Predicting Microbial Genome-Encoded Biomolecular Networks

Raphael Isokpehi, Bethune-Cookman University

Usage Details

This project will enable undergraduate students to develop skills and expertise to effectively use tools on Blue Waters to predict and visualize biomolecular networks from functional and structural annotations of microbial genes.

According to the Integrated Microbial Genomes database: “At the start of 2015, IMG had a total of 32,802 genome datasets from all domains of life and 5,234 metagenome datasets, out of which 27,341 genome datasets and 3,193 metagenome datasets are publicly available.”

Functional and structural annotations for genes in microbial genomes are increasingly available as multivariate data sets in formats suitable for a variety of cognitive activities including knowledge discovery, sense making, problem-solving and planning future research.

The exponential increase in whole genome sequences of bacteria and archaea presents a source of large and complex data on functional and structural annotations of genes. The annotations for function and transcriptional direction of genes adjacent to a gene locus in genomes of bacteria and archaea can be informative on biological process that involve the gene.

Therefore there is a critical need to index of Microbial Gene Loci based on Transcriptional Direction of Adjacent Genes to facilitate cognitive activities including knowledge discovery and planning future research.