Weekly BioML Digest [January 12, 2026]

Machine Learning × Computational Biology paper compilation

Hey! It's your weekly digest of machine learning papers in CompBio and Drug Discovery.

Better late than never is our slogan for this week:) Springer Nature API issues have been resolved and peer-reviewed section is back. Enjoy!

Feedback? Email me at biomldigest@gmail.com.

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

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

• Improved protein binder design using β-pairing targeted RFdiffusion
  Sappington, Isaac, Toul, Martin, Lee, David S., Robinson, Stephanie A., Goreshnik, Inna, McCurdy, Clara, Chan, Tung Ching, Buchholz, Nic, Huang, Buwei, Vafeados, Dionne, Garcia-Sanchez, Mariana, Roullier, Nicole, Glögl, Matthias, Kim, Christopher J., Watson, Joseph L., Torres, Susana Vázquez, Verschueren, Koen H. G., Verstraete, Kenneth, Hinck, Cynthia S., Benard-Valle, Melisa, Coventry, Brian, Sims, Jeremiah Nelson, Ahn, Green, Wang, Xinru, Hinck, Andrew P., Jenkins, Timothy P., Ruohola-Baker, Hannele, Banik, Steven M., Savvides, Savvas N., Baker, David — Nature Communications, 2026-01-10
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• A deep learning and large language hybrid workflow for omics interpretation
  Tang, Dachao, Zhang, Chi, Zhang, Weizhi, Lu, Funian, Xiao, Leming, Huang, Xinhe, Shao, Jiangyi, Liu, Dan, Fu, Shanshan, Zhao, Miaoying, Zhang, Luoying, Jia, Da, Shen, Han-Ming, Sun, Chaoyang, Chen, Gang, Liu, Bin, Peng, Di, Xue, Yu — Nature Biomedical Engineering, 2026-01-08
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• Learning the language of protein-protein interactions
  Ullanat, Varun, Jing, Bowen, Sledzieski, Samuel, Berger, Bonnie — Nature Communications, 2026-01-07
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• Deep learning guided design of protease substrates
  Martin-Alonso, Carmen, Alamdari, Sarah, Samad, Tahoura S., Yang, Kevin K., Bhatia, Sangeeta N., Amini, Ava P. — Nature Communications, 2026-01-06
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• Deep learning-assisted discovery of a potent and cell-active inhibitor of RNA N^6-methyladenosine recognition protein YTHDC2
  Yang, Zhenyu, Sun, Weining, Huang, Qiao, Li, Yueyue, Yuan, Meng, Yang, Yu, Zhao, Heng, Liu, Zheyi, Zeng, Xiaoxi, Wang, Fangjun, Jiang, Yuanyuan, Zhao, Yi, Chen, Runsheng — Nature Communications, 2026-01-06
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• VISTA uncovers missing gene expression and spatial-induced information for spatial transcriptomic data analysis
  Liu, Tianyu, Lin, Yingxin, Luo, Xiao, Sun, Yizhou, Zhao, Hongyu — Communications Biology, 2026-01-08
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• Mimicking opioid analgesia in cortical pain circuits
  Oswell, Corinna S., Rogers, Sophie A., James, Justin G., McCall, Nora M., Hsu, Alex I., Salimando, Gregory J., Mahmood, Malaika, Wooldridge, Lisa M., Wachira, Meghan, Jo, Adrienne Y., Sandoval Ortega, Raquel Adaia, Wojick, Jessica A., Beattie, Katherine, Farinas, Sofia A., Chehimi, Samar N., Rodrigues, Amrith, Wu, Jacqueline W. K., Ejoh, Lindsay L., Kimmey, Blake A., Lo, Emily, Azouz, Ghalia, Vasquez, Jose J., Banghart, Matthew R., Beier, Kevin T., Creasy, Kate Townsend, Crist, Richard C., Ramakrishnan, Charu, Reiner, Benjamin C., Deisseroth, Karl, Yttri, Eric A., Corder, Gregory — Nature, 2026-01-07
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• The inflammatory path toward type 1 diabetes begins during pregnancy
  Ahrens, Angelica P., Dias, Raquel, Hyötyläinen, Tuulia, Orešič, Matej, Triplett, Eric W., Ludvigsson, Johnny — Nature Communications, 2026-01-07
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• Harnessing machine learning-driven multiomics integration: deciphering programmed cell death networks for prognostication and immunotherapy prediction in lung adenocarcinoma
  Chang, Wuguang, Luo, Bin, Wen, Zhesheng, Chen, Youfang — Cell Biology and Toxicology, 2026-01-07
