As a result of advancement in sequencing technology and the substantial decrease in cost, gene discovery in biology has increased exponentially. As a result, the application of next generation sequencing, which includes the whole genome and exome sequencing, has become a powerful tool to understand the genetic etiology of complex traits. Choosing the most suitable next-generation sequencing platform can be challenging due to the considerable sequencing costs; which includes gathering a substantial amount of generated data before and after the analysis⁠. Therefore, the main challenge lies in choosing the appropriate approach for the analysis when dealing with these large amounts of sequence data and how to filter this data according to priority and pathogenicity. Whole genome sequencing is a cutting-edge technique where the best methods for analysis, both in data generation and statistical analysis, are currently unknown.

With every gene discovery, the next discovery becomes more difficult because the remaining genes are more likely to be rare and missed by previously used techniques. To overcome these obstacles, collaboration between geneticists, bioinformaticians, and biologists is an effective strategy. In this selection of articles, we are aiming to present bioinformatics algorithms and workflows in medicine and agriculture that are either inherently applicable to front-line practitioners, or have extensions or ancillary programs that make them usable. We believe that the realms of agriculture and medicine have much to learn from each other in this sense, and therefore have included them in a single Research Topic. Thus, we aim to improve bioinformatics applications to have a seamless interface with frontline practitioners such as clinicians, translational researchers, and plant scientists.

Themes of interest include, but are not limited to:

· New developments in genome bioinformatics and computational biology

· Computational algorithms, software, and statistical models.

· Recent progress in computational software and computing tools for modern day bioinformatics.

· Application of NGS for modern day genomics including agriculture and medicine.

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Frontiers in Bioinformatics

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