Weekly BioML Digest [March 30, 2026]

Machine Learning × Computational Biology paper compilation

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

Feedback? Email me at biomldigest@gmail.com.

📚 Peer-Reviewed Journals (Top 20)

586 matched filters -> 20 selected after LLM relevance + novelty ranking.

• Clustering the protein universe of life using DIAMOND DeepClust
  Buchfink, Benjamin J., Barbé, Émile, Ashkenazy, Haim, Reuter, Klaus, Kennedy, John A., Drost, Hajk-Georg — Nature Methods, 2026-03-24
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• Regulatory grammar in human promoters uncovered by MPRA-based deep learning
  Barbadilla-Martínez, Lucía, Klaassen, Noud, Franceschini-Santos, Vinícius H., Breda, Jérémie, Yücel, Hatice, Hernández-Quiles, Miguel, Lieshout, Tijs, Urzua Traslaviña, Carlos G., Boi, Minh Chau Luong, Akbarzadeh, Maryam, Hermana-Garcia-Agullo, Celia, Gregoricchio, Sebastian, Haas, Marcel, Straver, Roy, Derks, Sarah, Zwart, Wilbert, Voest, Emile, Franke, Lude, Vermeulen, Michiel, Ridder, Jeroen, Steensel, Bas — Nature, 2026-03-26
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• Integration of alternative fragmentation techniques into standard LC-MS workflows using a single deep learning model enhances proteome coverage
  Levin, Nikita, Saylan, Cemil Can, Lapin, Joel, Demyanenko, Yana, Yang, Kevin L., Sidda, John, Nesvizhskii, Alexey I., Wilhelm, Mathias, Mohammed, Shabaz — Nature Methods, 2026-03-23
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• 3d-OT: a deep geometry-aware framework for heterogeneous slices alignment of spatial multi-omics
  Dai, Bingjie, Yi, Litai, Wang, Peizhuo, Li, Hanshuang, Hu, Pengwei, Song, Yancheng, Xing, Jixiang, Feng, Zhenxing, Yuan, Zhiyuan, Zuo, Yongchun — Nature Methods, 2026-03-27
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• Atlas of predicted protein complex structures across kingdoms
  Qi, Xianzhi, Ye, Cheng, Liang, Jianqiang, Wen, Shimin, Li, Yuanyuan, Ding, Kai, Hao, Yongfu, Fei, Junjie, Mao, Weian, Li, Liupeng, Lin, Zhiyu, Shen, Yichong, Zhu, Hongjie, Hu, Yayun, Zhang, Rui, Ji, Pengli, Lu, Yafei, Liu, Bonan, Wang, Han, Chen, Yuxuan, Ma, Zhenguo, Yang, Peiyuan, Xu, Xinyu, Wu, Junlong, Zhu, Youyuan, Zou, Qiaosha, Zhu, Wencheng, Yao, Kelu, Li, Shuya, Xin, Hongyi, Ergu, Daji, Zeng, Jianyang, Xiao, Zhi-Xiong Jim, Shen, Chunhua, Cai, Ying, Yi, Yong, Ma, Dacheng — Nature Communications, 2026-03-25
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• Generative AI for misalignment-resistant virtual staining to accelerate histopathology workflows
  Ma, Jiabo, Li, Wenqiang, Li, Jinbang, Liu, Ziyi, Wu, Linshan, Zhou, Fengtao, Liang, Li, Chan, Ronald Cheong Kin, Wong, Terence T. W., Chen, Hao — Nature Communications, 2026-03-27
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• Toward ultimate NMR resolution with deep learning
  Amir Jahangiri, Tatiana Agback, Ulrika Brath, Vladislav Orekhov — Science Advances, 2026-03-27
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• Machine learning–directed massively parallel programmable nucleic acid amplification
  Zhi Weng, Wenle Huang, Yi Wu, Xuehao Xiu, Hui Lv, Fei Wang, Xiaolei Zuo, Chunhai Fan, Ping Song — Science Advances, 2026-03-25
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• DeepISO: deep learning-powered prediction of protein–protein interaction rewiring generated by alternative splicing
  Guo, Xiaokun, Jiang, Linyang, Li, Jiajun, Yuan, Mengdi, Li, Dianke, Shi, Wenyu, Zhang, Ziding, Wuchty, Stefan — Genome Biology, 2026-03-27
