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

• pyTransRate: 1 reference-free quality assessment of de novo transcriptome assemblies with current aligners and quantifiers
  Matthew MacManes · arXiv · Oct 27, 2026

  Summary: The original software TransRate scores a de novo transcriptome assembly by mapping the reads it was built from back to it, with no reference required. Its last release (1.0.3) depends on Ruby 2.2 and on aligner and quantifier versi…

• pyTransRate: reference-free quality assessment of de novo transcriptome assemblies with current aligners and quantifiers
  Matthew MacManes · arXiv · Oct 27, 2026

  Summary: The original software TransRate scores a de novo transcriptome assembly by mapping the reads it was built from back to it, with no reference required. Its last release (1.0.3) depends on Ruby 2.2 and on aligner and quantifier versi…

• Advances in Application of ESM3 and Multimodal Generative Protein Language Models in Intelligent Design of Antimicrobial Peptides
  Shang Wang · Theoretical and Natural Sci... · Oct 27, 2026

  Antimicrobial resistance (AMR) has emerged as a significant threat to global public health. Traditional methods for discovering antimicrobial peptides (AMPs) suffer from limitations such as lengthy screening cycles and high costs; however, …

• Escaping cells dilute CRISPR screen responses unequally across cell types
  Xuanrui Huang · arXiv · Oct 26, 2026

  Single-cell CRISPR screens run in many cell types are used to compare how cell types respond to perturbation, to train models that transfer effects between them and to score such models. These uses assume that cells carrying a guide RNA had…

• Benchmarking miRNA Target Prediction Methods
  Congliang Jin, Weibo Niu, Zhexing Wen, Zhaohui S Qin et al. · arXiv · Oct 25, 2026

  Background: MicroRNAs (miRNAs) regulate gene expression by binding to target mRNAs. Although many tools predict miRNA-target interactions, predictions show limited concordance, and benchmarks relying on curated databases may be biased by ov…

• Single-cell transcriptomic insights into conserved and divergent oligodendrocyte lineage programs across species
  Xi Han, Lingyan Zuo, Zhen Zhang, Yuanyi Yu et al. · Communications Biology · Oct 25, 2026

  Oligodendrocyte lineage cells (OLLCs) are essential for myelination and neuronal homeostasis, yet the evolutionary conservation of their transcriptional programs remains unclear. Here, we integrated approximately one million hippocampal sin…

• Multiscale Topology-Regulated Nonlinear Dynamics for Protein B-Factor Prediction and Single-Cell Type Classification
  Zihan Wang, Mushal Zia, Xiaoqi Wei, Li Shen et al. · arXiv · Oct 24, 2026

  Protein B-factor prediction and single-cell type classification are important for characterizing structural variability and cellular heterogeneity, with applications in biological function analysis and drug discovery. However, static geomet…

• Predicting protein electrostatics with protein language models
  Mingzhe Shen, Guy W. Dayhoff, Daniel Kortzak, Jana Shen · Nature Communications · Oct 24, 2026

  Abstract Ionization states are crucial to protein function, yet predicting their equilibrium constants remains challenging. Here we present KaML-ESMs, sequence-based neural networks built on the ESM protein language models and trained on th…

• Shared clones make random cell halves look reproducible in pooled screens
  Xuanrui Huang · arXiv · Oct 23, 2026

  Single-cell perturbation screens are used to train and evaluate models of perturbation effects, and model scores are judged against the reproducibility of the measured effects. Reproducibility is usually judged by splitting each perturbatio…

• Shared clones make random cell halves look reproducible in pooled screens
  Xuanrui Huang · arXiv · Oct 23, 2026

  Single-cell perturbation screens are used to train and evaluate models that predict perturbation effects, and model scores are judged against how reproducible the measured effects are. Reproducibility is usually judged by splitting each per…

• Spatially Informed and Direction Sensitive Representation Learning for Spatial Transcriptomics
  Azim Dehghani Amirabad, Ali Khodabandeh Yalabadi, Artem Moskalev, Yun-Ching Chen et al. · arXiv · Oct 20, 2026

  Cellular states are shaped by both intrinsic gene expression programs and the spatial microenvironment in which cells reside. Spatial transcriptomics makes this context measurable, but effective representation learning requires capturing bo…