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• A machine learning-defined cellular senescence signature systematically enhances prognostication and guides immunotherapy strategies for the treatment of gliomas
  Xu, Tianbing, Huang, Jing, Liu, Yufei, Lu, Lisen, Lovell, Jonathan F., Zhu, Mingxin, Jin, Honglin — npj Precision Oncology, 2026-01-07
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• PRIME: an interpretable artificial intelligence model based on liquid biopsy improves prediction of progression risk in non-small cell lung cancer
  Wang, Yu, Xiang, Yong-Bo, Chen, Xiao-Wei, Zhang, Tao, Wang, Jian-Yang, Liu, Wen-Yang, Deng, Lei, Wang, Lu-Hua, Gao, Shu-Geng, Bi, Nan — Military Medical Research, 2026-01-06
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• Detection of primary cancer types via fragment size selection in circulating cell-free extrachromosomal circular DNA
  Fang, Jingwen, Luo, Songwen, Li, Shouzhen, Xu, Yehong, Wang, Jing, Shan, Benjie, Hu, Mingjun, Yu, Qiaoni, Zhang, Wen, Liu, Ke, Shao, Yunying, Yang, Jiaxuan, Zhou, YouYang, Xu, Guangtao, Yao, Xinfeng, Sun, Ruoming, Zhang, Mengyuan, Li, Kun, Xu, Xihai, Zhang, Yongliang, Zhang, Zhihong, Han, Xinghua, Pan, Yueyin, Guo, Chuang, Qu, Kun — Genome Medicine, 2026-01-06
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• Structural variation drives enhancer hijacking via 3D genome disruption in ccRCC
  Dong, Yu, Xia, Wenjiao, Yang, Zitong, Ren, Liangliang, Wang, Hongru, Zhou, Yiyang, Li, Qinchen, Chen, Zhi, Xia, Zhinan, Zheng, Yichun, Wang, Feifan, He, Ning, Cheng, Bing, Ma, Dongmei, Shao, Wei, Guo, Wei, Wang, Shuwen, Liu, Ziqiao, Shen, Junxiao, Qi, Yiming, Gong, Xuke, Jin, Juan, Xie, Bo, Zhu, Guixin, Zhang, Cheng — npj Digital Medicine, 2026-01-06
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• Soft sonocapacitor with topologically integrated piezodielectric nanospheres enables wireless epidural closed-loop neuromodulation
  Wei, Zhidong, Jin, Fei, Li, Tong, Qian, Lili, Ma, Juan, Liu, Fengling, Zheng, Weiying, Wang, Yu, Zhang, Siwei, You, Ye, Feng, Zhang-Qi, Wang, Ting — Nature Communications, 2026-01-06
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• EMMPREDMLsub: multi-label prediction of mRNA subcellular localization based on the ESM2 large language model and MMDO-MDPU resampling strategy.
  Haoyue Luo, Yun Zuo, Jiayue Liu, Jun Wan, Wenying He, Xiangrong Liu, Zhaohong Deng — Journal of biomolecular structure & dynamics, 2026-01-06
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• QSAR Prediction of BBB Permeability Based on Machine Learning upon PETBD: A Novel Data Set of PET Tracers.
  Qing Su, Zhilong Ye, Chunyan Han, Ganyao Xiao, Jiazhi Chen, Haiyan Chen, Zigui Wang, Shun Huang, Lu Wang, Grace Peng, Wei Zhou, Zhiyun Du — Journal of medicinal chemistry, 2026-01-06
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• Model-based deep learning enables time-resolved computational microscopy
  Gao, Yunhui, Cao, Liangcai — PhotoniX, 2026-01-07
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• Uncertainty-aware machine learning to predict non-cancer human toxicity for the global chemicals market
  Borries, Kerstin, Beckwith, Katie V., Goodman, Jonathan M., Chiu, Weihsueh A., Jolliet, Olivier, Fantke, Peter — Nature Communications, 2026-01-07
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• A self-supervised machine learning pipeline for extracting information from live cell images at multiple doses and timepoints
  Isaev, Dmitry Yu., Liu, Wen Pei, Cuevas, Marc, Tang, Yubo, Ang, Kenny, Wilson, Chris, Mai, Quynh, Adra, Jovani, Cruz, Allan, Nguyen, Khoi, Ricasa, Michael, Gupta, Ankur, Hamadani, Mehrdad, Sridharan, Deepa, Yeghiazarians, Yerem, Ameri, Kurosh — Scientific Reports, 2026-01-07
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• Advancing spatial cellular communication inference with ligand diffusion and transport model
  Yu, Jiating, Zhao, Jinyue, Ren, Tao, Sun, Duanchen, Wu, Ling-Yun — Communications Biology, 2026-01-07
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🧬 Section 2: Preprints (arXiv + bioRxiv)

