Weekly BioML Digest [April 06, 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)

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

• AlphaFold as a prior: experimental structure determination conditioned on a pretrained neural network
  Fadini, Alisia, Li, Minhuan, McCoy, Airlie J., Banjara, Suresh, Okumura, Hiroki, Napier, Eve, Fontana, Pietro, Khan, Amir R., Jovine, Luca, Terwilliger, Thomas C., Read, Randy J., Hekstra, Doeke R., AlQuraishi, Mohammed — Nature Methods, 2026-04-01
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• Accurate predictions of disordered protein ensembles with STARLING
  Novak, Borna, Lotthammer, Jeffrey M., Emenecker, Ryan J., Holehouse, Alex S. — Nature, 2026-04-02
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• Two-dimensional geometric template diffusion for boosting single-sequence protein structure prediction
  Wang, Xudong, Zhang, Tong, Cui, Zhen, Guo, Xu, Wang, Fuyun, Wang, Yuanzhi, Cai, Xing, Zheng, Wenming — Nature Machine Intelligence, 2026-04-01
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• Disentangled autoencoding equivariant diffusion model for controlled generation of 3D molecules
  Li, Tianxiao, Liu, Haoran, Guo, Hongyu, Gerstein, Mark, Min, Martin Renqiang — Nature Communications, 2026-04-03
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• Accurate single-domain scaffolding of three nonoverlapping protein epitopes using deep learning
  Castro, Karla M., Watson, Joseph L., Wang, Jue, Southern, Joshua, Ayardulabi, Reyhaneh, Georgeon, Sandrine, Rosset, Stéphane, Baker, David, Correia, Bruno E. — Nature Chemical Biology, 2026-04-01
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• Compressing the collective knowledge of ESM into a single protein language model
  Dinh, Tuan, Jang, Seon-Kyeong, Zaitlen, Noah, Ntranos, Vasilis — Nature Methods, 2026-03-30
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• Scalable homology detection with ERAST
  Jiang, Yinuo, He, Bing, Wu, Zihan, Wang, Fang, Lv, Tianxu, Jia, Yuran, Zhao, Yu, Qin, Chenchen, Chen, Huajun, Zhang, Qiang, Yao, Jianhua — Nature Biotechnology, 2026-04-01
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• NMR-Solver: automated structure elucidation via large-scale spectral matching and physics-guided fragment optimization
  Jin, Yongqi, Wang, Jun-Jie, Xu, Fanjie, Ji, Xiaohong, Gao, Zhifeng, Zhang, Linfeng, Ke, Guolin, Zhu, Rong, E, Weinan — Nature Communications, 2026-04-02
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• CREsted: modeling genomic and synthetic cell-type-specific enhancers across tissues and species
  Kempynck, Niklas, Winter, Seppe, Blaauw, Casper H., Konstantakos, Vasileios, Ekşi, Eren Can, Dieltiens, Sam, Abaffyová, Darina, Bercier, Valérie, Taskiran, Ibrahim I., Hulselmans, Gert, Spanier, Katina, Christiaens, Valerie, Bosch, Ludo, Mahieu, Lukas, Aerts, Stein — Nature Methods, 2026-04-02
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• An end-to-end generalizable deep learning framework to comprehensively analyze transcriptional regulation
  Zhang, Zhaoxi, Fan, Xiaoya, Zhong, Jiaxin, Jia, Lijuan, Han, Yuanyuan, Yang, Chenyi, He, Zengyou, Li, Xiaoyan, Yau, Shing-Tung, Wu, Rongling, Danko, Charles G., Wang, Zhong — Nature Communications, 2026-04-01
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• A deep joint-learning proteomics model for diagnosis of six conditions associated with dementia
  An, Lijun, Pichet Binette, Alexa, Hristovska, Ines, Vilkaite, Gabriele, Xiao, Yu, Zendehdel, Romina, Dong, Zijian, Smets, Bart, Saloner, Rowan, Tasaki, Shinya, Xu, Ying, Krish, Varsha, Imam, Farhad, Janelidze, Shorena, Westen, Danielle, Stomrud, Erik, Whelan, Christopher D., Palmqvist, Sebastian, Ossenkoppele, Rik, Mattsson-Carlgren, Niklas, Hansson, Oskar, Vogel, Jacob W., The Global Neurodegenerative Proteomics Consortium (GNPC) — Nature Medicine, 2026-03-31
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• A Metabolism-Informed Neural Network Identifies Pathways Influencing the Potency and Toxicity of Antimicrobial Combinations
  Arora, Harkirat Singh, Lev, Katherine, Robida, Aaron, Velmurugan, Ramraj, Chandrasekaran, Sriram — npj Drug Discovery, 2026-04-01
