Latest Computational Biology Research Papers

The newest Computational Biology papers from across the field — arXiv, NeurIPS, CVPR, Nature, and more — refreshed daily and ranked by relevance. Distill AI tracks Computational Biology so you don’t have to: get the standout work delivered to your inbox every morning, with 2-sentence summaries and the option to chat with any paper.

Recent papers

• scDEFT: A deep learning framework for drug-effect prediction and counterfactual reasoning
  Murthy Devarakonda · arXiv · Sep 9, 2026

  Longitudinal single cell atlases now capture matched pre treatment and post treatment states from responders and non responders, presenting an opportunity to mechanistically explain why two patients on the same drug diverge. We introduce sc…

• MechSurv: mechanistic tumour–immune modelling for multimodal cancer survival prediction
  Noaman Khan, Zubair Shah · Scientific Reports · Sep 9, 2026

  Accurate cancer survival prediction remains challenging, partly because most existing deep learning models offer limited mechanistic interpretability of tumour–immune interactions. We developed MechSurv, a multimodal framework integrating W…

• Bayesian inference of gene regulatory networks at stochastic steady state
  Anshi Gupta, Ryeongkyung Yoon, Krešimir Josić · Journal of The Royal Societ... · Sep 9, 2026

  Gene Regulatory Networks (GRNs) form the regulatory backbone that coordinates gene expression. The architecture of GRNs shapes their function and constraints the biochemical pathways through which information flows. Inferring the structure …

• CHIMERA Challenge Task 2 and 3: Response Subtypes Classification and Progression Survival Prediction in Bladder Cancer Patients using Multimodal Datasets
  Catherine Chia, Tongjie Wang, Robert Spaans, Maryam Mohammadlou et al. · arXiv · Sep 8, 2026

  High-risk non-muscle-invasive bladder cancer (HR-NMIBC) carries substantial risks of recurrence and progression, while current clinical risk stratification remains limited. CHIMERA was established as a multimodal AI challenge to benchmark p…

• Mutation E300 recommended by protein language models gives ChrimsonR amplified photocurrent response
  Samuel M. Ehrlich, Alexandra D. Vandeloo, Benjamin Magondu, Athena Chien et al. · Scientific Reports · Sep 8, 2026

  Abstract A central challenge in opsin engineering is identifying mutations that reliably improve desired functional properties, a task made difficult by the enormous mutation space and limited throughput of electrophysiological screening. I…

• Architectural good practices for reproducible benchmarking in protein machine learning
  Julián García-Vinuesa, Diego Fernández-Villegas, Michelle Soto-García, Xavier Cadet et al. · Frontiers in Bioinformatics · Sep 8, 2026

  Reliable benchmarking in protein machine learning requires biological tasks, datasets, representations, execution conditions, and evaluation regimes to be explicitly defined and traceable. Protein-specific dependencies, including label sema…

• Single-cell–informed senescence programs underpin a machine-learning prognostic model robustly validated across melanoma cohorts
  Su Peng, Jiaheng Xie, Xiaohu He · Frontiers in Cell and Devel... · Sep 8, 2026

  Background Cellular senescence (CS) shapes tumor evolution and the tumor microenvironment (TME), yet senescence-informed prognostic models for skin cutaneous melanoma (SKCM) remain limited. We aimed to develop and validate a robust senescen…

• Exploratory spatial transcriptomic analysis of compartment-specific recurrence-associated gene expression in gastric cancer
  Chawisa Nampoolsuksan, Thanawat Suwatthanarak, Kullanist Thanormjit, Pariyada Tanjak et al. · Scientific Reports · Sep 8, 2026

  We hypothesized that the prognostic value of immune and stromal gene expression is spatially dependent—specifically, signals driving homeostasis in the superficial mucosa may differ functionally from those at the deep invasive front. We ana…

• MI-PEFT: Mixture-of-Experts Integrated Parameter-Efficient Fine-Tuning Protein Language Models Improves Acidophilic Proteins Classification
  Honghan Shen · arXiv · Sep 7, 2026

  Acidophilic proteins that remain stable and functional under highly acidic conditions, are important for industrial biocatalysis, acid-related bioprocessing, and the discovery of acid-stable enzymes. However, their identification relies hea…

• Enhancing detection of polygenic adaptation: a comparative study of machine learning and statistical approaches using simulated evolve-and-resequence data
  Cosima Caliendo, Susanne Gerber, Markus Pfenninger · BMC Genomics · Sep 7, 2026