• VGL-stGen: Learning a shared multimodal model for lung histology and spatial transcriptomics
  Haenara Shin, Dongjoo Lee, Sungwoo Bae, Kwon Joong Na et al. · arXiv · Oct 20, 2026

  VGL-stGen is a multimodal large language model adapted from a pretrained medical vision-language model using paired lung H&E and spatial transcriptomics with single-cell references. Training integrates image-expression and expression-ce…

• Confounder-robust causal discovery and inference in Perturb-seq using proxy and instrumental variables
  Kwangmoon Park, Hongzhe Li · Journal of the American Sta... · Oct 20, 2026

  Emerging single-cell technologies that combine CRISPR-based genetic perturbations with single-cell RNA sequencing, such as Perturb-seq, offer unprecedented opportunities to uncover cause-and-effect relationships among genes. Nonetheless, Pe…

• Simulation-free approximate Bayesian computation for stochastic reaction networks
  Zekai Li, Mauricio Barahona, Philipp Thomas · arXiv · Oct 19, 2026

  Uncovering stochastic reaction networks from data is central to single-cell biology. Simulation-based inference has evolved into a flexible paradigm for this purpose, circumventing the computational intractability of the likelihood. Notably…

• Decomposing multi-scale dynamic regulation from single-cell multiomics with scMagnify
  Xufeng Chen, Xi Yan, Bihan Shen, Heqi Wang et al. · Nature Communications · Oct 17, 2026

  Deciphering the highly coupled regulatory circuits that drive cellular dynamics remains a fundamental goal in biology. However, capturing the multi-scale time-lagged dynamics and combinatorial regulatory logic of gene regulation remains cha…

• A CRC–MYB chromatin loop controls auxin-mediated nectary growth in Arabidopsis
  Hideaki Iimura, Makoto Takahashi, Ryosuke Ohta, Asumi Nagamori et al. · Nature Communications · Oct 17, 2026

  Abstract Floral nectaries, typically located at stamen bases, secrete sugar-rich nectar containing diverse secondary metabolites. Despite their defined position and specialized function, the mechanisms governing nectary formation remain unc…

• Poisoning the corpora of protein design systems during pre-training and retrieval
  Charalampos Koilakos, Kimon-Antonios Provatas, Michail Patsakis, Candace SY Chan et al. · arXiv · Oct 15, 2026

  Protein foundation models increasingly support the generation of novel biological sequences, yet their reliance on large public datasets creates opportunities for adversarial manipulation of the material they learn from and retrieve. We inv…

• ProtModernBERT: Compute-Efficient Protein Language Modeling
  Alberto Martínez, Natalia Flechas Manrique, Llorenç Espinosa-Portalés, Luc Andrea · arXiv · Oct 14, 2026

  Large protein language models provide a powerful framework for learning sequence-function relationships and guiding experimental design. However, architectural improvements are underexplored, especially in low-compute regimes of relevance f…

• Influencing the exposome, patient macroenvironment, tumor microenvironment through-line to improve clinical outcomes
  Samuel F. Yanuck, Neil E. Alexis · Frontiers in Oncology · Oct 12, 2026

  Previous studies have identified an association between a tumor microenvironment characterized by a predominance of T helper cell type 2 (Th2) system cells (Th2 cells, M2 macrophages, innate lymphoid cells type 2), regulatory T cells, and m…

• PhySeqNet: physics-informed fluorescent foci detection for BARseq spatial transcriptomics
  Neha Goswami, John Hover, Renae Galluccio, Yichen Wu et al. · arXiv · Oct 9, 2026

  BARseq enables spatially resolved gene-expression profiling across intact tissue, but its sensitivity depends on accurate detection and decoding of dense fluorescent rolonies. Existing spot-calling approaches can be conservative where signa…

• sc P rofiterole : Clustering of Single-Cell Proteomic Data Using Graph Contrastive Learning via Spectral Filters
  Mustafa Coşkun, Filipa Blasco Tavares Pereira Lopes, Pınar Kubilay Tolunay, Mark R. Chance et al. · Journal of Computational Bi... · Oct 9, 2026