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• HistoGWAS: an AI-enabled framework for automated genetic analysis of tissue phenotypes in histology cohorts
  Chaudhary, Shubham, Voigts, Almut, Bereket, Michael, Albert, Matthew L., Schwamborn, Kristina, Zeggini, Eleftheria, Casale, Francesco Paolo — Genome Biology, 2026-03-31
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• Machine learning survival model for personalised prevention of catheter-related thrombosis in tumour patients
  Ge, Hewei, Liu, Qiao, Xie, Junying, Pang, Jianan, Li, Bin, Xue, Jie, Xu, Lina, Yang, Nana, Cai, Haifeng, Wang, Jian, Qi, Yalong, Wei, Yuhan, Mo, Hongnan, Li, Sidan, Zhang, Lili, Liu, Ziming, Wang, Hongyi, Li, Zehao, Chen, Xinqiao, Gao, Xiaoxue, Li, Fangqi, Xing, Weiwei, Sun, Xiaoying, Li, Yufeng, Qian, Haili, Cui, Jiuwei, Ma, Fei — Communications Medicine, 2026-03-30
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• AI-guided multi-omics analysis identifies NPC1-modulated susceptibility to SARS-CoV-2 infection under PM_2.5 exposure
  Feng, Guoqing, Dong, Zheng, Ke, Limei, Zhou, Weilai, Tian, Yu, Li, Xingtian, Xiang, Wenxin, Li, Yanjun, Huang, Qi, Liu, Linfeng, Yin, Bo, Yan, Shouyi, Liu, Jianxiu, Ma, Xindong, Chen, Huaiyong, He, Miao, Hao, Ke, Liu, Sijin, Di, Qian — Nature Communications, 2026-03-30
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• The Extreme Environment Microbiome Catalog (EEMC): a global resource for microbial diversity and antimicrobial discovery
  Jiang, Puzi, Liang, Zhengjiao, Kovacevic, Vladimir, Shi, Jingya, Milicevic, Nikola, Wang, Feng, Liu, Lin, Liu, Yue, Jiang, Yunjiang, Han, Mo, Lin, Xiaonan, Petronić, Časlav, Stanojevic, Nikola, Wang, Lingqin, Wang, Suwan, Cheng, Haixian, Li, Jiani, Chen, Rouxi, Zhang, Yong, Li, Yuxiang, Li, Junhua, Fang, Xiaodong, Yue, Zhen, Xue, Chuang, Yin, Peng, Chen, Haixin — Nature Communications, 2026-04-02
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• Graph-based deep learning approach for high-throughput protein-DNA interaction scoring
  Zhao, Yi-hao, Wang, Ying, Shen, Chao, Jiang, De-jun, Gu, Shu-kai, Zhao, Hui-feng, You, Zi-yi, Hou, Ting-jun, Kang, Yu — Acta Pharmacologica Sinica, 2026-04-01
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• GCNPath: introspecting drug response prediction with pathway-guided graph convolution networks
  Yoon, Hyeon Jun, Lee, Minho — Communications Biology, 2026-04-01
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• Protein buffering of aneuploidy is driven by coordinated factors identified through machine learning
  Heller, Erik Marcel, Barthel, Karen, Räschle, Markus, Schukken, Klaske M, Sheltzer, Jason M, Storchová, Zuzana — Molecular Systems Biology, 2026-04-02
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• AI guided discovery of a murine model of asymptomatic Alzheimer’s disease
  Jati, Suborno, Taheri, Sahar, Kal, Satadeepa, Sinha, Subhash C., Head, Brian P., Mahata, Sushil K., Sahoo, Debashis — Acta Neuropathologica Communications, 2026-04-04
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🧬 Preprints (arXiv + bioRxiv)

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

• 📄 Scaling Atomistic Protein Binder Design with Generative Pretraining and Test-Time Compute
  Kieran Didi, Zuobai Zhang, Guoqing Zhou, Danny Reidenbach, Zhonglin Cao, Sooyoung Cha, Tomas Geffner, Christian Dallago, Jian Tang, Michael M. Bronstein, Martin Steinegger, Emine Kucukbenli, Arash Vahdat, Karsten Kreis — arXiv, 2026-03-30
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• 🧬 Co-designing sequence and structure of functional de novo enzymes with EnzyGen2
  Song, Z.; Liu, H.; Zhao, Y.; Yang, Y.; Li, L. — bioRxiv, 2026-03-31
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• 📄 Latent-Y: A Lab-Validated Autonomous Agent for De Novo Drug Design
  Latent Labs Team, Sebastian M. Schmon, Daniella Pretorius, Simon Mathis, Rebecca Bartke-Croughan, Aishaini Puvanendran, James Vuckovic, Henry Kenlay, Mária Vlachynská, Alex Bridgland, Ivan Grishin, Sven Over, David Li, Bridget Li, Jonathan Crabbé, Agrin Hilmkil, Alexander W. R. Nelson, David Yuan, Annette Obika, Simon A. A. Kohl — arXiv, 2026-03-31
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• 🧬 Enabling the prediction of phage receptor specificity from genome data