  Abstract Background Detecting signals of polygenic adaptation remains a significant challenge in population genomics, as traditional methods often struggle to identify the associated subtle, multi-locus allele-frequency shifts. Here, we int…

• A Network-Structured Bayesian Hierarchical Model for Sparse Mutation-Drug Response Associations: Application to Cancer Pharmacogenomics
  Hammed A. Olayinka, Saheed O. Olayemi · arXiv · Sep 5, 2026

  We develop a network-structured Bayesian hierarchical model for sparse association mapping between genomic alterations and quantitative treatment-response phenotypes. The framework combines a Gaussian Markov random field prior that borrows …

• Tracing the evolutionary history of Dracocephalum austriacum: Insight from population genomics and species distribution modelling
  Ľuboš Majeský, Lucie Vaculná, Lucie Kobrlová, Costantino Bonomi et al. · Conservation Genetics · Sep 5, 2026
• Simulation-free Unbalanced Dynamic Optimal Transport with General Growth Penalty
  Junda Ying, Yuxuan Wang, Bowen Yang, Peijie Zhou et al. · arXiv · Sep 4, 2026

  Inferring cellular dynamics from unpaired single-cell snapshots requires modeling both state transitions and population growth or death. Unbalanced dynamic optimal transport (UDOT) addresses this by penalizing growth along transport paths, …

• Graph-based representations in modern protein science
  Dana S. Matthews, Sacha B. Pulsford, Anthony Brancewicz, John Z. Chen et al. · Biochemical Journal · Sep 4, 2026

  For more than 50 years, the linear sequence and the multiple sequence alignment have been the foundational data structures of protein science, and they remain central to homology search, phylogenetic inference, covariance-based contact pred…

• Weighted sliced inverse regression for scalable supervised dimensionality reduction of spatial transcriptomics data
  Maximilian Woollard, Pratibha Panwar, Luke Harland, Jeremy Mo et al. · Nature Communications · Sep 3, 2026

  Abstract With the dramatic take-up of spatially resolved transcriptomics biotechnologies, performing spatially-aware analysis of the resulting data is crucial to maximise advances in biological understanding. Dimensionality reduction is a f…

• New thinking for the next generation of antimalarials
  Hannah Asiki, Jason Hlozek, Kathryn J. Wicht, John G. Woodland et al. · EMBO Molecular Medicine · Sep 2, 2026

  Despite decades of intensive research and substantial clinical gains, malaria remains a major global health challenge exacerbated by the continued emergence of drug-resistant strains of the causative agent, Plasmodium parasites. Encouraging…

• Integrative multi-omics and network biology in cardiovascular disease: a systems-level framework for translational discovery
  Vanesa Brecher, Vasiliki Androutsopoulou, Serge Sicouri, Basel Ramlawi et al. · Frontiers in Systems Biology · Sep 2, 2026

  Cardiovascular diseases remain a leading cause of global morbidity and mortality, driven by the complex interplay of genetic, epigenetic, transcriptomic, proteomic, and metabolic networks. Traditional reductionist approaches have inadequate…

• Kinematics-based assessment of reaching and grasping movements in LRN ablated animals identifies a role for the LRN in endpoint stabilization and reach timing
  Gavin T. Koma, Joshua D. Ross, Thomas Campion, Jacquelynn Rajavong et al. · eNeuro · Aug 28, 2026

  The lateral reticular nucleus (LRN) is positioned to relay motor-related information to cerebellar circuits, but its direct contribution to skilled reaching and grasping remains unclear. Here, we examined skilled forelimb behavior in intact…

• Finetuning Foundation Models for Temporal Clinical Transcriptomics Data
  Sachin Mathur, Alexander Kagan, Peyman Passban, Hamid Mattoo et al. · Bioinformatics · Aug 27, 2026

  BACKGROUND: Timeseries clinical transcriptomic datasets offer the opportunity to gain insights into the dynamics of disease mechanisms/treatment responses. However, their utility in uncovering temporal patterns is often limited by high nois…

• Fusion-driven oncogenic programs shape the immune landscape in translocation renal cell carcinoma
  Prathyusha Konda, Alexandra J. Wakolbinger, Y. Cui, Gabriel Roberti De Oliveira et al. · Nature Communications · Aug 26, 2026

  Renal cell carcinomas comprise multiple molecularly distinct cancers but most are treated empirically with therapies designed for clear cell RCC (ccRCC), the most common subtype, due to incomplete understanding of subtype-specific biology. …