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• Accurate protein-protein interactions modeling through physics-informed geometric invariant learning
  Rao, Jiahua, Liu, Deqin, Zhou, Xiaolong, Yuan, Qianmu, Wei, Wentao, Lu, Wei, Zhang, Jixian, Rong, Yu, Yang, Yuedong, Zheng, Shuangjia — Communications Biology, 2026-03-27
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• GlycanGT: A Pretrained Graph Transformer Framework for Glycan Graph Representation and Generative Learning
  Akihiro Kitani, Bingyuan Zhang, Koichi Himori, Yusuke Matsui — Bioinformatics, 2026-03-28
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• A Deep Learning-Driven Framework Integrating Organoid-Based Functional Validation Identifies Universal Neoantigens from Recurrent Glioma Mutations
  Chen Wang, Ting Sun, Yufei He, Mingchen Yu, Chang-Qing Pan, Huimin Hu, Yishuo Sun, Die Wang, Zhongliang Cui, Jiazheng Zhang, Y. Zhai, Zhongfang Shi, Ziwei Li, Menghui Xu, Young Taik Oh, T. Jiang, Zhiyuan Xu, Guanzhang Li, Jing Zhang, Wei Zhang — Cancer Research, 2026-03-26
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• Tumor lactate metabolism shapes immune suppression and therapeutic resistance revealed by integrative multi-omics and digital pathology
  B. Feng, Yongwu Zhu, Zheng-xing Zhang, Yu Wang, Patrick J. Schuler, Jochen Hess — Frontiers in Immunology, 2026-03-26
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• SegDesign: A modular framework for controllable protein segment engineering
  Chenjie Feng, Junbo Yin, Chao Zha, M. Saif, Xiaopeng Xu, Xin Gao, Wenjia He — Protein Science, 2026-03-25
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• ThermoFormer: Predicting Protein Melting Temperature Through Large-Scale Pretraining
  Jingchuan Li, Mingchen Li — Catalysts, 2026-03-24
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• Improving severity grading of chemotherapy-induced myelosuppression in AML via data-driven and model-based deep learning
  Zhou, Yu, Xiao, Yuyang, Wang, Qian, Mo, Chenfeng, Cao, Rui, Liu, Hongli, Ma, Xin, Fu, Li, Gao, Huimin, Xu, Li, Jin, Suoqin, Zhou, Fuling, Zou, Xiufen — npj Systems Biology and Applications, 2026-03-24
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• Mapping the local effectiveness of mass drug administration for malaria using transportability methods
  Roh, Michelle E., Tong, Yanwei, Heitmann, Gabriella Barratt, Jia, Junran, Ba, El-hadji Konko Ciré, Ndiaye, Jean Louis, Fogelson, Ari, Milligan, Paul, Seck, Amadou, Diallo, Abdoulaye, Lo, Aminata Colle, Baiocchi, Michael, Gosling, Roly, Bennett, Adam, Hsiang, Michelle S., Benjamin-Chung, Jade — Nature Health, 2026-03-24
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• ProtCross: Bridging the PDB-AlphaFold Gap for Binding Site Prediction with Protein Point Clouds.
  Shuyu Zhong, Yuying Jiang — Journal of chemical information and modeling, 2026-03-24
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• KinForm: kinetics-informed feature optimised representation models for enzyme k_cat and K_M prediction
  Alwer, Saleh, Fleming, Ronan M. T. — npj Systems Biology and Applications, 2026-03-28
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• PRIMED: predicting DNA binding residues by leveraging pre-trained protein language models
  Lu Zhang, Xin Li, R. Song, Qianqian Song, Xiaodong Fan — Frontiers in Artificial Intelligence, 2026-03-25
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🧬 Preprints (arXiv + bioRxiv)

