Informatics and Biology are two sciences which are as different to each other as possible. One runs on core concept of variation and another on strict reasoning. But still these two have combined in a most natural way under the realm of “Bioinformatics”. For a biologist today it’s difficult to imagine a world without all biological databases and further no branch to decipher the huge enigma that it brings. Bioinformatics Review (BiR) journal is a platform to discover the latest happening in this melting pot of two varied fields.
The era of “omics” kick-started with drafting of Human Genome Project (HGP) in 2003. Since then, a number of technological advancements especially, NGS has been generating mind boggling data to the knowledge banks. Latest inventions like single cell transcriptomics or metagenomics of most unusual habitats show how evolution of technological advancements is directly resulting in breakthroughs of biological sciences.
Among various areas of biology which has benefited from these advancements is Pathology. In fact, deciphering the molecular and genetic basis of diseases in humans was the guiding force behind human genome sequencing Project. Bioinformatics has led to an impressive increase in recognition of possible pathogenic factors in varied systems, so much so that new techniques are being devised to increase the speed to actually test these factors in wet lab. If we consider computationally, smaller but ever changing genomes and transcriptomes of these pathogens, make them a much suitable candidate to test out many hypothesis for Bioinformatics studies. Effector Bioinformatics involves building custom pipelines for distinct species based on characteristics of effectors and size of genome involved. These can be based on Homology or feature extraction or both, e.g. discovery of RXLR motifs in Oomycete effectors allowed many more effectors to be identified. This collaboration of two sciences for plant pathology has led to development of many general use platforms like Broad-Fungal Genome Initiative, EuPathDB, PhytoPath and so on, but there is much need of developing specified resources like PHI-base for specific areas like effector biology. The use of machine-learning techniques like artificial neural network approach (which is actually based on biological neural networks) really shows how the two branches are so distinct yet so intertwined. All in all, it’s a brave new world where artificial communication is not only simulating but also helping us understand the communication (between host and pathogen) going within the realm of life.
In this issue, BiR focusses on reviews related to some of the very basic techniques which have been used in computational biology and its applications in various biological studies. We look forward to continuous support from our readers and contributors. For suggestions and feedback, do write to us at [email protected]
With Best Wishes
Roopam Sharma, Ph.D.
Editor, Bioinformatics Review