mlsanityData to 14 Oct 2026

Automated Bioinformatics Analysis via AutoBA

arXiv 2309.03242 ↗First posted 6 Sep 2023q-bio.GN cs.AI cs.LGcited by 6

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Abstract (arXiv)

With the fast-growing and evolving omics data, the demand for streamlined and adaptable tools to handle the analysis continues to grow. In response to this need, we introduce Auto Bioinformatics Analysis (AutoBA), an autonomous AI agent based on a large language model designed explicitly for conventional omics data analysis. AutoBA simplifies the analytical process by requiring minimal user input while delivering detailed step-by-step plans for various bioinformatics tasks. Through rigorous validation by expert bioinformaticians, AutoBA's robustness and adaptability are affirmed across a diverse range of omics analysis cases, including whole genome sequencing (WGS), RNA sequencing (RNA-seq), single-cell RNA-seq, ChIP-seq, and spatial transcriptomics. AutoBA's unique capacity to self-design analysis processes based on input data variations further underscores its versatility. Compared with online bioinformatic services, AutoBA deploys the analysis locally, preserving data privacy. Moreover, different from the predefined pipeline, AutoBA has adaptability in sync with emerging bioinformatics tools. Overall, AutoBA represents a convenient tool, offering robustness and adaptability for complex omics data analysis.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 7 of its 86 references that are in the map. First posted on arXiv 6 Sep 2023.

Builds on

7 of 86 references.

References · 7

  1. 2022Emergent Abilities of Large Language Modelscited by 2,512
  2. 2023Towards Generalist Biomedical AIcited by 289
  3. 2023ChatCAD: Interactive Computer-Aided Diagnosis on Medical Image using Large Language Modelscited by 116
  4. 2021MatSciBERT: A Materials Domain Language Model for Text Mining and Information Extractioncited by 83
  5. 2021Keeping it Simple: Language Models can learn Complex Molecular Distributionscited by 68
  6. 2023SkinGPT-4: An Interactive Dermatology Diagnostic System with Visual Large Language Modelcited by 18
  7. 2023Path to Medical AGI: Unify Domain-specific Medical LLMs with the Lowest Costcited by 12

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 3; 2025: 2; 2026: 1.

6 papers.