Abstract
Objective: Computational infrastructure of medical biotechnology provides insight into elements of genomics, proteomics for understanding diseases and biological systems in a more comprehensive and systematic way. The present study exclusively focuses on role of computational and bioinformatics tools employed in troubleshooting heterogeneous data of biology origin. Method and Analysis: Methodology adopted for study included analysis of online literature through Google Scholar, Pub-med, and Science Direct by searching with comprehensive input like computational tools, biotechnology, proteomics, genomics, drug design and discovery, metagenomics to include all relevant research/review articles within period from 1980 to 2016. Collection, inclusion and exclusion of published articles, review and reports were critically assessed and discussed within line of available databases. Furthermore, bibliography of relevant research articles was taken into consideration. Findings: Major conventional biological databases i.e., National Centre for Biotechnology Information (NCBI) and its subset PubMed, not only provide and exchange biological sequence information but also allow comprehensive analysis for sequence alignment and comparisons to find out disease biomarkers like Single Nucleotide Polymorphisms (SNPs). Likewise, other computational tools and servers are developed to be specific for organism, disease, biological pathway, microbial resistance and drug design. Use of currently available computational techniques provides rapid cross-reference search with higher accession of the sequences with statistical approach. However, a significant challenge in this field is to organize and provide user access, readability and skill sets to heterogeneous data repositories like databases and web servers as well as to keep data privacy. These temporal processes significantly enhanced the vision and understanding about cryptic biological processes. Novelty/Improvement: Present study exclusively targets computational tools employed in deciphering complex biological systems through use of algorithms and software which made available large data repositories in public domain. Current study will enhance and compile amalgam of computational and bioinformatics pipelines engaged in vast perspectives of basic and applied biology.
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