Bioinformatics

Follow this topic Ask about this topic

Latest papers

40 papers5 papers in the last four weeks, up 67% on the four weeks before. 0.0% of all new papers.

Recommending Bacterial Cultivation Conditions from 16S rRNA
Oct 20, 2026Juntang Wang, Hao Wu, Yihan Wang +3Bioinformatics
Harvard University USA · Duke Kunshan University China · Duke University USA +1
REFLEX: RNA Ensemble Generation via Flexibility-Calibrated Stochastic Bridge
Oct 19, 2026Wanli Ma, Tianmeng Hu, Ke LiMolecular Generation Bioinformatics
University of Exeter · Earlham Institute
HyperTaxa: Multiscale Genome Representations for Generalized Microbial Taxonomic Inference
Oct 19, 2026Akash Rao, Sushim Gupta, Vishalini Ramnath +2Bioinformatics Representation Learning
CSSE Department, Auburn University, Auburn, AL, USA · Oklahoma Animal Disease Diagnostic Laboratory, Oklahoma State University, Stillwater, OK, USA
OmicsBench: a long-horizon multi-turn benchmark of AI agents on research-study-scale bioinformatics
Oct 15, 2026Gideon Shaked, Siddharth NagisettyBioinformatics AI Agent Benchmarks
Department of Computational Medicine and Bioinformatics, University of Michigan · AfterQuery
What DNA Foundation Models Learn Beyond Sequence Composition
Oct 11, 2026Vincenzo Yuto Civale, Andrew David Bagdanov, Alberto MagiGenomic Foundation Models Molecular Foundation Models
University of Florence
RAGenome: Scaling Retrieval-Based Genomic Language Models to Long Contexts
Oct 8, 2026Frederikke Isa Marin, Panagiotis Antoniadis, Dionysia Danai Brilli +5Genomics Bioinformatics
University of Copenhagen · Novo Nordisk A/S · Technical University of Denmark
An LLM-in-the-loop RL Framework for Bioinformatics Feature Selection
Oct 4, 2026Xinyuan Wang, Deepti Agrawal, Yanjie FuReinforcement Learning LLM-Guided RL
School of Computing and AI Arizona State University Tempe, USA
When Do Biological Reasoning Models Use Their Biological Inputs?
Oct 1, 2026Ada Fang, Nikitha Thoduguli, Lukas Fesser +3Faithfulness of Language Model Explanations Causal Interventions in Language Models
Harvard University · Massachusetts Institute of Technology
Bioinfoysis Technical Report
Sep 3, 2026Qingyang Shao, Xin Zhang, Zhouyang Yuan +24Multi-Agent LLM Systems LLM Agent Harnesses
DeepAutonomy Team
Expert Knowledge & Machine Understanding: Bridging Reactome's Ontology with LLM Semantic Embeddings
Aug 28, 2026Susanna Bravi, Riccardo De Luca, Rosa Sicilia +2Bioinformatics Biomedical KGs
Istituto per le Applicazioni del Calcolo Mauro Picone, Italian National Research Council, Rome, Italy. · Unit of Artificial Intelligence and Computer Systems, Department of Engineering, Universit`a Campus Bio-Medico di Roma, Rome, Italy · UniCamillus-Saint Camillus International University of Health Sciences, Rome, Italy
BixBench3: Benchmarking AI agents on research-study-scale computational biology tasks
Aug 26, 2026Zane Koch, Asmamaw T. Wassie, Javier Valdes-Aleman +5AI for Science AI Agent Benchmarks
Edison Scientific, Inc., San Francisco, CA, USA
Natural-Language-Guided Generator-Agnostic Shortlisting for Protein Binder Design
Aug 21, 2026Gyubok Lee, Kiwoong Yoo, Jimin Seo +3LLM Reranking Bioinformatics
Kim Jaechul Graduate School of AI, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea · LG AI Research, Seoul, South Korea · Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea +1
Static analysis-guided agentic AI translation enables Rust as a full stack bioinformatics language
Aug 13, 2026Johan HenrikssonCode Translation Bioinformatics
Department of Molecular Biology, Umeå University, Umeå, Sweden · Umeå Centre for Microbial Research (UCMR), Umeå University, Umeå, Sweden · Integrated Science Lab (IceLab), Umeå University, Umeå, Sweden +1
bioMoR: Biology-Guided Mixture-of-Recursions for Effective Genomic Learning
Aug 7, 2026Koushik Howlader, Tirtho Roy, Md Tauhidul Islam +1Recurrent Transformers Genomics
1Iowa State University, Iowa, USA · 2Stanford University, CA, USA
Evolutionary Curriculum Learning Improves Biological Sequence Modeling
Aug 1, 2026Richard Zhu, Kento NishiVariational Autoencoders Curriculum Learning
Department of Computer Science, Harvard University, Cambridge, MA, USA · Department of Statistics, Harvard University, Cambridge, MA, USA.
PlantBGC: Transformer for Plant BGC Discovery via Label-Free Domain Adaptation and Weak Supervision
Jul 29, 2026Yuhan Zhao, Nidhi Grover, Zhishan Guo +1Genomics Bioinformatics
