Weekly BioML Digest [December 22, 2025]

🧠 Machine Learning × Computational Biology Digest

Hey! Here’s your weekly digest with ML/CompBio papers from the last week. Enjoy, and happy holidays!

📚 Section 1: Peer-Reviewed Journals (Top 20)

468 papers matched filters → 20 selected after LLM relevance + novelty ranking.

• Generalizable and scalable protein stability prediction with rewired protein generative models
  Li, Ziang, Luo, Yunan — Nature Communications, 2025-12-20
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• Integrating protein language and geometric deep learning models for enhanced vaccine antigen prediction
  Zai, Xiaodong, Zhao, Yunxiang, Wang, Xiaolin, Leng, Mingyue, Lu, Menglong, Yang, Yilong, Zhao, Xiaofan, Li, Ruihua, Li, Yaohui, Zhang, Yue, Zhang, Jun, Li, Dongsheng, Ren, Hongguang, Xu, Junjie, Chen, Wei — Nature Communications, 2025-12-21
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• Designing molecular RNA switches with Restricted Boltzmann machines
  Fernandez-de-Cossio-Diaz, Jorge, Hardouin, Pierre, Lyonnet du Moutier, Francois-Xavier, Gioacchino, Andrea, Marchand, Bertrand, Ponty, Yann, Sargueil, Bruno, Monasson, Rémi, Cocco, Simona — Nature Communications, 2025-12-18
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• Engineered base editors with reduced bystander editing through directed evolution
  Perrotta, Ramiro M., Vinke, Svenja, Ferreira, Raphaël, Moret, Michaël, Mahas, Ahmed, Chiappino-Pepe, Anush, Riedmayr, Lisa M., Mehra, Anna-Thérèse, Lehmann, Louisa S., Church, George M. — Nature Biotechnology, 2025-12-18
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• Genome-scale spatial mapping of the Hodgkin lymphoma microenvironment identifies tumor cell survival factors
  Shanmugam, Vignesh, Tokcan, Neriman, Chafamo, Daniel, Sullivan, Sean, Borji, Mehdi, Martin, Haley, Newton, Gail, Nadaf, Naeem, Hanbury, Saoirse, Barrera, Irving, Cable, Dylan, Weir, Jackson, Ashenberg, Orr, Pinkus, Geraldine, Rodig, Scott, Uhler, Caroline, Macosko, Evan, Shipp, Margaret, Louissaint, Abner, Jr., Chen, Fei, Golub, Todd R. — Nature Communications, 2025-12-20
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• MIDAS: rapid, multiplexed molecular profiling for integrated host–pathogen analysis
  Lim, Yong Jun, Asadi Tokmedash, Mohammad, Allen, Matthew, Gruich, Cameron, Choi, Jun Hee, Kim, Changheon, Falkowski, Nicole, Goldsmith, Bryan, Stringer, Kathleen A., Dickson, Robert P., Bong, Ki Wan, Min, Jouha — Nature Communications, 2025-12-19
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• ChemFM as a scaling law guided foundation model pre-trained on informative chemicals
  Cai, Feiyang, Zacour, Katelin, Zhu, Tianyu, Tzeng, Tzuen-Rong, Duan, Yongping, Liu, Ling, Pilla, Srikanth, Li, Gang, Luo, Feng — Communications Chemistry, 2025-12-18
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• Superwater as a generative AI framework to predict water molecule positions on protein structures
  Kuang, Xiaohan, Liu, Yunchao Lance, Lin, Xiaobo, Spencer-Smith, Jesse, Derr, Tyler, Wu, Yinghao, Bitter, Hans, Hu, Yongbo, Meiler, Jens, Su, Zhaoqian — Communications Chemistry, 2025-12-18
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• A pooled Cell Painting CRISPR screening platform enables de novo inference of gene function by self-supervised deep learning
  Sivanandan, Srinivasan, Leitmann, Bobby, Lubeck, Eric, Sultan, Mohammad Muneeb, Stanitsas, Panagiotis, Ranu, Navpreet, Ewer, Alexis, Mancuso, Jordan E., Phillips, Zachary F., Kim, Albert, Bisognano, John W., Cesarek, John, Ruggiu, Fiorella, Feldman, David, Koller, Daphne, Sharon, Eilon, Kaykas, Ajamete, Salick, Max R., Chu, Ci — Nature Communications, 2025-12-16
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• An open-source screening platform accelerates discovery of drug combinations
  Wright, William C., Pan, Min, Phelps, Gregory A., Low, Jonathan, Currier, Duane, Sanjali, Ankita, Trotter, Marlon, Hwang, Jihye, Chapple, Richard H., Liu, Xueying, Bennett, Declan, Zhang, Yinwen, Lee, Richard E., Chen, Taosheng, Geeleher, Paul — Nature Communications, 2025-12-15
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• Comprehensive discovery of m^6A sites in the human transcriptome at single-molecule resolution
  Kang, Gihyeon, Hwang, Hyeonseo, Jeon, Hyeonseong, Choi, Heejin, Chang, Hee Ryung, Yeo, Nagyeong, Park, Junehee, Son, Narae, Jeon, Eunkyeong, Lim, Jungmin, Yun, Jaeung, Choi, Wook, Jo, Jae-Yoon, Kim, Jong-Seo, Park, Sangho, Kim, Yoon Ki, Baek, Daehyun — Nature Communications, 2025-12-15
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• Generalizable compound protein interaction prediction with a model incorporating protein structure aware and compound property aware language model representations
  Zhang, Yiming, Ishitani, Ryuichiro, Takemoto, Mizuki, Tomita, Atsuhiro — Communications Chemistry, 2025-12-19
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• DeepKinome: quantitative prediction of kinase binding affinity by a compound using deep learning based regression model
  Y. Lee, Jisu Eun, Jinhyuk Lee, Seungyoon Nam — Frontiers in Molecular Biosciences, 2025-12-17
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• MambaTransDTA: A Hybrid Mamba-Transformer Architecture for Accurate Drug-Target Binding Affinity Prediction.
  Xinpo Lou, Jianxiu Cai, Qidong Liu, Shirley W. I. Siu — Journal of chemical information and modeling, 2025-12-17
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• LGABAN: An Integrated Multi-Scale Approach Combining Graph and Sequence Features for Enhanced Prediction of Drug-Protein Interactions.
  Yi Wen, Shiyu Yan, Min Chen, Mohamed Amine Moatadid, Jiaoxing Yang — Journal of chemical information and modeling, 2025-12-18
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• A geometric graph-based deep learning model for drug-target affinity prediction
  Rana, Md Masud, Mukta, Farjana Tasnim, Nguyen, Duc D. — BMC Bioinformatics, 2025-12-18
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• ProjFusNet: deep neural network for peptide precursor prediction using projection-fused protein language model and structural features
  Li, Jinjin, Fang, Fang, Lin, Changhang, Shi, Hua, Cui, Feifei, Zhang, Zilong, Wei, Leyi — Journal of Cheminformatics, 2025-12-19
  abs

