bioinformatics papers | Gist.Science

Bioinformatics sits at the exciting intersection where biology meets data science, using powerful computer tools to decode the vast complexity of living systems. From mapping the human genome to tracking how viruses evolve, this field transforms raw biological information into actionable insights that drive modern medicine and research forward without requiring a supercomputer to understand the basics.

On Gist.Science, we ensure you never miss a breakthrough by processing every new preprint in this category directly from bioRxiv. Our team provides both plain-language explanations and detailed technical summaries for each paper, making cutting-edge discoveries accessible to everyone regardless of their background.

Below are the latest bioinformatics papers added from bioRxiv, ready for you to explore with clarity and depth.

💻 bioinformatics

Probabilistic coupling of cellular and microenvironmental heterogeneity by masked self-supervised learning

The paper introduces Mievformer, a Transformer-based masked self-supervised learning framework that effectively couples cellular and microenvironmental heterogeneity in spatial omics data by learning probabilistic representations of cell states conditioned on their spatial context, thereby outperforming existing methods in niche clustering and enabling the discovery of biologically significant cell subpopulations and gene-expression signatures.

Kojima, Y., Tanaka, Y., Hirose, H., Chiwaki, F., Nishimura, K., Hayashi, S., Itahashi, K., Ishikawa, M., Shimamura, T. (…)2026-04-24

💻 bioinformatics

Genomic dialects: How amino acid properties and the second codon base shape the informational accents of life

This study proposes a "genomic dialects" framework demonstrating that species-specific codon usage bias patterns, which reflect translational fidelity and protein stability constraints rather than true phylogeny, are significantly shaped by amino acid physicochemical properties and the second codon base classification.

Martinez, O., Ochoa-Alejo, N.2026-04-24

💻 bioinformatics

Efficient and scalable modelling of cotranscriptional RNA folding with deterministic and iterative RNA structure sampling

This paper introduces "iterative sampling," a deterministic and scalable framework implemented in the memerna tool that exhaustively enumerates RNA secondary structures in increasing order of free energy, thereby overcoming the limitations of stochastic methods to enable efficient modeling of cotranscriptional folding and the identification of kinetic traps.

Courtney, E., Choi, E., Ward, M., Lucks, J. B.2026-04-24

💻 bioinformatics

SpaceBender: Denoising Spatial Transcriptomics Data to Enhance Biological Signals

SpaceBender is a novel, open-source denoising method for spatial transcriptomics that leverages spatial-specific information to remove RNA diffusion noise, thereby outperforming existing tools and revealing enhanced biological insights across various data resolutions.

Chen, D. G., Ribas, A., Campbell, K. M.2026-04-23

💻 bioinformatics

Tensor-Derived Similarity Networks for Characterising Spatial Patterns in Colorectal Cancer

This study proposes a tensor-derived similarity network framework that decomposes colorectal cancer spatial transcriptomics data to reveal how tissue architecture constrains molecular connectivity, offering a quantitative approach to characterizing spatial heterogeneity and discovering biomarkers.

Pham, T. D.2026-04-23

💻 bioinformatics

Network-based integration of cross-dataset proteomic profiles using fold-change directionality

This study presents a network-based framework that integrates heterogeneous proteomic datasets by analyzing the concordance of differential protein fold-change directions, successfully identifying biologically meaningful clusters such as breast cancer profiles associated with tumor stage and lipid-related pathways.

Nishizaki, M., Araki, N., Kawano, S.2026-04-22

💻 bioinformatics

BioEngine: scalable execution and adaptation of bioimage AI through agent-readable interfaces

BioEngine is a scalable execution and adaptation layer that bridges curated bioimage AI models with diverse hardware, enabling scientists to run, fine-tune, and deploy complex analysis workflows through natural language interactions with an AI agent.

Mechtel, N., Källander, H. D., Cheng, S., Zhang, H., AI4Life Horizon Europe Program Consortium,, Ouyang, W.2026-04-22

💻 bioinformatics

Agent-Guided Ranking Policy Improvement for Peptide Drug Candidate Prioritization

This paper demonstrates that an automated agent-guided policy search outperforms traditional weighted-sum, NSGA-II, and random-weight approaches in prioritizing peptide drug candidates, capturing 65% of the best options in its top-20 shortlist across a public antimicrobial benchmark.

Wijaya, E.2026-04-22

💻 bioinformatics

Human-supervised Agentic AI for Hypothesis Generation and Experimental Assistance in Drug Repurposing

The paper introduces RepurAgent, a human-supervised hierarchical multi-agent AI system that successfully automates and supports the entire drug repurposing lifecycle—from hypothesis generation and experimental design to data analysis and candidate refinement—across diverse disease scenarios including Acute Myeloid Leukemia, COVID-19, and Multiple Sulfatase Deficiency.

Huynh, D.-L., Asp, E., Ballante, F., Puigvert, J. C., DeGrave, A., Karki, R., Nader, K., Östling, P., Pokharel, B., Rie (…)2026-04-22

💻 bioinformatics

Protein inverse folding through joint modeling of surface and backbone geometry

The paper introduces Surleton, a novel inverse protein folding framework that jointly models backbone geometry and protein surface organization to overcome the limitations of backbone-only representations, thereby significantly improving sequence recovery and modeling balance for both buried and exposed residues.

hong, y., cai, y., jiao, y., qi, m., Huang, Q., Sun, L.2026-04-22

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