126 matched filters -> 20 selected after LLM relevance + novelty ranking.

• 🧬 Teaching Diffusion Models Physics: Reinforcement Learning for Physically Valid Diffusion-Based Docking
  Broster, J. H.; Popovic, B.; Kondinskaia, D.; Deane, C. M.; Imrie, F. — bioRxiv, 2026-03-27
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• 🧬 Evaluating SARS-CoV-2 Antibody Resilience via Prediction and Design of Escape Viral Variants
  Huot, M.; Rosenbaum, P.; Planchais, C.; Mouquet, H.; Monasson, R.; Cocco, S. — bioRxiv, 2026-03-27
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• 🧬 A single-cell and spatial atlas of prostate cancer reveals the combinatorial nature of gene modules underlying lineage plasticity and metastasis
  Song, H.; Xu, J.; Velazquez-Arcelay, K.; Demirci, A.; Raizenne, B. L.; Hsu, S. C.; Choi, J.; Pham, J. H.; Chen, Y.-A.; Weinstein, H. N. W.; Salzman, I.; Tsui, M.; Akutagawa, J.; Adingo, W.; Goldschmidt, E.; Carroll, P. R.; Hong, J. C.; Heaphy, C. M.; Cooperberg, M. R.; Greenland, N.; Campbell, J. D.; Huang, F. W. — bioRxiv, 2026-03-27
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• 🧬 Protein Electrostatic Properties are Finetuned Through Evolution
  Shen, M.; Dayhoff, G. W.; Kortzak, D.; Shen, J. — bioRxiv, 2026-03-29
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• 🧬 IDPForge: Deep Learning of Proteins with Global and Local Regions of Disorder
  De Castro, S.; Zhang, O.; Liu, Z. H.; Forman-Kay, J. D.; Head-Gordon, T. — bioRxiv, 2026-03-27
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• 📄 A Priori Sampling of Transition States with Guided Diffusion
  Hyukjun Lim, Soojung Yang, Lucas Pinède, Miguel Steiner, Yuanqi Du, Rafael Gómez-Bombarelli — arXiv, 2026-03-26
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• 🧬 Chiron3D: an interpretable deep learning framework for understanding the DNA code of chromatin looping
  Hoenig, S.; Grover, A.; Neri, P.; Surdez, D.; Boeva, V. — bioRxiv, 2026-03-23
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• 📄 ZeroFold: Protein-RNA Binding Affinity Predictions from Pre-Structural Embeddings
  Josef Hanke, Sebastian Pujalte Ojeda, Shengyu Zhang, Werngard Czechtizky, Leonardo De Maria, Michele Vendruscolo — arXiv, 2026-03-24
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• 📄 Central Dogma Transformer III: Interpretable AI Across DNA, RNA, and Protein
  Nobuyuki Ota — arXiv, 2026-03-24
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• 🧬 Bacterial proteome foundation model enhances functional prediction from enzymes to ecological interactions
  Sethi, P.; Pereira, L. A.; Zhou, J. — bioRxiv, 2026-03-23
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• 🧬 Predicting Unseen Gene Perturbation Response Using Graph Neural Networks with Biological Priors
  Dip, S. A.; Zhang, L. — bioRxiv, 2026-03-26
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• 🧬 Mosaic integration of spatial multi-omics with SpaMosaic
  Yan, X.; Fang, Z.; Ang, K. S.; Olst, L. v.; Edwards, A.; Watson, T.; Zheng, R.; Fan, R.; Li, M.; Gate, D.; Chen, J. — bioRxiv, 2026-03-25
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• 🧬 Physics-Grounded Evaluation to Guide Accurate Biomolecular Prediction
  Lyu, N.; Du, S.; Shao, Q.; Yang, Z.; Ma, J.; Herschlag, D. — bioRxiv, 2026-03-25
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• 🧬 MHCBind: A Pan- and Allele-Specific Model for Predicting Class I MHC-Peptide Binding Affinity
  Peddi, N.; Bijjula, D. R.; Gogte, S.; Kondaparthi, V. — bioRxiv, 2026-03-23
