Proteomic Approach of Medicinal Plant and Its Informatics Use in Health Science

Authors

  • Soumya Khare Department of Biotechnology, Kalyan PG College, Bhilai Nagar, Chhattisgarh
  • Tanushree Chatterjee Department of Biotechnology, Raipur Institute of Technology, Raipur Chhattisgarh
  • Amiy Dutt Chaturvedi Plant Ecology and Environmental Science Divisions CSIR- National Botanical Research Institute, Lucknow, Uttar Pradesh

DOI:

https://doi.org/10.30732/ijbbb.20170202002

Keywords:

KEGG (Kyoto Encyclopedia of Genes and Genomes), USDA (United States Department of Agriculture), TCM- ID (Traditional Chinese Medicine Information Data).

Abstract

Medical informatics has recently been a part of bioinformatics, the clinical proteomic plays an important role in the analysis of genetic. Proteomic is set to play a major role in defining biological systems at a molecular level. Medicinal plants are used as a raw material for some important drugs and antibiotics brought about a revolution in controlling different disease. The potential of higher plants as source for new drugs is still largely unexplored. Proteomic provides essential mechanisms to analyze information generated from using databases techniques. In particular, these approaches have made possible for the identification of genes and pathways involved in synthesis of bioactive metabolites in medicinal plants. Here we look at large scale proteomic in the post genomic era and reflect on its future impact to study biological systems in health science and medical research. Its main aim is to convert raw gene sequences data and measurement of gene expression, to informations describing the actions of those proteins controlling biological systems. This paper reviews on the bioinformatics have deal with to medicinal plants research and highlight a crucial role in working towards health science.

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Published

2017-09-14

How to Cite

Khare, S., Chatterjee, T., & Chaturvedi, A. D. (2017). Proteomic Approach of Medicinal Plant and Its Informatics Use in Health Science. CSVTU International Journal of Biotechnology, Bioinformatics and Biomedical, 2(2), 20–24. https://doi.org/10.30732/ijbbb.20170202002

Issue

Vol. 2 No. 2 (2017): Peer Review

Section

Review Article

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