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 : Improving health in over 40,000 patients: The impact of nanomedicine fighting antibiotic resistant infections
Thomas J Webster, Brown University, United States
Title : Advancement in dual lateral flow immunoassay design for sensitive, rapid detection of rotavirus and adenovirus in stool samples
Ayan Ahmed Isse, Genexus Biotech Company, Somalia
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Luis Jesus Villarreal Gomez, Universidad Autonoma de Baja California, Mexico
Title : Renewed novel biotech ideas, with bioreactor bioengineering economic impact
Murray Moo Young, University of Waterloo, Canada
Title : Osmotic lysis–driven Extracellular Vesicle (EV) engineering
Limongi Tania, University of Turin, Italy
Title : Diversity analyses of microbial communities in Armanis gold-polymetallic mine and acid mine drainage: Bioremediation
Anna Khachatryan, SPC Armbiotechnology of NAS of Armenia, Armenia