• Saritha Kommidi

Artificial intelligence (AI) and machine learning (ML) are rapidly transforming biological sciences by enabling efficient analysis of large, complex, and high-dimensional biological datasets. Recent advances in AI have revolutionized genomics, bioinformatics, systems biology, plant phenotyping, disease detection, and environmental monitoring. AI-driven tools support genome assembly, variant calling, protein structure prediction, multi-omics integration, and precision agriculture, while large language models facilitate literature mining, experimental planning, and scientific communication. Despite these advances, challenges related to data quality, interpretability, computational accessibility, and ethical governance remain significant. This article provides a comprehensive overview of AI tools used in biological sciences, highlights recent developments, discusses limitations and ethical concerns, and outlines future directions toward interpretable, equitable, and sustainable AI-enabled biological research.

Artificial Intelligence, Plant Phenotyping, Plant Disease Detection, Precision Agriculture, Systems Biology, Environmental Monitoring

"AI Tools Usage in Biological Sciences", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.13, Issue 2, page no.51-53, February-2026, Available :http://www.jetir.org/papers/JETIRHJ06013.pdf

"AI Tools Usage in Biological Sciences", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.13, Issue 2, page no. pp51-53, February-2026, Available at : http://www.jetir.org/papers/JETIRHJ06013.pdf