What are the most important skills every aspiring biotechnologist should learn?
Better understanding of instrumentation (HPLC , GC, MS, IR etc) and no doubt In-silica analysis knowledge are the most important skills every aspiring biotechnologist should learn .
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Abhishek
The HPLC-photometric and/or HPLC-fluorimetric method with gradient system (two-pump system; with high recovery system) is an unique method, which surely gives the quantitative and reliable results (please see files; Lysozyme by RP-HPLC, HPLC-Surf-SEC protein determination method, and J Chrom B Rat BIN LIP Km). Other methods such as MS, PCR, Electron Microscopy, NMR, ESR, X-ray Crystalography, Western Blotting, Direct use of Spectrophotometer and Fluorimeter without purification, low recovery GC, ELISA, RIA, Flow Cytometry, MRI, and IR are not quantitative methods.
Further, our new proteomics PDMD (protein-direct-microsequencing-deciphering) method (with quantitative protein-direct-binding Edman Degradation and with quantitative RP-HPLC-photometric-PTH-amino acid analyzer) is also a quantitative method, which is surely required for the future biotechnology (please see file; HepG2 fucoidan).
Learning basic bioinformatics principles is absolutely essential for future biotechnological research.
The developments in next generation sequencing technology is changing the way the high throughput genomic research is done. In the pre-NGS era, researchers used to spend close to 90 % of the time in generating data and spend about 10 % of their time in analyzing and interpreting the data using computational tools. In the NGS era, due to the cost reduction and simplicity, huge data is generated every day on each organism / trait and are made available for free, thanks to the insistence of Scientific Journals. So, in future, a researcher starting a research in any organism or trait actually starts with voluminous raw genomic data available for free that can be analyzed using bioinformatics tools and predictions can be made before starting lab work to confirm the prediction. In addition to starting with the huge data already available, researchers can generate huge genomic data in very short time i.e. within months. Moreover, this data generation has moved out of the researcher’s lab to industry to whom raw data generation is out sourced. Hence, the role of researcher will be restricted to planning the work by doing analysis of already available data, outsourcing additional data generation and substantial time will be spent on analyzing the generated data and interpreting them.
Better understanding of instrumentation (HPLC , GC, MS, IR etc) and no doubt In-silica analysis knowledge are the most important skills every aspiring biotechnologist should learn .
Regards
Abhishek
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