As biological data expands exponentially, the integration of Bioinformatics, Computational Biology & AI in Biotech is becoming indispensable for meaningful interpretation and application. Bioinformatics tools help manage and analyze genomic, transcriptomic, and proteomic datasets, while computational biology models complex biological systems, simulating metabolic pathways, evolutionary patterns, and disease progression. Artificial intelligence and machine learning are transforming how scientists predict drug responses, design proteins, and classify disease biomarkers. From personalized medicine to synthetic biology design automation, the impact of Bioinformatics, Computational Biology & AI in Biotech is vast and growing. These digital frameworks empower researchers to uncover hidden patterns, optimize bioprocesses, and make data-driven decisions that accelerate discovery, development, and clinical translation in biotechnology.
Title : Renewed novel biotech ideas, with bioreactor bioengineering economic impact
Murray Moo Young, University of Waterloo, Canada
Title : Improving health in over 40,000 patients: The impact of nanomedicine fighting antibiotic resistant infections
Thomas J Webster, Brown University, United States
Title : Osmotic lysis–driven Extracellular Vesicle (EV) engineering
Limongi Tania, University of Turin, Italy
Title : Evaluating cell compatibility and subcutaneous host response of silk fibroin–chitosan plug composites as potential resorbable implants
Luis Jesus Villarreal Gomez, Universidad Autonoma de Baja California, Mexico
Title : Comparative study of endo-?-1,4-mannanases from novel bacterial strains for the production of galactomanno-oligosaccharides
Shruti Saini, National Agri-food and Bio-manufacturing Institute, India
Title : Engineering Sf9 host cells with AcMNPV genes to control baculovirus infection dynamics and heterologous gene expression
Tamer Z Salem, Zewail City of Science and Technology, Egypt