Artificial intelligence (AI) is significantly contributing to the field of biological research, catalyzing progress in genomics and drug discovery. Several state-of-the-art AI tools have evolved in this domain.
Google’s deep neural network-based tool, ‘DeepVariant,’ processes genetic variants data from DNA sequencing algorithms. ‘DNAnexus,’ another tool, utilizes cloud technology for genomic data management, accelerating scientific discovery and improving patient care.
‘Rosetta,’ a software suite for protein structure analysis, has marked significant progress in computational biology, while ‘Bionano’s VIA’ integrates data from microarrays, next-gen sequencing, and optical genome mapping, offering significant insights. ‘DRAGEN,’ developed by Illumina, is a comprehensive bioinformatics software suite leveraging AI for data interpretation.
‘PathAI’ has been instrumental in diagnosing cancer, ensuring accurate diagnoses and effective treatments. Similarly, ‘Seven Bridges’ and ‘VarSome’ use AI for genomics exploration, with the latter also focusing on variants interpretations.
‘BenchSci’ is a unique technology to understand the complexity of pre-clinical R&D. ‘Parabricks,’ a freely available software suite, expedites genomics analysis using GPU-based parallel computing.
‘Biocellion’ simulates cellular activities based on AI, and its digital twin, ‘YAcc,’ helps cellular agriculture businesses enhance yield and profitability.
The ‘DeepMetabolism’ system makes phenotype predictions using genome sequencing and employs both supervised and unsupervised learning. ‘Basepair’ uses AI to analyze data from next-gen sequencing. ‘insitro,’ using machine learning and high-throughput biology, is advancing the pharmaceutical industry.
‘Tinybio’ is a genomic generative AI company that increases scientists’ productivity and optimizes resource utilization, while ‘BioBam’ uses AI-powered solutions for functional genomics research, specifically in areas such as agricultural genomics, environmental NGS studies, and microbiology.
‘MedGenome’ uses AI in genomics research and diagnosis, and ‘PetaGene’ leverages AI to manage and reduce genomic data. ‘Genialis’ is an AI-driven platform simplifying genomic data interpretation.
‘Immunai,’ focused on immunology, employs AI for target and treatment development using multi-omic patient data, and ‘BenevolentAI’ builds technology helping researchers understand disease progress, discover new therapeutic targets, and make informed decisions.
This overview demonstrates the potential and diversity of AI use in genomics, drug discovery, and machine learning, suggesting an exciting future for the interplay of AI and biology.