• ProMoHGT: a heterogeneous graph transformer with graph contrastive learning for robust microbial protein function prediction
  Sui, Jianan, Wang, Xiaomiao, Su, Yufeng, Gao, Menglong, Huang, Huanjie, Liu, Hao, Zhang, Jianfeng, Tang, Yaohan — BMC Genomics, 2025-12-17
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• An AI-driven multi-omics framework identifies lactylation-mediated therapeutic targets to overcome drug resistance in ovarian cancer
  Zhang, Lijia, Guo, Qi, Lei, Xue, Yin, Xinyu, Ling, Yun, Liu, Ye, Liu, Songjiang — npj Precision Oncology, 2025-12-20
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• Comprehensive molecular characterization of high-stemness gastric cancer cells using single-cell transcriptomics, spatial mapping, and machine learning
  Wang, Ziyi, Li, Xuehao, Wang, Jin, Yu, Huidong, Zhao, Defeng, Xu, Yan, Zhou, Siyu, Men, Wanfu — npj Precision Oncology, 2025-12-17
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🧬 Section 2: Preprints (arXiv + bioRxiv)

106 papers matched filters → 20 selected after LLM relevance + novelty ranking.

• 🧬 PXDesign: Fast, Modular, and Accurate De Novo Design of Protein Binders
  Ren, M.; Sun, J.; Guan, J.; Liu, C.; Gong, C.; Wang, Y.; Wang, L.; Cai, Q.; Ma, W.; Zhang, Y.; Liu, Z.; Zhang, H.; Chen, X.; Xiao, W. — bioRxiv, 2025-12-17
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• 📄 Structure-Aware Antibody Design with Affinity-Optimized Inverse Folding
  Xinyan Zhao, Yi-Ching Tang, Rivaaj Monsia, Victor J. Cantu, Ashwin Kumar Ramesh, Xiaozhong Liu, Zhiqiang An, Xiaoqian Jiang, Yejin Kim — arXiv, 2025-12-19
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• 🧬 DeepRank-Ab: a dedicated scoring function for antibody-antigen complexes based on geometric deep learning
  Xu, X.; Coratella, I.; Reys, V. G. P.; Bonvin, A. M. — bioRxiv, 2025-12-19
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• 🧬 ProFam: Open-Source Protein Family Language Modelling for Fitness Prediction and Design
  Wells, J.; Hawkins Hooker, A.; Livne, M.; Lin, W.; Miller, D. M.; Dallago, C.; Bordin, N.; Paige, B.; Rost, B.; Orengo, C.; Heinzinger, M. — bioRxiv, 2025-12-21
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• 🧬 Enigma: An Efficient Model for Deciphering Regulatory Genomics
  Jung, A. J.; Zhu, H.; Li, R.; Gao, A. J.; Lau, T. T. Y.; Chu, V. S.; Lim, D.; Cole, C. B.; Lee, L. J.; Celaj, A.; Frey, B. J. — bioRxiv, 2025-12-19
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• 🧬 Enhanced sampling of protein conformations in AlphaFold3 with repulsive bias in the diffusion generative model
  Ohnuki, J.; Okazaki, K.-i. — bioRxiv, 2025-12-18
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• 🧬 Foundation model reveals the shared organization of transcription and topologically associating domains
  Liang, H.; Berger, B.; Singh, R. — bioRxiv, 2025-12-16
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• 🧬 AlphaRING-X: accurate interpretation of missense variant deleteriousness based on protein structural stability
  Mamane-Logsdon, A.; Safari, R.; Barnard, A.; Maertens, G. N.; Bellos, E. — bioRxiv, 2025-12-16
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• 🧬 Identification of genomic features that uniquely impact estrogen receptor alpha binding and its effects on gene expression in endometrial cancer
