Genome sequencing and next-generation sequence data analysis: A comprehensive compilation of bioinformatics tools and databases

Jose C. Jimenez-Lopez, Emma W. Gachomo, Sweta Sharma, Simeon O. Kotchoni

Department of Biochemistry, Cell and Molecular Biology of Plants, Estacion Experimental del Zaidin, High Council for Scientific Research (CSIC), Granada, Spain.
Department of Biology, Rutgers University, Camden, USA.

DOI: 10.4236/ajmb.2013.32016                

Abstract

Genomics has become a ground-breaking field in all areas of the life sciences. The advanced genomics and the development of high-throughput techniques have lately provided insight into whole-genome characterization of a wide range of organisms. In the post-genomic era, new technologies have revealed an outbreak of prerequisite genomic sequences and supporting data to understand genome wide functional regulation of gene expression and metabolic pathways reconstruction. However, the availability of this plethora of genomic data presents a significant challenge for storage, analyses and data management. Analysis of this mega-data requires the development and application of novel bioinformatics tools that must include unified functional annotation, structural search, and comprehensive analysis and identification of new genes in a wide range of species with fully sequenced genomes. In addition, generation of systematically and syntactically unambiguous nomenclature systems for genomic data across species is a crucial task. Such systems are necessary for adequate handling genetic information in the context of comparative functional genomics. In this paper, we provide an overview of major advances in bioinformatics and computational biology in genome sequencing and next-generation sequence data analysis. We focus on their potential applications for efficient collection, storage, and analysis of genetic data/information from a wide range of gene banks. We also discuss the importance of establishing a unified nomenclature system through a functional and structural genomics approach.

Keywords

Databases; Computational Biology; Genomics; Proteomics; Next-Generation Sequencing

Conflicts of Interest

The authors declare no conflicts of interest.

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