  Moriniere, L.; Noonan, A. J. C.; Kazakov, A.; Pena, M.; Svab, M.; Rivera-Lopez, E. O.; Maucourt, F.; Johnson, M. S.; Roux, S.; Koskella, B.; Deutschbauer, A. M.; Dudley, E. G.; Mutalik, V. K.; Arkin, A. P. — bioRxiv, 2026-04-02
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• 🧬 mRNA-GPT: A Generative Model for Full-Length mRNA Design and Optimization
  Li, S.; Chauvin, P.; Gross, O.; Bailey, M.; Jager, S. — bioRxiv, 2026-04-02
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• 🧬 A Generative Neuro-Symbolic AI for Protein Sequence Design
  Defresne, M.; Dessaux, D.; Buchet, S.; Barthe, L.; Ammar-Khodja, L.; Azizi, B.; Durante, V.; Cioci, G.; de Givry, S.; Roussel, A.; Garcia-Alles, L.; Schiex, T.; Barbe, S. — bioRxiv, 2026-04-02
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• 🧬 CardamomOT: a mechanistic optimal transport-based framework for gene regulatory network inference, trajectory reconstruction and generative modeling
  Mauge, Y.; Ventre, E. — bioRxiv, 2026-04-02
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• 🧬 Generative machine learning unlocks the first proteome-wide image of human cells
  Sun, H.; Kahnert, K.; Hansen, J. N.; Leineweber, W. D.; Li, M.; Feng, W.; Ballllosera Navarro, F.; Axelsson, U.; Ouyang, W.; Lundberg, E. — bioRxiv, 2026-04-02
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• 🧬 seq2ribo: Structure-aware integration of machine learning and simulation to predict ribosome location profiles from RNA sequences
  Kaynar, G.; Kingsford, C. — bioRxiv, 2026-04-03
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• 📄 ViraHinter: a dual-modal artificial intelligence framework for predicting virus-host interactions
  Weiqiang Bai, Fei Wang, Jialin Wang, Sheng Xu, Lifeng Qiao, Juan Li, Zhuyi Guo, Xiangyun Hou, Lei Bai, Bowen Zhou, Edward C. Holmes, Weifeng Shi, Siqi Sun — arXiv, 2026-04-03
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• 🧬 SSAlign: Ultrafast and Sensitive Protein Structure Search at Scale
  Wang, L.; Zhang, X.; Wang, Y.; Xue, Z. — bioRxiv, 2026-04-02
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• 🧬 Protein Language Models Outperform BLAST for Evolutionarily Distant Enzymes: A Systematic Benchmark of EC Number Prediction
  Sathyamoorthy, R.; Puri, M. — bioRxiv, 2026-04-01
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• 🧬 Protein sequence domain annotation using a language model
  Sarkar, A.; Krishnan, K.; Eddy, S. R. — bioRxiv, 2026-03-31
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• 🧬 DESPOT: Direction-Enhanced Scoring POTentials
  Poelmans, R.; Bruncsics, B.; Arany, A.; Van Eynde, W.; Shemy, A.; Moreau, Y.; Voet, A. R. — bioRxiv, 2026-04-02
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• 🧬 A structure-informed deep learning framework for modeling TCR-peptide-HLA interactions
  Cao, K.; Li, R.; Strazar, M.; Brown, E. M.; Nguyen, P. N. U.; Pust, M.-M.; Park, J.; Graham, D. B.; Ashenberg, O.; Uhler, C.; Xavier, R. — bioRxiv, 2026-04-02
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• 🧬 When Multimodal Fusion Fails: Contrastive Alignment as a Necessary Stabilizer for TCR--Peptide Binding Prediction
  Qi, C.; Wang, W.; Fang, H.; Wei, Z. — bioRxiv, 2026-04-02
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• 🧬 Baktfold: Sensitive protein functional annotation across the microbial tree of life using structural information
  Bouras, G.; Lim, S. w.; Durr, L.; Vreugde, S.; Goesmann, A.; Edwards, R. A.; Schwengers, O. — bioRxiv, 2026-04-01
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• 🧬 SSPSPredictor: A Sequence and Structure based Deep Learning Model for Predicting Phase-Separating Proteins
  Wang, T.; Liao, S.; Qi, Y.; Zhang, Z. — bioRxiv, 2026-04-01
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• 🧬 emb2dis: a novel protein disorder prediction tool based on ResNets, dilated convolutions & protein language models
  Duarte, S. A.; Mehdiabadi, M.; Bugnon, L. A.; Aspromonte, M. C.; Piovesan, D.; Milone, D. H.; Tosatto, S.; Stegmayer, G. — bioRxiv, 2026-04-01
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• 🧬 Millisecond Prediction of Protein Contact Maps from Amino Acid Sequences
  Lin, R.; Ahnert, S. E. — bioRxiv, 2026-03-31
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