv.org/pdf/2604.04474.pdf ---------------------------------------- scholarfm.com

    1 min

  8. 6 APR

    06.04.2026: Deep Learning for Protein States, Goal-Directed Molecular Generation, and Trillion-Scale Chemical Libraries

    This podcast is brought to you by Scholar FM. ---------------------------------------- Papers included in this episode: 0:08 - Estimating Protein Conformational States from High-Speed AFM Images with Molecular Dynamics and Deep Learning. https://doi.org/10.1021/acs.jcim.6c00142 1:01 - Discovery of WRN helicase inhibitors by 3D-CNN docking and ML consensus from traditional Chinese medicine monomers. https://doi.org/10.1016/j.jmgm.2026.109376 1:53 - Constructing and characterizing trillion-scale combinatorial chemical library. https://doi.org/10.1186/s13321-026-01185-7 2:44 - SiteContext: A Web Server for Protein Binding Site Comparison. https://doi.org/10.1016/j.jmb.2026.169791 3:38 - HybridMolGen: A Unified Framework for Goal-Directed Molecular Generation via Multi-Objective Reinforcement Learning. https://doi.org/10.1093/bioinformatics/btag170 ---------------------------------------- scholarfm.com

    5 min
  • 8 Episodes

About

Daily summaries of preprints from arXiv and bioRxiv. Generated for Decoding Biomolecular Languages.

Information