Weekly BioML Digest [October 28, 2025]

Machine Learning × Computational Biology compilation from arXiv + bioRxiv

Hey! It's your weekly automated digest of machine learning papers in CompBio and Drug Discovery. Here is how it was created:

• Both arXiv and bioRxiv queried for new papers published in the past week [October 21, 2025 - October 27, 2025].
• Found 3461 new arXiv papers and 1301 new bioRxiv papers.
• 21 arXiv papers and 81 bioRxiv papers matched keyword filters.
• 30 papers are included in this digest after deduplication and ChatGPT relevance+novelty reranking.

If you find specific papers particularly interesting, feel free to leave a comment about it under the post at biomldigest.com. I think it would be great to share opinions, as it may help others in their research, and it will help me adjust the search algorithm in the future.

Here are your top 30 papers:

• 📄 Triangle Multiplication Is All You Need For Biomolecular Structure Representations
  Jeffrey Ouyang-Zhang, Pranav Murugan, Daniel J. Diaz, Gianluca Scarpellini, Richard Strong Bowen, Nate Gruver, Adam Klivans, Philipp Krähenbühl, Aleksandra Faust, Maruan Al-Shedivat — q-bio.QM, 2025-10-21
  abs · pdf

• 🧬 Tahoe-x1: Scaling Perturbation-Trained Single-CellFoundation Models to 3 Billion Parameters
  Gandhi, S.; Javadi, F.; Svensson, V.; Khan, U.; Jones, M. G.; Yu, J.; Merico, D.; Goodarzi, H.; Alidoust, N. — bioRxiv:systems biology, 2025-10-23
  abs · pdf

• 🧬 Accurate protein structure determination from cryo-EM maps using deep learning and structure prediction
  Li, T.; Chen, J.; Li, H.; Cao, H.; Huang, S.-Y. — bioRxiv:bioinformatics, 2025-10-24
  abs · pdf

• 🧬 M-DeepAssembly2: A Web Server for Predicting Multiple Conformations of Multi-domain Proteins Using Deep Learning
  Cui, X.; Ge, L.; Yang, X.; Li, X.; Zhang, G. — bioRxiv:bioinformatics, 2025-10-24
  abs · pdf

• 🧬 Venus-MAXWELL: Efficient Learning of Protein-Mutation Stability Landscapes using Protein Language Models
  Yu, Y.; Jiang, F.; Ma, X.; Zhang, L.; Zhong, B.; Ouyang, W.; Fan, G.; Yu, H.; Hong, L.; Li, M. — bioRxiv:bioinformatics, 2025-10-24
  abs · pdf

• 🧬 MetaboFM: A Foundation Model for Spatial Metabolomics
  Ozturk, E.; Moctezuma, F. G. R.; Coskun, A. F. — bioRxiv:bioinformatics, 2025-10-24
  abs · pdf

• 📄 Uncertainty-Aware Multi-Objective Reinforcement Learning-Guided Diffusion Models for 3D De Novo Molecular Design
  Lianghong Chen, Dongkyu Eugene Kim, Mike Domaratzki, Pingzhao Hu — cs.LG, 2025-10-24
  abs · pdf

• 🧬 SLOGEN: A Structure-based Lead Optimization Model Unifying Fragment Generation and Screening
  Yang, B.; Xu, Y.; Xiang, C.; Zhu, Y.; Li, T.; Sinitskiy, A.; Li, J. — bioRxiv:bioinformatics, 2025-10-24
  abs · pdf

• 📄 Learning Boltzmann Generators via Constrained Mass Transport
  Christopher von Klitzing, Denis Blessing, Henrik Schopmans, Pascal Friederich, Gerhard Neumann — cs.LG, 2025-10-21
  abs · pdf

• 📄 Extending machine learning model for implicit solvation to free energy calculations
  Rishabh Dey, Michael Brocidiacono, Kushal Koirala, Alexander Tropsha, Konstantin I. Popov — physics.chem-ph, 2025-10-23
  abs · pdf

• 🧬 Multi-omics integration and batch correction using a modality-agnostic deep learning framework
  Alvira Larizgoitia, J. I.; Partel, G.; Venturelli, L.; Zhang, W.; Spotbeen, X.; Vanuytven, S.; Kint, S.; Vandereyken, K.; Wouters, D.; Ismail, A.; Scarceriaux, R.; Idkowiak, J.; Sarretto, T.; Ellis, S. R.; Loda, M.; Socciarelli, F.; Gevaert, T.; Joniau, S.; Claesen, M.; Verbeeck, N.; Voet, T.; Swinnen, J.; Jacobs, J.; Sifrim, A. — bioRxiv:bioinformatics, 2025-10-22
  abs · pdf

• 🧬 A blueprint for mutation-defined hallmark vulnerabilities across human cancers
  Xu, R.; Gil, R. S.; Liu, X. T.; Qi, Y.; Tran, D.; Xu, C.; Wong, J. J.-L.; Munoz, L.; Mann, G. J.; Feng, Y. — bioRxiv:cancer biology, 2025-10-25
  abs · pdf

• 📄 MS-BART: Unified Modeling of Mass Spectra and Molecules for Structure Elucidation
  Yang Han, Pengyu Wang, Kai Yu, Xin Chen, Lu Chen — cs.LG, 2025-10-23
  abs · pdf