  Novel technologies for the acquisition of protein expression data at the single cell level are emerging rapidly. Although there exists a substantial body of computational algorithms and tools for the analysis of single cell gene expression …

• A pathway-guided kernel MLP architecture for interpretable cross-disease transfer from rheumatoid arthritis to hematological malignancies
  Lütviye Özge Temur, Ebru Geçici Birkan, Esra İ̇lbahar, Mehmet Gönen et al. · Scientific Reports · Oct 7, 2026

  Gene expression profiling has improved understanding of disease-specific molecular processes; however, the extent to which transcriptomic patterns from chronic inflammatory conditions can be reused across hematological malignancies remains …

• Analysis of immediate upstream gene regions in orthopoxvirus genomes through the use of DNA Duplex Stability and explainable machine learning
  Alex Sánchez Yumbo, Anuj Kumar, André Borges Farias, Ali Toloue Ostadgavahi et al. · Scientific Reports · Oct 7, 2026

  Orthopoxviruses are double-stranded DNA viruses with a temporally regulated gene expression program divided into early, intermediate, and late stages. Although many temporal gene functions are known, the promoter features that distinguish e…

• Linear Fitness Subspace in Protein Language Models Enables Sample-Efficient Directed Evolution
  SiYuan Ma, Canran Xiao, Zikai Xiao, Albert Gao et al. · arXiv · Oct 6, 2026

  Model-guided directed evolution seeks to identify high-fitness protein variants under limited oracle budgets. Protein language models (PLMs) provide rich representations for this task, but task-agnostic zero-shot scores can be misaligned wi…

• Integrated DNA methylation and gene expression analysis identifies CpG biomarkers in breast cancer
  Zeynab Mashayekh, Sadeq Vallian, Mohammad Hossein Sepehri · Scientific Reports · Oct 6, 2026

  DNA methylation alterations are frequently associated with transcriptional dysregulation and tumor-associated molecular changes in breast cancer; however, CpG-specific methylation patterns linked to aberrant gene expression remain incomplet…

• scTIME: single-cell-informed interpretable modeling of immunotherapy-associated immune states in non-small cell lung cancer
  Guozhi Chen, Chenqiu You, Hong Gao, Chengjie Xu · Frontiers in Artificial Int... · Oct 6, 2026

  Immune checkpoint inhibitor response in non-small cell lung cancer (NSCLC) reflects coordinated tumor and immune states that are not fully captured by single biomarkers. We developed scTIME, an interpretable model that translates single-cel…

• Bayesian Gaussian process inference of RNA velocity as a probabilistic vector field on single-cell manifolds
  A. S. M. Bakibillah, Hampei Sasahara, Jun‐ichi Imura · Scientific Reports · Oct 5, 2026

  RNA velocity analysis is widely used to infer cellular state transitions from single-cell transcriptomic data by estimating directional changes in gene expression. However, most existing methods provide deterministic velocity estimates desp…

• GlycoMAC: A Multiscale Metabolic‐Glycosylation Framework for Predicting Glycosylation Across Conditions in Mammalian Cell Cultures
  Yuming Zeng, Sarah W. Harcum, Jinxiang Pei, Wei Xie · Biotechnology and Bioengine... · Oct 5, 2026

  Antibody productivity and glycosylation quality in CHO cell cultures emerge from a dynamically evolving metabolic environment, yet existing models often work in isolation or at a single scale. Here, we present a multiscale mechanistic frame…

• Integrated omics reveals actionable drivers of bioactive variation in US milk
  Cheng-En Tan, Mariana Barboza, Pagkratios Tagkopoulos, Shanghyeon Kim et al. · arXiv · Oct 4, 2026

  Despite milk being a global dietary staple, the molecular basis of its health-relevant bioactivity and the factors governing fine-scale compositional variation remain poorly understood. Here, we present an integrated seven-layer omics chara…

• Analysis of Quantized and Efficiently Adapted Protein Language Models
  Ilan Yaniv Zeisler, Sebastian Clancy, Pouriya Bayat, Saaim Raad et al. · arXiv · Sep 30, 2026

  Background: Protein language models (PLMs) are increasingly used for sequence generation and property prediction, but their size makes fine-tuning and deployment expensive. The effects of quantization and parameter efficient fine-tuning on …