It is often necessary to import sample textbook data into R before you start working on your homework.
Excel File
Quite frequently, the sample data is in Excel format, and needs to be imported into R prior to use. For this, we can...
NCBI Hackathon are pleased to announce the second installment of the SoCal Bioinformatics Hackathon. From January 9-11, 2019, the NCBI will help run a bioinformatics hackathon in Southern California hosted by the Computational Sciences Research...
www.melbournebioinformatics.org.au - Written and maintained by Simon Gladman - Melbourne Bioinformatics (formerly VLSCI)
Protocol Overview / Introduction
In this protocol we discuss and outline the process of de novo assembly for small to medium sized...
amp.pharm.mssm.edu - With BioJupies you can produce in seconds a customized, reusable, and interactive report from your own raw or processed RNA-seq data through a simple user interface
BioJupies now supports user accounts! Sign in from the top right corner of the page...
clauswilke.com - The book is meant as a guide to making visualizations that accurately reflect the data, tell a story, and look professional. It has grown out of my experience of working with students and postdocs in my laboratory on thousands of data...
rosenberglab.stanford.edu - distruct is a program that can be used to graphically display results produced by the genetic clustering program structure or by other similar programs. The figures produced by distructdisplay individual membership coefficients...
www.ncbi.nlm.nih.gov - A new approach to rapid, genome-wide identification and ranking of horizontal transfer candidate proteins is presented. The method is quantitative, reproducible, and computationally undemanding. It can be combined with genomic signature and/or...
github.com - Simka is a de novo comparative metagenomics tool. Simka represents each dataset as a k-mer spectrum and compute several classical ecological distances between them.
Developper: Gaëtan Benoit, PhD, former member of...
Huge amounts of genotype data are being produced with recent technological advances, both from increasingly comprehensive and inexpensive genome-wide SNP microarrays and from ever more accessible whole-genome and whole-exome sequencing methods