• 🧬 A universal model for drug-receptor interactions
  Menezes, F.; Wahida, A.; Froehlich, T.; Grass, P.; Zaucha, J.; Napolitano, V.; Siebenmorgen, T.; Pustelny, K.; Barzowska-Gogola, A.; Rioton, S.; Didi, K.; Bronstein, M.; Czarna, A.; Hochhaus, A.; Plettenburg, O.; Sattler, M.; Nissen-Meyer, J.; Conrad, M.; Kurzrock, R.; Popowicz, G. M. — bioRxiv:bioinformatics, 2025-10-24
  abs · pdf

• 🧬 Spatially varying cell-specific gene regulation network inference
  Li, Y.; Chen, J.; Wang, H. — bioRxiv:bioinformatics, 2025-10-23
  abs · pdf

• 🧬 Modelling transcription with explainable AI uncovers context-specific epigenetic gene regulation at promoters and gene bodies
  Chhatbar, K.; Bird, A.; Sanguinetti, G. — bioRxiv:bioinformatics, 2025-10-23
  abs · pdf

• 🧬 IRIS: A Machine Learning-Based Pose Re-Ranking Tool for RNA-Ligand Docking
  Amburn, A.; Jayaraman Rukmani, S.; Parks, J. M.; Smith, J. C. — bioRxiv:molecular biology, 2025-10-25
  abs · pdf

• 🧬 Deep Learning Bridges Histology and Transcriptomics to Predict Molecular Subtypes and Outcomes in Muscle-Invasive Bladder Cancer
  Blondel, A.; Krucker, C.; Harter, V.; Da Silva, M.; Groeneveld, C.; De Reynies, A.; Karimi, M.; Benhamou, S.; Bernard-Pierrot, I.; Pfister, C.; Culine, S.; Allory, Y.; Walter, T.; Fontugne, J. — bioRxiv:cancer biology, 2025-10-24
  abs · pdf

• 🧬 Universal super-resolution for subcellular fluorescence imaging
  Xu, X.; Zhang, R.; Chen, Q.; Gao, X.; Xie, Z.; Lin, D.; Yan, W.; Wang, X.; Pan, L.; Liu, L.; Li, J.; Qu, J. — bioRxiv:bioinformatics, 2025-10-26
  abs · pdf

• 🧬 Generating Synthetic MR Perfusion Maps from DWI and FLAIR in Acute Ischemic Stroke using Deep Learning
  Matsulevits, A.; Koch, A.; Mahe-Verdure, C.; Bendszus, M.; Hilbert, A.; Boullet, M.; Marnat, G.; Mutke, M.; Aydin, O.; Olindo, S.; Sibon, I.; Thiebaut de Schotten, M.; Tourdias, T.; Frey, D. — bioRxiv:neuroscience, 2025-10-24
  abs · pdf

• 🧬 Gradient-based Optimization for mRNA Sequence Design
  Li, H.; Terai, G.; Otagaki, T.; Asai, K. — bioRxiv:bioinformatics, 2025-10-23
  abs · pdf

• 📄 Leveraging Classical Algorithms for Graph Neural Networks
  Jason Wu, Petar Veličković — cs.LG, 2025-10-24
  abs · pdf

• 📄 Layer-to-Layer Knowledge Mixing in Graph Neural Network for Chemical Property Prediction
  Teng Jiek See, Daokun Zhang, Mario Boley, David K. Chalmers — cs.LG, 2025-10-23
  abs · pdf

• 📄 M-GLC: Motif-Driven Global-Local Context Graphs for Few-shot Molecular Property Prediction
  Xiangyang Xu, Hongyang Gao — cs.LG, 2025-10-24
  abs · pdf

• 🧬 NyxBind: enhancing DNN representations via contrastive learning for TFBS prediction
  Yang, X.; Xiao, Q.; Xu, Y.; Yang, J.; Hou, Y.; Long, W.; Huang, M.; Zhang, Y. — bioRxiv:bioinformatics, 2025-10-23
  abs · pdf

• 🧬 A machine learning method for calculating highly localized protein stabilities
  Lu, C.; Weber, K. C.; McBride, S. K.; Reckers, A.; Glasgow, A. — bioRxiv:biophysics, 2025-10-23
  abs · pdf

• 🧬 KSMoFinder - Knowledge graph embedding of proteins and motifs for predicting kinases of human phosphosites
  Anandakrishnan, M.; Ross, K. E.; Chen, C.; Vijay-Shanker, K.; Wu, C. H. — bioRxiv:bioinformatics, 2025-10-23
  abs · pdf

• 🧬 Evolutionary Reasoning Does Not Arise in Standard Usage of Protein Language Models
  Ektefaie, Y.; Shen, A.; Jain, L.; Farhat, M. R.; Zitnik, M. — bioRxiv:bioinformatics, 2025-10-24
  abs · pdf

• 📄 g-DPO: Scalable Preference Optimization for Protein Language Models
  Constance Ferragu, Jonathan D. Ziegler, Nicolas Deutschmann, Arthur Lindoulsi, Eli Bixby, Cradle ML Team — cs.LG, 2025-10-22
  abs · pdf

• 📄 Protein generation with embedding learning for motif diversification
  Kevin Michalewicz, Chen Jin, Philip Alexander Teare, Tom Diethe, Mauricio Barahona, Barbara Bravi, Asher Mullokandov — q-bio.QM, 2025-10-21
  abs · pdf