Eras of bioinformatics technologies from command-line interfaces to artificial intelligence (AI) chatbots.

Area of Science:

• Biomedical Informatics
• Computational Biology
• Life Sciences

Background:

• Bioinformatics transformed from specialized tools to a central role in life sciences over 75 years.
• Technological eras, including genomics and next-generation sequencing, spurred computational advances and data analysis challenges.

Purpose of the Study:

• To trace the historical evolution of bioinformatics through distinct technological eras.
• To contextualize the rise of artificial intelligence (AI) within bioinformatics history.
• To provide a roadmap for navigating challenges in the AI-driven era of bioinformatics.

Main Methods:

• Historical review of bioinformatics development.
• Analysis of technological shifts driven by data growth and computational progress.
• Examination of challenges and patterns across different bioinformatics eras.

Main Results:

• Bioinformatics evolved through genomic, next-generation sequencing, and AI eras.
• Scalability, accessibility, and reproducibility challenges were addressed by web servers, cloud platforms, and containerized workflows.
• The AI era, featuring deep learning and large language models, is reshaping structural biology and data integration.

Conclusions:

• Each technological era in bioinformatics lowers entry barriers but raises questions about transparency, trust, and rigor.
• AI's integration into bioinformatics necessitates critical evaluation of its cultural, ethical, and technical implications.
• A historical perspective is crucial for guiding the future of bioinformatics research and application.