North Carolina State University Department of Computer Science Raleigh, North Carolina, USA · North Carolina State University Department of Molecular and Structural Biochemistry Raleigh, North Carolina, USA
TheBioCollection: Unified Pre-Training Scale LLM Corpus for Biology
Jul 9, 2026Hyunjin Seo, Hyeon Hwang, Gyubok Lee +7Language Model Pretraining Bioinformatics
Trillion Labs · KAIST · SK Biopharmaceuticals Co., Ltd. +2
Prompt-to-Paper: Agentic AI System for Bioinformatics
Jul 5, 2026Ramsha Kamran, Maheera Amjad, Zartasha Mustansar +3Long-Form Document Generation AI-Assisted Scientific Research
School of Interdisciplinary Engineering and Sciences (SINES), National University of Sciences and Technology (NUST), Islamabad, Pakistan · College of Electrical and Mechanical Engineering (CEME), NUST, Rawalpindi, Pakistan
BioMatrix: Towards a Comprehensive Biological Foundation Model Spanning the Modality Matrix of Sequences, Structures, and Language
Jun 20, 2026Qizhi Pei, Zhimeng Zhou, Yi Duan +9Multimodal Understanding Multimodal Pretraining
1Gaoling School of Artificial Intelligence, Renmin University of China, 2OpenDataLab, Shanghai Artificial Intelligence Laboratory · 3Zhejiang University, 4Shanghai Innovation Institute · 2OpenDataLab, Shanghai Artificial Intelligence Laboratory, 3Zhejiang University, 4Shanghai Innovation Institute +5
Process-Reward Tactic Evolution for Long-Horizon Bioinformatics Workflows
Jun 18, 2026Lingzhi Yang, Yubo Fan, Song Wu +1LLM Agent Skill Learning Process Supervision
Stony Brook University · Vanderbilt University · Brookhaven National Lab
MultiMolecule: a modular ecosystem for biomolecular sequence-model workflows
Jun 15, 2026Zhiyuan ChenSequence Modeling Bioinformatics
1*DanLing Team.
$p$ -adic Bi-Filtrations for Topological Machine Learning on Genomic Sequences
Jun 4, 2026Tirtharaj Dash, Gunja SachdevaGenomics Persistent Homology
Department of CS & IS, BITS Pilani, K K Birla Goa Campus, Zuarinagar, Goa 403726, India. · Department of Mathematics, BITS Pilani, K K Birla Goa Campus, Zuarinagar, Goa 403726, India.
TadA-Bench: A Million-Variant Benchmark for Future-Round Discovery Toward Agentic Protein Engineering
May 29, 2026Jin Gao, Juntu Zhao, Zirui Zeng +5Protein Fitness Prediction Benchmark Design
Shanghai Jiao Tong University · Shanghai Innovation Institute.
AMix-2: Establishing Protein as a Native Modality in Large Language Models
May 29, 2026Keyue Qiu, Yixin Wu, Lihao Wang +19Diffusion Language Models Protein Language Models
1Shanghai Artificial Intelligence Laboratory · Institute for AI Industry Research (AIR), Tsinghua University
PROTOCOL: Late Interaction Retrieval for Protein Homolog Search
May 27, 2026Gabrielle Cohn, Rohan Gumaste, Minh Hoang +1Late Interaction Retrieval Protein Language Models
MIT · Princeton University
Better Protein Function Prediction by Modeling Survivorship Bias
May 7, 2026Zhongmou Chao, Poompol Buathong, Ekaterina Selivanovitch +2Protein Function Prediction Weakly Supervised Learning
Smith School of Chemical and Biomolecular Engineering, Cornell University, USA · Center for Applied Mathematics, Cornell University, USA · School of Operations Research and Information Engineering, Cornell University, USA
ProtSent: Protein Sentence Transformers
May 7, 2026Dan Ofer, Oriel Perets, Michal Linial +1Contrastive Learning Protein Language Models
Department of Biological Chemistry The Hebrew University of Jerusalem · Department of Computer and Information Science Ben-Gurion University of the Negev
OmicsLM: A Multimodal Large Language Model for Multi-Sample Omics Reasoning
May 7, 2026Maciej Sypetkowski, Joanna Krawczyk, Łukasz Smoliński +4Multimodal Large Language Models Question Answering
Ingenix.AI, Warsaw, Poland
BioMiner: A Multi-modal System for Automated Mining of Protein-Ligand Bioactivity Data from Literature
Apr 23, 2026Jiaxian Yan, Jintao Zhu, Yuhang Yang +8Document Information Extraction Multimodal Large Language Models
State Key Laboratory of Cognitive Intelligence, University of Science and Technology of China · Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University · Princeton University +2
Biomedical systems biology workflow orchestration and execution with PoSyMed
Apr 21, 2026Simon Süwer, Zoe Chervontseva, Kester Bagemihl +3Scientific Reproducibility Scientific Workflow Automation
Institute for Computational Systems Biomedicine, University of Hamburg, Hamburg, Germany · Department for Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark · Faculty of Science, Computer Science, Vrije Universiteit Amsterdam, Amsterdam, Netherlands

