BOL

https://pgapx.ybzhao.com/ - PGAP-X is a microbial comparative genomic analysis platform with graphic interface. Serials of algorithms and methodologies have been developed and integrated to analyze and visualize genomics structure variation, gene distribution with different...

github.com - bpRNA, a novel annotation tool capable of parsing RNA structures, including complex pseudoknot-containing RNAs, to yield an objective, precise, compact, unambiguous, easily-interpretable description of all loops, stems, and pseudoknots, along with...

pypi.org - The Environment for Tree Exploration (ETE) is a Python programming toolkit that assists in the recontruction, manipulation, analysis and visualization of phylogenetic trees (although clustering trees or any other tree-like data structure are also...

Sample bandage input file for visual analysis ...

https://breedbase.org/ - Breedbase is a comprehensive breeding management and analysis software. It can be used to design field layouts, collect phenotypic information using tablets, support the collection of genotyping samples in a field, store large amounts of high...

https://r-graphics.org/ - R is powerful tool for data analysis, visualization, and machine learning. And it costs $0 to use! Here are six FREE books you can use to learn R...

The pacman package is an R package management tool that combines the functionality of base library related functions into intuitively named functions.

www.bioconductor.org - statistical analysis and visulization of functional profiles for genes and gene clustersBioconductor version: Release (3.3)This package implements methods to analyze and visualize functional profiles (GO and KEGG) of gene and gene clusters.Author:...

web.mit.edu - The following is a step-by-step guide to creating your own R package.  Even beyond this course, youmay find this useful for storing functions you create for your own research or for editing existingR packages to suit your needs. This guide...

bioconductor.org - The dupRadar package gives an insight into the duplication problem by graphically relating the gene expression level and the duplication rate present on it. Thus, failed experiments can be easily identified at a glance