Urmila Kulkarni-Kale

By Pandurang Kolekar, Mohan Kale and Urmila Kulkarni-Kale

Part of the book: Computational Biology and Applied Bioinformatics

By Sunitha M. Kasibhatla, Vaishali P. Waman, Mohan M. Kale and Urmila Kulkarni-Kale

Viruses are the most abundant and the smallest organisms, which are relatively simple to sequence. Genome sequence data of viruses for individual species to populations outnumber that of other species. Although this offers an opportunity to study viral diversity at varying levels of taxonomic hierarchy, it also poses challenges for systematic and structured organization of data and its downstream processing. Extensive computational analyses using a number of algorithms and programs have opened exciting opportunities for virus discovery and diagnostics, apart from augmenting our understanding of the intriguing world of viruses. Unravelling evolutionary dynamics of viruses permits improved understanding of phenomena such as quasispecies diversity, role of mutations in host switching and drug resistance, which enables the tangible measurements of genotype and phenotype of viruses. Improved understanding of geno-/serotype diversity in correlation with antigenic diversity will facilitate rational design and development of efficacious vaccines against emerging and re-emerging viruses. Mathematical models developed using the genomic data could be used to predict the spread of viruses due to vector switching and the (re)emergence due to host switching and, thereby, contribute towards designing public health policies for disease management and control.

Part of the book: Next Generation Sequencing

By Kiran Kadam, Sangeeta Sawant, V.K. Jayaraman and Urmila Kulkarni-Kale

Allergic diseases are considered as one of the major health problems worldwide due to their increasing prevalence. Advancements in genomic, proteomic, and analytical techniques have resulted in considerable progress in the field of allergology, which has led to accumulation of huge amount of data. Allergen bioinformatics comprises allergen-related data resources and computational methods/tools, which deal with an efficient archival, management, and analysis of allergological data. Significant work has been done in the area of allergen bioinformatics that has proven pivotal for the development and progress of this field. In this chapter, we describe the current status of databases and algorithms, encompassing the field of allergen bioinformatics by examining work carried out thus far with respect to features such as allergens and allergenicity, allergen databases, algorithms/tools for allergen/allergenicity prediction, allergen epitope prediction, and allergenic cross-reactivity assessment. This chapter illustrates concepts and algorithms in allergen bioinformatics, as well as it outlines the key areas for potential development in allergology field.

Part of the book: Bioinformatics