Address of the bookmark: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0090581

http://www.nbri.res.in/temp.php

Address of the bookmark: http://www.cytoscape.org/

School of Life Sciences

Department of Animal Biology

Applications are invited on a plane paper (along with copies of educational qualifications and experience) from eligible candidates for the selection of following position to work under a collaborative research project entitled “Development and application of high resolution genome conformation capture technology to investigate genome architecture in space and time” between University of Hyderabad and CR Rao advanced Institute of Mathematics, Statistics and Computer Sciences, sponsored by Department of Biotechnology, Government of India, New Delhi

Name and No. of positions JRF‐ONE

Emoluments for the position Rs. 25,000/p.m. + Eligible HRA

Qualifications MSc or M.Tech in any branch of biology/bioinformatics/computational biology/computer sciences/Mathematics/Physics

Duration Appointments are made initially for ONE year and can be extended further TWO years or until the duration of project

Our laboratory is interested in understanding signalling and spatiotemporal dynamics of 3‐Dimensional genome architecture and gene expression during embryonic stem cell differentiation by utilizing a combination of cellular, molecular genetics, Biochemical and computational tools in combination with next generation sequencing based chromatin structure analysing methods. Successful candidates shall pursue project related to either experimental or computational analysis of genome and Epigenomics data derived from human and mouse cells. Experience in Computational biology, bioinformatics, statistics, machine learning and algorithmic development is required. Knowledge of programming languages (e.g. C, C++, Perl, Python, Ruby etc.) and statistical framework (e.g. R, matlab, etc.) is preferable. Basic understanding of molecular biology will be an added advantage.

Interested candidates with the above mentioned qualification can send their curriculum vitae to Dr. K. Sreenivasulu, Department of Animal Biology, School of Life Sciences, South campus, University of Hyderabad or via email at positionssklab@gmail.com or svksl@uohyd.ernet.in.

Candidates with CSIR/UGC/ICMR/DBT/BINC qualifications if interested in above mentioned area of research are welcomed to approch principal investigator for a position leading to PhD. Last date for submission of applications is 17/06/2016. Eligible candidates will be called for an interview and they should carry all original certificates of the qualifying exam. No TA/ DA will be paid for attending the interview or at the time of joining the post.

Advertisement: http://www.uohyd.ac.in/images/recruitment/jrf_260516.pdf

More at http://www.ncbi.nlm.nih.gov/projects/HistoneDB2.0/index.fcgi/browse/

Address of the bookmark: http://www.ncbi.nlm.nih.gov/projects/HistoneDB2.0/index.fcgi/browse/

Blobsplorer is unlikely to be of use on its own as it requires contig data to be supplied in a format that involves considerable preprocessing (see below for a description). The easiest way to use Blobsplorer is as part of a workflow using scripts from here.

Address of the bookmark: http://nematodes.org/martin/blobsplorer/blobsplorer.html

Results: We present Cnidaria, a practical tool for clustering genomic and transcriptomic data with no limitation on ge-nome size or phylogenetic distances. We successfully simultaneously clustered 169 genomic and transcriptomic datasets from 4 kingdoms, achieving 100% accuracy at supra-species level and 78% accuracy for species level.

Availability and Implementation: Cnidaria is written in C++ and Python and is available at http://www.ab.wur.nl/cnidaria.

Contact: Saulo Aflitos - sauloal@gmail.com

Supplementary information: Supplementary data are available at Bioinformatics online.

Address of the bookmark: https://github.com/sauloal/cnidaria/wiki

LPI scores are inversely proportional to the phylogenetic distance between database match sequences and the query genome. These scores are useful not only for large-scalede novo predictions of horizontally transferred proteins, but can also serve as an independent quality control test for potential horizontal transfer candidates identified by alternative methods, especially those based on nucleic acid signatures. Candidates having high LPI scores are unlikely to have been horizontally transferred, since they are highly conserved among closely related organisms.

One unique and powerful feature of the DarkHorse HGT Candidate database is the opportunity to explore the phylogenetic background of potential HGT donors as well as recipients. The breadth of the database allows not only query sequences, but also their database match partners to be evaluated for sequence similarity or novelty compared to taxonomically related organisms.

DarkHorse is configurable for varying degrees of phylogenetic granularity and protein sequence conservation. Users should consult the references cited below for a complete explanation of parameter selection and result interpretation. A brief tutorial page is also available on-line.

Address of the bookmark: http://darkhorse.ucsd.edu/download.html