Cargando…
Biotechnology, Bioinformatics and Bioinformation in an Autobiography
Science is observation. Application of Science is engineering. A 0% error is desired in Science, while a 25% error is usually allowed in Engineering. Technology is engineering with Science where the error rate is considerably reduced to improve precision. Biotechnology is truly interdisciplinary wit...
Autor principal: | |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Biomedical Informatics
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10259221/ https://www.ncbi.nlm.nih.gov/pubmed/37313394 http://dx.doi.org/10.6026/97320630016039 |
Sumario: | Science is observation. Application of Science is engineering. A 0% error is desired in Science, while a 25% error is usually allowed in Engineering. Technology is engineering with Science where the error rate is considerably reduced to improve precision. Biotechnology is truly interdisciplinary with an optimal mix of physics, chemistry and biology linked by Mathematics. Chemistry evolved into Chemical Engineering and thus Biochemistry into Biochemical Engineering. Biochemical engineering with genetics and molecular biology created Biotechnology. Biotechnology with computer science developed Bioinformatics. Bioinformatics used biological data to glean BIOINFORMATION for Biological Knowledge Discovery (BKD). This helped to accelerate drug discovery and develop other biologics (biomarkers, vaccines, seed developments, bio-fertilizers and bio-pesticides) towards improved service in healthcare, agriculture, food production, food processing and food distribution across international borders as per demand supply in the supply chain. It is joyful to realize the personal experience with the multifaceted features of Biotechnology, Bioinformatics and Bioinformation in a comprehensive manner over a period of three decades. This educational path is truly exciting, engaging and enterprising. This journey provided an opportunity to debate on cry toxins, lipase, ibuprofen, HLA alleles, antigens, peptide vaccines, protein-protein interactions, genomes and biological knowledge discovery models. |
---|