BOL

github.com - ContigExtender, was developed to extend contigs, complementing de novo assembly. ContigExtender employs a novel recursive Overlap Layout Candidates (r-OLC) strategy that explores multiple extending paths to achieve longer and highly accurate...

github.com - Phylogenomic Analysis Pipeline for Herbarium Specimens What is PhyloHerb: PhyloHerb is a wrapper program to process genome skimming data collected from plant materials. The outcomes include the plastid genome (plastome) assemblies,...

GATB Library. The Genome Analysis Toolbox with de-Bruijn graph. A large part of tools developed by the GenScale team are based on this library.These methods enable the analysis of data sets of any size on multi-core desktop...

http://ga4gh.org/#/ - GA4GH Data Working Group Led by David Haussler (UCSC) and Richard Durbin (Sanger Institute), the Data Working Group (DWG) of the Global Alliance brings together the leading Genome Institutes and Centers with IT industry leaders to create global...

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...

The genome of 130 mammals was sequenced by a large international consortium and the data was analyzed together with 110 existing genomes to allow scientists to identify the important positions in the DNA.

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...

Python Programming is a general purpose programming language that is open source, flexible, powerful and easy to use. One of the most important features of python is its rich set of utilities and libraries for data processing and analytics...

www.nature.com - Because of the increasing size and inherent complexity of biological data, there has been an increase in the application of machine learning in biology to create useful and predictive models of the underlying biological processes. All machine...

homes.sice.indiana.edu - Machine learning techniques have been successful in analyzing biological data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. In this class, we will learn basics about probabilistic models...