BOL

github.com - gggenomes is a versatile graphics package for comparative genomics. It extends the popular R visualization packageggplot2 by adding dedicated plot functions for genes, syntenic regions, etc. and verbs to manipulate the plot to, for example,...

github.com - Description LoVis4u is a bioinformatics tool for Loci Visualisation. LoVis4u, a command-line tool and Python API designed for highly customizable and fast visualisation of multiple genomic loci. LoVis4u generates vector images in...

chunlab.wordpress.com - A tetra-nucleotide is a fragment of DNA sequence with 4 bases (e.g. AGTC or TTGG). Pride et al. (2003) showed that the frequency of tetra-nucleotides in bacterial genomes contain useful, albeit weak, phylogenetic signals. Even though...

tree.bio.ed.ac.uk - FigTree is designed as a graphical viewer of phylogenetic trees and as a program for producing publication-ready figures. As with most of my programs, it was written for my own needs so may not be as polished and feature-complete as a commercial...

Learn basics of Perl in a day

manuals.bioinformatics.ucr.edu - This tutorial is intended to introduce users quickly to the basics of R, focusing on a few common tasks that  biologists need to perform  some basic analysis:  load a table, plot some graphs, and perform some basic statistics. More...

en.wikibooks.org - Employing different technologies, the purpose of NGS platform is to decode the identity or modification on the nucleotides. NGS platforms evolve quickly and capture the main stream. This bookmark is created to provide NGS online books links.

An R tutorial for Microsoft Excel users

Part of the reason R has become so popular is the vast array of packages available at the cran and bioconductor repositories. In the last few years, the number of packages has grown exponentially! This is a short post giving steps on how to...

www.r2d3.us - In machine learning, computers apply statistical learning techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions. More at http://www.r2d3.us/visual-intro-to-machine-learning-part-1/