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

VicMAG, an open-source tool for visualizing circular metagenome-assembled genomes highlighting bacterial virulence and antimicrobial resistance

The authors present VicMAG, an open-source visualization tool designed to comprehensively display circular metagenome-assembled genomes (cMAGs) with annotations for virulence factors, antimicrobial resistance genes, and mobile genetic elements, thereby facilitating holistic surveillance of bacterial pathogen spread in clinical and environmental settings.

Tsuda, Y., Tanizawa, Y., Vu, T. M. H., Nishimura, Y., Shintani, M., Abe, H., Hasebe, F., Kasuga, I., Nagao, M., Suzuki (…)2026-04-01

💻 bioinformatics

Baktfold: Sensitive protein functional annotation across the microbial tree of life using structural information

Baktfold is a new, ultra-sensitive, and taxon-independent command-line tool that leverages protein structure information via Foldseek and ProstT5 to significantly improve the functional annotation of hypothetical proteins across the microbial tree of life compared to existing methods like Bakta and Prokka.

Bouras, G., Lim, S. w., Durr, L., Vreugde, S., Goesmann, A., Edwards, R. A., Schwengers, O.2026-04-01

💻 bioinformatics

Protein sequence domain annotation using a language model

The paper introduces PSALM, a novel protein domain annotation method that integrates a pretrained protein language model (ESM-2) with a structured probabilistic decoder to achieve domain detection sensitivity and specificity comparable to traditional HMMER tools while offering improved coverage at relaxed confidence thresholds.

Sarkar, A., Krishnan, K., Eddy, S. R.2026-03-31

💻 bioinformatics

Co-designing sequence and structure of functional de novo enzymes with EnzyGen2

EnzyGen2 is a 730-million-parameter protein foundation model that enables the rapid, simultaneous co-design of sequence and structure for functional de novo enzymes by leveraging multi-task learning on protein-ligand pairs, achieving superior performance and experimental validation across multiple enzyme families compared to state-of-the-art methods.

Song, Z., Liu, H., Zhao, Y., Yang, Y., Li, L.2026-03-31

💻 bioinformatics

Flipper: An advanced framework for identifyingdifferential RNA binding behavior with eCLIP data

The paper introduces Flipper, a robust framework that adapts the DESeq2 statistical model to overcome limitations in current tools by integrating input controls and hierarchical normalization, thereby enabling more accurate and sensitive identification of differential RNA binding behavior in eCLIP data.

Flanagan, K., Xu, S., Yeo, G. W.2026-03-31

💻 bioinformatics

WayFindR: Investigating Feedback in Biological Pathways

The paper introduces WayFindR, an R package that converts pathway data from WikiPathways and KEGG into graph structures to reveal that negative feedback loops are significantly underrepresented in current biological databases, highlighting the need for improved data curation to better understand regulatory dynamics.

Bombina, P., McGee, R. L., Reed, J., Abrams, Z., Abruzzo, L. V., Coombes, K. R.2026-03-31

💻 bioinformatics

MoCoO: Momentum Contrast ODE-Regularized VAE for Single-Cell Trajectory Inference and Representation Learning

The paper introduces MoCoO, a modular framework combining Variational Autoencoders, Neural ODEs, and Momentum Contrast with Phase-2 Flow Matching refinement, which systematically outperforms existing methods in capturing both discrete cell-type identities and continuous developmental trajectories across 20 scRNA-seq datasets.

Fu, Z.2026-03-31

💻 bioinformatics

Cell type composition drives patient stratification in single-cell RNA-seq cohorts

This study demonstrates that simple, interpretable cell-type composition metrics, particularly centered log-ratio-transformed proportions, outperform complex computational methods for unsupervised patient stratification in single-cell RNA-seq cohorts by capturing clinically relevant variation driven by cellular heterogeneity, and introduces the open-source R package scECODA to facilitate this approach.

Halter, C., Andreatta, M., Carmona, S.2026-03-31

💻 bioinformatics

Protein Language Model Decoys for Target Decoy Competition in Proteomics: Quality Assessment and Benchmarks

This study introduces protein language model-based decoys for proteomics target-decoy competition and benchmarks them against classical methods, finding that while they offer superior sequence-level indistinguishability and diagnostic value, they currently do not outperform traditional reverse decoys in overall search performance.

Reznikov, G., Kusters, F., Mohammadi, M., van den Toorn, H. W. P., Sinitcyn, P.2026-03-31

💻 bioinformatics

Pan-Metabolomics Repository Mapping of the Carnitine Landscape

By applying a pan-repository data mining strategy with MassQL filtering to LC-MS/MS data across major public databases, this study systematically mapped the carnitine landscape to generate a comprehensive library of over 34,000 unique MS/MS spectra representing nearly 3,000 atomic compositions, thereby enabling the discovery of novel carnitine conjugates and advancing the understanding of their roles in host metabolism, diet, and disease.

Mannochio-Russo, H., Ferreira, P. C., Kvitne, K. E., Patan, A., Deleray, V., Agongo, J., Gouda, H., Goncalves Nunes, W. (…)2026-03-31

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