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

Hierarchical Breakdown of RNA Structure Prediction in CASP16: From Reliable Local Features to Speculative Multimer Assembly

This paper presents a CASP16 case study by LCBio demonstrating that while expert-guided workflows can achieve competitive rankings in RNA multimer prediction, current methods exhibit a hierarchical decline in accuracy where reliable local features fail to translate into precise global architectures due to persistent challenges in modeling multi-helix junctions and non-canonical interactions.

Nithin, C., Pilla, S. P., Kmiecik, S.2026-04-30

💻 bioinformatics

linearPOA: A parallel, memory-efficient framework for Partial Order Alignment with linear space complexity

This paper introduces linearPOA, a parallel and memory-efficient framework that utilizes a divide-and-conquer strategy to achieve linear space complexity for Partial Order Alignment, significantly reducing memory consumption compared to existing quadratic algorithms when handling ultra-long, error-prone sequencing reads.

Wei, Y., Huang, Z., Zhang, P., Tian, Q., Li, Y., Zou, Q., Yu, L.2026-04-30

💻 bioinformatics

Species-specific transformer models of bacterial gene order and content for genomic surveillance tasks

This study introduces PanBART, a species-specific transformer model trained on the gene content and order of *Escherichia coli* and *Streptococcus pneumoniae*, demonstrating its superior ability to unsupervisedly learn population structures, identify emergent lineages, predict antibiotic resistance gene uptake, and analyze gene co-selection for critical genomic surveillance tasks.

Horsfield, S. T., Wiatrak, M., McInerney, J. O., Bentley, S. D., Colijn, C., Lees, J. A.2026-04-30

💻 bioinformatics

A Conditional Variational Autoencoder with QSAR-Guided Surrogate-Weighted Fine-Tuning and Cross-Entropy Optimization for Targeted Antimicrobial Peptide Generation

This paper presents a conditional variational autoencoder pipeline that integrates QSAR-guided surrogate-weighted fine-tuning and cross-entropy optimization to overcome data scarcity and circular dependency challenges, successfully generating targeted antimicrobial peptides with high predicted efficacy and favorable structural properties.

Castanon, I., Wan, F., de la Fuente, C., Pini, A., Falciani, C.2026-04-30

💻 bioinformatics

Systems Pharmacology Reveals Type I Interferon and Myeloid-Like B Cell Reprogramming as Druggable Axes in Antiphospholipid Syndrome

This study employs an integrative systems pharmacology approach to characterize the molecular heterogeneity of antiphospholipid syndrome, identifying Type I interferon signaling and myeloid-like B cell reprogramming as key druggable axes that enable patient stratification and the repurposing of existing therapies for precision medicine.

Sun, B., Lu, Y., Liu, W., Wang, C.2026-04-30

💻 bioinformatics

Deterministic retrieval recovers biomedical associations lost by language models

The paper introduces BioChirp, an open-source framework that combines LLM-based query interpretation with deterministic graph-based retrieval to recover more biomedical associations with higher reproducibility than conventional LLM-based systems.

Halder, A., Singh, M., Kesarwani, R., Mathew, B., Bhattacharya, N., Chikhaliya, O., Motwani, D., Peela, S. C. M., Samant (…)2026-04-29

💻 bioinformatics

Explainable Prototype Booster: Enhancing Latent Representations of Foundation Models for Gene Expression Prediction

The paper introduces the Explainable Prototype Booster (EP-Booster), a method that integrates biological prior knowledge into foundation models to refine latent representations for accurate and interpretable gene expression prediction from histological images, thereby overcoming the cost and time limitations of spatial transcriptomics.

Li, C., Nguyen, Q.2026-04-29

💻 bioinformatics

PixelDeck: A local-first media library manager for biomedical imaging

PixelDeck is an open-source, local-first browser application that streamlines the organization, deduplication, and interactive browsing of large biomedical image and video collections on standard hardware through a modular architecture featuring recursive import, SHA-256 duplicate detection, and asynchronous processing.

Kidder, B. L.2026-04-28

💻 bioinformatics

Accurate ab initio gene prediction in eukaryotes with Tiberius in multiple clades

The paper introduces Tiberius, a deep learning-based ab initio gene predictor that achieves state-of-the-art accuracy and significantly faster runtimes across diverse eukaryotic clades by training lineage-specific models, effectively addressing current bottlenecks in genome annotation.

Gabriel, L., Bruna, T., Kaur, A., Krishnan, A., Ortmann, F., Salamov, A., Talbot, S., Becker, F., Krieg, R., Wheat, C. W (…)2026-04-28

💻 bioinformatics

Uniform pre-processing of bacterial single-cell RNA-seq

This paper adapts the kallisto-bustools suite to enable efficient, accurate, and uniform pre-processing of bacterial single-cell RNA-seq data, addressing challenges posed by operons and short gene lengths to establish a scalable foundation for microbial transcriptomics.

Oakes, C. G., Beilinson, V., McFall-Ngai, M. J., Pachter, L. G.2026-04-27

← Previous Next →