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Generative AI Transforms Bioinformatics: A Systematic Review

By PulseAugur Editorial · [1 sources] ·

A systematic review published on arXiv examines the impact of generative artificial intelligence (GenAI) on bioinformatics, covering models, applications, and methodological advancements. The review found that GenAI significantly enhances areas like genomics, proteomics, and drug discovery, often surpassing traditional methods due to improved pattern recognition and data generation capabilities. While specialized GenAI architectures show superior performance in domain-specific tasks, limitations such as poor scalability, data bias, and restricted generalizability persist, necessitating stronger evaluation and biologically grounded modeling approaches. AI

IMPACT This review highlights how GenAI is advancing biological research and drug discovery, potentially accelerating new therapeutic developments.

RANK_REASON The item is a systematic review paper published on arXiv detailing methodological advances in a specific field. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Generative AI Transforms Bioinformatics: A Systematic Review

COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Wasimul Karim, Riasad Alvi, Sayeem Been Zaman, Arefin Ittesafun Abian, Mohaimenul Azam Khan Raiaan, Saddam Mukta, Md Rafi Ur Rashid, Md Rafiqul Islam, Yakub Sebastian, Sami Azam ·

    Generative Artificial Intelligence in Bioinformatics: A Systematic Review of Models, Applications, and Methodological Advances

    arXiv:2511.03354v2 Announce Type: replace-cross Abstract: Generative artificial intelligence (GenAI) is transforming bioinformatics by advancing genomics, proteomics, transcriptomics, structural biology, and drug discovery. Following the Preferred Reporting Items for Systematic R…

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