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

• 🧬 De novo design of metalloproteases for targeted amyloid-β cleavage
  Qu, Y.; Wang, C.; Zhu, H.; Wang, Y.; Cao, L. — bioRxiv, 2026-01-06
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• 🧬 Phenotype-Guided In Silico Molecular Generation Using Large Language Models
  Jiang, Q.; Ye, X.; Guo, Z.; Xia, Y.; Liu, Z.; Xu, J.; Jin, P.; Ju, F.; Xia, H.; Feng, S.; Jiang, R.; Liu, H.; Qin, T.; Deng, P.; Shao, S. — bioRxiv, 2026-01-05
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• 🧬 Controllable All-Atom Protein Generation with Latent Diffusion
  Lu, A. X.; Yan, W.; Robinson, S. A.; Kelow, S.; Yang, K. K.; Gligorijevic, V.; Cho, K.; Bonneau, R.; Abbeel, P.; Frey, N. C. — bioRxiv, 2026-01-07
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• 🧬 Dual-encoder contrastive learning accelerates enzyme discovery
  Rocks, J. W.; Truong, D. P.; Rappoport, D.; Maddrell-Mander, S.; Martin-Alarcon, D. A.; Lee, T. M.; Crossan, S.; Goldford, J. E. — bioRxiv, 2026-01-07
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• 📄 Surface-based Molecular Design with Multi-modal Flow Matching
  Fang Wu, Zhengyuan Zhou, Shuting Jin, Xiangxiang Zeng, Jure Leskovec, Jinbo Xu — arXiv, 2026-01-08
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• 🧬 moPPIt: De Novo Generation of Motif-Specific and Functionally Active Peptide Binders via Discrete Flow Matching
  Chen, T.; Quinn, Z.; Mishra, K.; O'Connor, E. C.; Silver, S. E.; Zhang, Y.; Valencia, M. J.; Mei, Y.; Behmoaras, J.; Ferreira, L. M. R.; Chatterjee, P. — bioRxiv, 2026-01-09
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• 🧬 AptaBLE: A Deep Learning Platform for Aptamer Generation and Analysis
  Patel, S.; Peng, F. Z.; Fraser, K.; Dwivedy, A.; Gandavadi, D.; Wang, X.; Chatterjee, P.; Yao, S. — bioRxiv, 2026-01-07
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• 🧬 Small Molecule Approach to RNA Targeting Binder Discovery (SMARTBind) Using Deep Learning Without Structural Input
  Jiang, S.; Taghavi, A.; Wang, T.; Meyer, S. M.; Childs-Disney, J. L.; Li, C.; Disney, M. D.; Li, Y. — bioRxiv, 2026-01-07
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• 🧬 Learning a PRECISE language for small-molecule binding
  Erden, M.; Zhang, X.; Devkota, K.; Singh, R.; Cowen, L. — bioRxiv, 2026-01-05
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• 🧬 KASSPer: Kinase Active Site Structure Prediction using Protein and Ligand Language Models and Its Application to Virtual Screening
  Jang, W.; Shin, W.-H. — bioRxiv, 2026-01-08
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• 📄 AntibodyDesignBFN: High-Fidelity Fixed-Backbone Antibody Design via Discrete Bayesian Flow Networks
