Address of the bookmark: https://github.com/tanghaibao/jcvi

• dbCAN provides the capability of automated and comprehensive CAZyme annotation of a given genome submitted by the user;
• dbCAN provides an explicitly defined signature domain for each and every CAZyme family along with its location in all the relevant full-length CAZyme proteins in all sequenced genomes;
• dbCAN provides the most complete set of metagenomic CAZyme genes published so far and represents the first step towards discovering novel CAZyme catalysts in metagenomes;
• dbCAN provides a subfamily classification of the existing CAZyme families based on sequence similarities;
• dbCAN make all pre-computed data freely available to the public, including sequence alignments, hidden markov models (HMMs) and phylogenies of the signature domain regions in each and every CAZyme family and subfamily.

dbCAN is updated regularly when CAZy database created new families based on latest literature.

Address of the bookmark: http://csbl.bmb.uga.edu/dbCAN/index.php

Documentation can be found at https://nanoporetech.github.io/katuali/.

Address of the bookmark: https://github.com/nanoporetech/katuali

http://www.extension.org/pages/67926/upcoming-webinar:-selective-sequencing-through-combinatorial-pooling#.UggsVuHyPqU

The fate of a cell is ultimately the product of the regulation of its genes. Gene regulation is a coordinated process acting at multiple levels of which transcription and translation are the most prominent. The Valen group is dedicated to the fundamental question of how transcription and translation is integrated to obtain the desired protein abundance. The recent development of high-throughput next generation sequencing techniques to monitor both active translation and transcription has made it possible to study this connection at the genome scale.

This project aims to elucidate the links between regulation of translation and transcription. The applicant will analyze next generation sequencing data and model gene regulation on a genome-wide level to identify the features that affect the translational output of transcripts. The work will be done in close collaboration with experimental scientists who will test the predictions of the computational models.

Additional information on the position can be obtained by contacting Eivind Valen (eivind.valen@ii.uib.no).

The research fellow must take part in the University’s approved PhD program leading to the degree within a time limit of 3 years. Application for admission to the PhD program, including a project plan outline for the training module, will be worked out in collaboration with the research group in question.

In total, the fellowship period is 4 years, 25 % of this will be allocated to teaching and/or administrative duties. The fellowship period may be reduced if the successful applicant has held previous employment as a research fellow or similar.

http://www.jobbnorge.no/en/available-jobs/job/102235/research-fellow-phd-candidate-in-computational-biology-2-positions

About 8,000 years ago, the gene EGLN1 changed by a single DNA base pair. Today, a relatively short time later on the scale of human history, 88 percent of Tibetans have the genetic variation, and it was virtually absent from closely related lowland Asians. The findings indicate the genetic variation endows its carriers with an advantage.

In those without the adaptation, low oxygen caused their blood to become thick with oxygen-carrying red blood cells, an attempt to feed starved tissues, which could cause long-term complications such as heart failure. The researchers found that the newly identified genetic variation protected Tibetans by decreasing the over-response to low oxygen.

Reference: http://www.nature.com/nature/journal/v512/n7513/abs/nature13408.html

http://katjulab.com/research.html

If you would like to use GeneValidator on a few sequences, see our online GeneValidator Web App -http://genevalidator.sbcs.qmul.ac.uk.

If you use GeneValidator in your work, please cite us as follows:

Dragan M‡, Moghul MI‡, Priyam A, Bustos C & Wurm Y. 2016. GeneValidator: identify problems with protein-coding gene predictions. Bioinformatics, doi: 10.1093/bioinformatics/btw015.

 

Address of the bookmark: https://github.com/wurmlab/genevalidator

Address of the bookmark: http://pbil.univ-lyon1.fr/software/DeCoSTAR/

(i) can be used for HGT detection in both prokaryotes and eukaryotes,

(ii) can report a statistical P value for each gene to indicate how likely it is to be horizontally transferred, and

(iii) is fully automated (requires minimal human intervention), as well as very easy to install and run. 

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4626719/