github.com - OMArk is a software for proteome (protein-coding gene repertoire) quality assessment. It provides measures of proteome completeness, characterizes the consistency of all protein coding genes with regard to their homologs, and identifies the presence...
There are many R software and bioconductor packages for NGS data analysis, some of them are as follows
Biostrings
The Biostrings package from Bioconductor provides an advanced environment for efficient sequence management and analysis in R. It...
Horizontal gene transfer (HGT), the “non-sexual movement of genetic material between two organisms” , is relatively common in prokaryotes and single-celled eukaryotes, but a number of factors combine to make it far rarer in...
The research group of Dr. Michele Trabucchi at the Centre Méditerranéen de Médecine Moléculaire (C3M) at INSERM U1065 (University of Nice Sophia-Antipolis, France) is seeking candidates for a Postdoctoral fellow position to start on October 2014 for...
github.com - MECAT is an ultra-fast Mapping, Error Correction and de novo Assembly Tools for single molecula sequencing (SMRT) reads. MECAT employs novel alignment and error correction algorithms that are much more efficient than the state of art of aligners and...
www.homolog.us - Useful bioinformatics tutorial, such as
De Bruijn Graphs for NGS AssemblyAlgorithms for PacBio ReadsSoftware and Hardware Concepts for BioinformaticsFinding us in Homolog.us (Search Algorithms)NGS Genome and RNAseq Assembly - a Hands on...
github.com - gapFinisher is based on the controlled use of a previously published gap filling tool FGAP and works on all standard Linux/UNIX command lines. They compare the performance of gapFinisher against two other published gap filling tools PBJelly and...
Workshop On Molecular Modeling and Dynamics Simulation Analyses
August1-2, 2014
Organised By
Centre of Excellence in Bioinformatics
Bioinformatics Infrastructure Facility
Department of Biochemistry
University of...
the sequenced reads can be mapped to the organism’s genes to assess how differently the genes are expressed under the experimental circumstances as opposed to the control scenario. This is known as differential expression (DE) analysis