• Predicting Protein Aggregation Using Artificial Intelligence
  Mariam Fatima · Zenodo (CERN European Organ... · Aug 26, 2026

  Artificial intelligence is reshaping how researchers predict protein aggregation, a process central to biopharmaceutical stability and neurodegenerative disease. This review synthesizes recent machine learning and deep learning approaches t…

• AI-Driven Multi-Omics Integration for Early Disease Detection: A Comprehensive Survey
  Ahamadi Firdose, Deepthi Raj D, Bhargavi B, Jenita J, Apoorva H G, Dr. Madhu Gopinath · International Journal of Ad... · Aug 22, 2026

  artificial intelligence (AI) is transforming the way we stumble on ailments early, but relying on a single form of facts—which includes genomics on my own—offers most effective a restrained picture of the whole organic complexity. Multi-omi…

• Integrating deep learning and pangenomics to recover missing heritability from wild structural variations
  Yiquan Wang, Minnuo Cai, Yahui Ma, Aurélien Tellier et al. · BMC Genomics · Aug 22, 2026

  Crop domestication has induced a severe genetic bottleneck that reduces the adaptive diversity present in modern cultivars. Standard intra-population genomic prediction models reliant on linear reference genomes and SNPs fail to capture the…

• Characterization of MicroRNA Expression in Neuron-Enriched Extracellular Vesicles During Early Life
  Allison Molen · VCU Scholars Compass (Virgi... · Aug 21, 2026

  Extracellular vesicles (EVs) are membrane-bound sacs released by cells that carry molecular cargo reflective of their cell of origin. EVs enriched using L1 cell adhesion molecule (L1CAM) as a marker of putative neuronal origin can cross the…

• Sex-specific trajectories of nonlinear immune aging at single-cell level
  Harry Park, Nina Le Bert, Antonio Bertoletti, Nicholas S. Tolwinski et al. · Nature Communications · Aug 21, 2026

  Despite the female predominance in age- and immune-associated diseases, the pathways underlying sex differences in healthy immune aging remain incompletely understood. Here, we analyze a multi-ethnic single-cell transcriptome of healthy hum…

• Bayesian model discovery for reverse-engineering biochemical networks from data
  Andreas Christ Sølvsten Jørgensen, Marc Sturrock, Atiyo Ghosh, Vahid Shahrezaei · PLoS ONE · Aug 20, 2026

  Abstract The reverse engineering of gene regulatory networks based on gene expression data is a challenging inference task. A related problem in computational systems biology lies in identifying signalling networks that perform particular f…

• A machine-learning enhanced data fusion pipeline identifies new G-protein-based regulators of Drosophila wing growth and morphogenesis
  Nilay Kumar, Maria Unger, Francisco J. Huizar, Vijay Velagala et al. · npj Systems Biology and App... · Aug 20, 2026

  The development of multicellular organisms relies on a symphony of spatiotemporally coordinated signals that selectively regulate gene expression. In particular, G protein-coupled receptors (GPCRs), the largest superfamily of transmembrane …

• Integrating single-cell transcriptomics with deep learning for glioblastoma treatment
  Marybeth Yonk, Mainak Mustafi, Megan A. Lim, Kimberly B. Hoang et al. · Frontiers in Genetics · Aug 17, 2026

  Glioblastomas are aggressive, heterogeneous tumors that present significant challenges in both diagnosis and treatment. Despite advances in surgical resection, radiotherapy, and chemotherapy with temozolomide (TMZ), the prognosis for gliobl…

• A Computational Framework for Erythropoietin Protein Synthesis and Optimization: Integrating Protein Language Models, AlphaFold3 Structural Prediction, and Bayesian Optimization
  Gaurav Nandagawli · Iconic Research and Enginee... · Aug 15, 2026

  Erythropoietin (EPO) is a 166-residue, four-helix-bundle glycoprotein hormone that regulates erythropoiesis and remains one of the most clinically significant recombinant biopharmaceuticals in use today. Despite four decades of structural a…

• LncPNdeep: A long non-coding RNA classifier based on large language model with peptide and nucleotide embedding
  Zongrui Dai, F. Deng, Hsiao H. Sung · Non-coding RNA Research · Aug 13, 2026

  Abstract Long non-coding RNA plays an important role in various gene transcription and peptide interactions. Classifying lncRNAs from coding RNA is a crucial step in bioinformatics analysis which seriously affects the post-analysis for tran…