  Yue Hu, YingChao Liu — arXiv, 2026-01-09
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• 🧬 Context-aware Multi-Property Antibody Predictor: a Novel Framework Integrating Text and Protein Language Models
  Giancardo, L.; Yilmaz, M.; Lee, E.; Ren, K.; Zhao, Y.; Trang, G.; Sonmez, K.; Cheng, N. — bioRxiv, 2026-01-08
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• 🧬 HERMES: Holographic Equivariant neuRal network model for Mutational Effect and Stability prediction
  Visani, G. M.; Jones, Z.; Galvin, W.; Pun, M. N.; Daniel, E.; Borisiak, K.; Wagura, U.; Nourmohammad, A. — bioRxiv, 2026-01-09
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• 🧬 GraphESMStable: A Deep Learning Framework for Protein Stability Prediction Fusing Pre-trained Sequence Models and Graph Neural Networks
  Zhang, H.; Li, Z.; He, J. — bioRxiv, 2026-01-09
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• 🧬 Protein Language Models Trained on Biophysical Dynamics Inform Mutation Effects
  Hou, C.; Zhao, H.; Shen, Y. — bioRxiv, 2026-01-07
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• 🧬 NetMHCIIphosPan: a machine learning tool for predictingHLA class II antigen presentation of phosphorylated peptides.
  Alvarez, H. M. G.; Kaabinejadian, S.; Yari, H.; Shepherd, C. M.; Hildebrand, W. H.; Sette, A.; Peters, B.; Parker, R.; Ternette, N.; Nielsen, M. — bioRxiv, 2026-01-05
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• 🧬 DNA sequence quantitatively encodes CTCF-binding affinity at genome scale
  Yin, Z.; Wang, Y.; Hou, G.; Chen, Y.; Feng, H.; Zhu, J.; Xie, Y.; Wang, R.; Zhang, Z.; Wu, T.; Huang, H.; Xie, S.; Wang, W.; Gu, W.; Wu, Q.; Shen, N.; Guo, Y. — bioRxiv, 2026-01-05
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• 🧬 Predicting the Evolutionary and Functional Landscapes of Viruses with a Unified Nucleotide-Protein Language Model: LucaVirus
  Pan, Y.; He, Y.; Liu, Y.-Q.; Shan, Y.-T.; Liu, S.-N.; Ma, J.-H.; Liu, X.; Pan, X.; Bai, Y.; Xu, Z.; Hou, T.; Wang, Z.; Ye, J.; Holmes, E. C.; Li, B.; Chen, Y.-Q.; Li, Z.-R.; Shi, M. — bioRxiv, 2026-01-05
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• 📄 ChemBART: A Pre-trained BART Model Assisting Organic Chemistry Analysis
  Kenan Li, Yijian Zhang, Jin Wang, Haipeng Gan, Zeying Sun, Xiaoguang Lei, Hao Dong — arXiv, 2026-01-06
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• 🧬 Protein Language Models: Is Scaling Necessary?
  Fournier, Q.; Vernon, R. M.; van der Sloot, A.; Schulz, B.; Chandar, S.; Langmead, C. J. — bioRxiv, 2026-01-05
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