  Richey, A.; Kitchen, N.; Rush, C. M.; Vahrenkamp, J. M.; Abewe, H.; Osborne, K. S.; Bott, A. J.; Dalley, B. K.; Rutter, J.; Gertz, J. — bioRxiv, 2025-12-15
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• 🧬 SpaCEy: Discovery of Functional Spatial Tissue Patterns by Association with Clinical Features Using Explainable Graph Neural Networks
  Rifaioglu, A. S.; Ervin, E. H.; Sarigun, A.; Germen, D.; Bodenmiller, B.; Tanevski, J.; Saez-Rodriguez, J. — bioRxiv, 2025-12-15
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• 🧬 DeepDOX1: A Dual-Drive Framework Integrating Deep Learning and First-Principles Physics for Drug-Protein Affinity Prediction
  Liu, Z.; Sun, H.; Wang, Y.; Ren, Y.; Rao, L.; Huang, Z.; Cao, H.; Hu, X.; Zhu, X.; Li, M.; Wan, J. — bioRxiv, 2025-12-15
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• 📄 Accelerating MHC-II Epitope Discovery via Multi-Scale Prediction in Antigen Presentation
  Yue Wan, Jiayi Yuan, Zhiwei Feng, Xiaowei Jia — arXiv, 2025-12-16
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• 🧬 SiaRNA: A Siamese Neural Network with Bidirectional Cross-Attention for Pairwise siRNA-mRNA Efficacy Prediction
  Vaishnavi, S.; Rajkumar, N.; Venkata Harshit, M.; Varun Raju, N.; Bhargava Chary, B.; Kondaparthi, V. — bioRxiv, 2025-12-16
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• 🧬 Fine-Grained Structural Classification of Biosynthetic Gene Cluster-Encoded Products
  Porokhin, V.; Mevers, E.; van der Hooft, J. J. J.; Hassoun, S. — bioRxiv, 2025-12-16
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• 🧬 GlycanGT: A Foundation Model for Glycan Graphs with Pretrained Representation and Generative Learning
  Kitani, A.; Zhang, B.; Himori, K.; Matsui, Y. — bioRxiv, 2025-12-16
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• 🧬 Quantitative profiling of millions of nucleotides reveals sequence-encoded interactions that govern plasmid propagation
  Copeman, T.; Fong, J. H. C.; Mayne, J. R.; Gorochowski, T. E.; Conde, S. R.; Ellis, T.; Ceroni, F. — bioRxiv, 2025-12-16
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• 🧬 TRIO-AI: Hybrid temporal graph, ODE, and VAE modeling for high-resolution cellular trajectory inference in liver injury
  li, h.; Ju, C.; Liu, H.; Wen, y.; Wang, j. — bioRxiv, 2025-12-19
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• 🧬 Cross-species etiologically informed stratification enables T cell receptor-based diagnosis of Parkinson's Disease
  Chen, J.; Xia, X.; Zhang, Y.; Tong, X.; Liang, Y.; Fan, X.; Tao, R.; Meng, Q.; Wei, Y.; Hu, G. — bioRxiv, 2025-12-18
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• 🧬 A Machine Learning- 3D Microvessel Platform Identifies Kinase Targets Restoring Blood-Brain-Barrier Endothelial Integrity.
  Shin, Y. J.; Wei, L.; Hong, S.; Ren, C.; Jeffrey, M.; Cardneas, J.; Higgins, H.; Ho, N.; Evitts, K.; Smith, J.; Dong, J.-f.; Kaushansky, A.; ZHENG, Y. — bioRxiv, 2025-12-15
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• 🧬 Deep learning inference of universal dormancy pseudotime reveals the cellular targets of anti-cancer therapies
  Beckmann, H. M.; Tong, M.; Chang, G.; Steif, A. — bioRxiv, 2025-12-16
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