Oct 20, 2026J/K move · Enter open · S save

Recommending Bacterial Cultivation Conditions from 16S rRNA

Juntang Wang, Hao Wu, Yihan Wang, Runkun Guo+2

Harvard University USA · Duke Kunshan University China · Duke University USA+1

Bioinformatics

Open paper AskPDF arXiv

Recommending bacterial cultivation conditions from sequence data is a challenging structured problem characterized by missing standardized benchmarks and limited use of sequence structure. To address this, we introduce DSNI, a benchmark of 65,023 bacterial strains with phylogeny-aware splits, pairing 16S rRNA sequences with four cultivation conditions (media, temperature, pH, oxygen). Exploiting the mosaic structure of 16S rRNA, where hypervariable regions support discrimination and conserved regions support primer design, we propose a Variability-Gated Encoder that learns position-dependent importance weights conditioned on biological features (region type, position, and local complexity). The gating module adds minimal overhead (1,280 parameters, <1%) while providing an explicit inductive bias valuable in low-data regimes. Experiments demonstrate that the learnable gate improves flat Transformers by 4.7% in joint accuracy and complements RNABERT, yielding 44.2% exact-match joint accuracy. The model also recovers 90.2% of ground-truth cultivation protocols within its top-25 recommendations, narrowing the exhaustive search space by approximately 60 times.