Adding Bio-Statistical Machine Learning Models and Graphical visualization to ABioTrans V2

<p>ABioTrans is a bio-statistical/informatics tool, developed in R for gene expression analysis. The tool allows the user to directly read RNA-Seq data files deposited in the Gene Expression Omnibus or GEO database. It provides easy options for performing very commonly used statistical techniques, namely, Pearson and Spearman rank correlations, Principal Component Analysis (PCA), k-means and hierarchical clustering, Shannon entropy, Noise (square of the coefficient of variation), differential expression (DE) analysis, and gene ontology classifications</p> <p>This project aims to develop the 2nd version of ABioTrans. ABioTrans version-2 will be web-based and will provide extensive analysis options to the gene expression analysis results such as pathway enrichment analysis, gene function, t-SNE, Protein Protein Interaction, SOM , SVM as well as publication-ready visualization options including network visualization using Cytoscape.JS As the current version of Abiotrans is not online, it gets very difficult and time consuming process for the biologist who want to perform few analysis. As it's a very time consuming &amp; tedious process. So, taking it online will solve a huge problem.</p>