Artificial intelligence (AI) is already widely used in biotechnology to solve a variety of problems. These include, for example, drug discovery, drug safety, functional and structural proteomics/genomics, metabolomics, pharmacology, pharmacogenetics and pharmacogenomics, among many others. Future advances in this domain depend critically on the ability of biotechnology researchers to use advanced AI solutions effectively. The biotechnology industry currently relies heavily on data storage, filtering, analysis and sharing. Biotechnology companies and various healthcare organizations around the world already maintain huge data bases. Drug manufacturing, chemical analysis of various compounds, sequencing of RNA and DNA, enzyme studies, and other similar biological processes all require strong support from AI software solution to move faster and reduce manual errors. It is important to emphasize at the very beginning that all the successful AI we are describing today relies entirely on digital technology to function. Digitalization is therefore the very first step towards any AI application. In many cases, AI systems are integrated with other digital technologies such as sensors, actor
📖 افتح في inklap 🔗 DOI 📮 اطلب بحثاً