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• 🧬 CombinGym: a benchmark platform for machine learning-assisted design of combinatorial protein variants
  Chen, Y.; Fu, L.; Lu, X.; Li, W.; Gao, Y.; Wang, Y.; Ruan, Z.; Si, T. — bioRxiv, 2026-03-25
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• 🧬 LAMBDA: A Prophage Detection Benchmark for Genomic Language Models
  Lindsey, L. M.; Pershing, N. L.; Dufault-Thompson, K.; Gwak, H.-j.; Habib, A.; Schindler, A.; Rakheja, A.; Round, J.; Stephens, W. Z.; Blaschke, A. J.; Sundar, H.; Jiang, X. — bioRxiv, 2026-03-26
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• 📄 Intern-S1-Pro: Scientific Multimodal Foundation Model at Trillion Scale
  Yicheng Zou, Dongsheng Zhu, Lin Zhu, Tong Zhu, Yunhua Zhou, Peiheng Zhou, Xinyu Zhou, Dongzhan Zhou, Zhiwang Zhou, Yuhao Zhou, Bowen Zhou, Zhanping Zhong, Zhijie Zhong, Haiteng Zhao, Penghao Zhao, Xiaomeng Zhao, Zhiyuan Zhao, Yechen Zhang, Jin Zhang, Wenwei Zhang, Hongjie Zhang, Zhuo Zhang, Wenlong Zhang, Bo Zhang, Chao Zhang, Chen Zhang, Yuhang Zang, Fei Yuan, Jiakang Yuan, Jiashuo Yu, Jinhui Yin, Haochen Ye, Qian Yao, Bowen Yang, Danni Yang, Kaichen Yang, Ziang Yan, Jun Xu, Yicheng Xu, Wanghan Xu, Xuenan Xu, Chao Xu, Ruiliang Xu, Shuhao Xing, Long Xing, Xinchen Xie, Ling-I Wu, Zijian Wu, Zhenyu Wu, Lijun Wu, Yue Wu, Jianyu Wu, Wen Wu, Fan Wu, Xilin Wei, Qi Wei, Bingli Wang, Rui Wang, Ziyi Wang, Zun Wang, Yi Wang, Haomin Wang, Yizhou Wang, Lintao Wang, Yiheng Wang, Longjiang Wang, Bin Wang, Jian Tong, Zhongbo Tian, Huanze Tang, Chen Tang, Shixiang Tang, Yu Sun, Qiushi Sun, Xuerui Su, Qisheng Su, Chenlin Su, Demin Song, Jin Shi, Fukai Shang, Yuchen Ren, Pengli Ren, Xiaoye Qu, Yuan Qu, Jiantao Qiu, Yu Qiao, Runyu Peng, Tianshuo Peng, Jiahui Peng, Qizhi Pei, Zhuoshi Pan, Linke Ouyang, Wenchang Ning, Yichuan Ma, Zerun Ma, Ningsheng Ma, Runyuan Ma, Chengqi Lyu, Haijun Lv, Han Lv, Lindong Lu, Kuikun Liu, Jiangning Liu, Yuhong Liu, Kai Liu, Hongwei Liu, Zhoumianze Liu, Mengjie Liu, Ziyu Liu, Wenran Liu, Yang Liu, Liwei Liu, Kaiwen Liu, Junyao Lin, Junming Lin, Tianyang Lin, Dahua Lin, Jianze Liang, Linyang Li, Peiji Li, Zonglin Li, Zehao Li, Pengze Li, Guoyan Li, Lingkai Kong, Linglin Jing, Zhenjiang Jin, Feifei Jiang, Qian Jiang, Junhao Huang, Zixian Huang, Haian Huang, Zhouqi Hua, Han Hu, Linfeng Hou, Yinan He, Conghui He, Tianyao He, Xu Guo, Qipeng Guo, Aijia Guo, Yuzhe Gu, Lixin Gu, Jingyang Gong, Qiming Ge, Jiaye Ge, Songyang Gao, Jianfei Gao, Xinyu Fang, Caihua fan, Yue Fan, Yanhui Duan, Zichen Ding, Shengyuan Ding, Xuanlang Dai, Erfei Cui, Ganqu Cui, Pei Chu, Tao Chu, Guangran Cheng, Yu Cheng, Kai Chen, Yongkang Chen, Chiyu Chen, Guanzhou Chen, Qiaosheng Chen, Sitao Chen, Xin Chen, Haojiong Chen, Yicheng Chen, Weihan Cao, Yuhang Cao, Qinglong Cao, Lei Bai — arXiv, 2026-03-26
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• 🧬 AI-Enforced Ultra-Large Virtual Screening Discovers Potent CD28 Binders
  Upadhyay, S.; Roggia, M.; Yuan, S.; Cosconati, S.; Gabr, M. — bioRxiv, 2026-03-29
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• 🧬 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, 2026-03-24
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• 🧬 Generative Deep Learning and Molecular Dynamics Reveal Design Principles for Amyloid-Like Antimicrobial Peptides
  Prasad, A. K.; Awatade, V.; Patel, M. K.; Plisson, F.; Martin, L.; Panwar, A. S. — bioRxiv, 2026-03-23
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