Computational and functional annotation at genomic scale

Abstract Genomics provides molecular support for the research and discoveries of new diagnostic methods and treatment of diseases. The development of technologies involved in genome analysis revolutionized the field of genomics. The methods for identification, storage, and analysis of genes become easier with newer technologies. Computational approaches allow researchers to identify, measure, and annotate genomic data. This chapter provides a comprehensive view of various techniques involved in the analysis of genomes by computational means and remolds our understanding of biodiversity, cellular functions, and evolution. It covers most of the basic platforms of sequencing from past to current generations resulting in short or long DNA reads and techniques for grouping together high-throughput data obtained from advanced sequencing techniques. Subsequently, we discuss the different computational approaches involved in genome annotation, mapping, algorithms, and software involved in data mining, and gene ontologies for functional analysis of gene expression are demonstrated. These approaches provide the relevant representation and integration of data obtained from sequencing and gene expression techniques. Automated computational techniques are beneficial to verify and justify the experimental outcomes. Besides the benefits, major shortcomings of these approaches in classification and annotation of datasets are discussed for inferring gene functions. New technologies provide clinicians a reference and guide to recognize pathogenic variants in disease diagnostics. Advancement in technologies abruptly increases the quantity of genomic data, sometimes giving misleading results. Therefore high accuracy should be a potential feature of all the computational genome analyses. Consequently, there is still scope for improvement in the technologies to enhance genome annotation and analysis methods by reclassification and reanalysis of data for the welfare of biomedical research.