BOL: Related items

FACULTY POSITION at NATIONAL INSTITUTE OF TECHNOLOGY, ROURKELA

Sun, 05 Oct 2014 15:45:13 -0500

NIT, Rourkela, an institute of national importance under Ministry of HRD, Govt. of India invites applications from Indian nationals possessing excellent academic background along with commitment to quality teaching and research for faculty positions at the level of Professor, Associate Professor and Assistant Professor in most branches of Engineering, Science, Management and Humanities as per following table:-

1 Asst. Professor (on Pre-Ph.D. Contract)

2 Asst. Professor (on Contract)

3 Asst. Professor

4 Associate Professor

5 Professor

Life Sciences:-

i)Biochemistry and Molecular Biology; ii)Cell and Developmental Biology; iii)Immunology and Molecular Medicine; (iv) Microbiology and Ecology (v)Bioinformatics Group; vi)Biophysical Sciences

HOW TO APPLY:-

a. Candidates willing to apply for one or more posts are requested to apply online at “http://www.nitrkl.ac.in/ JOBS & TENDERS /Faculty Position” .
b. Persons employed in Government and Semi-Government organizations may apply directly against the standing advertisement. For this the application should be completed online. The printout of the application generated online should be submitted through employer if shortlisted for interview.
c. The online application can be filled in multiple sessions.
d. Candidates are required to check the Institute website from time to time for latest information, application status call for interview, change of dates and final results.
e. Applications shall be received online only. Please do not send application or CV against this advertisement by email or letter mail.

More Info: http://nitrkl.ac.in/Jobs_Tenders/1FacultyPosition/Default.aspx

Finishing !!

Jit — Sat, 20 May 2017 15:50:20 -0500

The process of finishing a genome and moving it from a draft stage (the result of sequencing and initial assembly) to a complete genome is typically a time and resource intensive task. The advent of new sequencing technologies has come with its own set of opportunities and pitfalls in the finishing process. While genomes can now be sequenced to high redundancy in a cost-effective manner, the process of assembling the genomes is more challenging and often draft genomes are fragmented into hundreds of contigs. Correspondingly, the task of producing the complete genome can involve months of lab work and thousands of finishing experiments and is usually done in large genome centers.

The work in our lab has focussed on computational approaches to speed-up the finishing process. Specifically, we have explored the use of optical mapping and mate-pair data to augment assemblies and direct finishing experiments. The tools developed in our lab have been used in several finishing projects, producing complete genomes (and near-complete ones) with surprisingly little computational and experimental effort (Nagarajan et al., in submission). The executables (as well as source code) for these tools are freely available here:

Scaffolding using Optical Restriction Mapping
Optical Maps are global, ordered maps of restriction site locations in a genome. This information can be quite useful in scaffolding contigs from a shotgun assembly to guide the finishing process. A set of programs to exploit optical maps for assembly can be found here: SOMA v2.0 (63 MB tar.gz file). This version of SOMA contains several improvements to programs in v1.0 as well as new scripts for working with multiple maps, contig graphs and scaffolds.
Augmenting assemblies with mate-pair data
Mate-pair information can be valuable in augmenting short-read assemblies and reconstructing the genome as larger scaffolds. AMOS-Hybrid is a pipeline written in the AMOS framework (open-source assembly tools) to merge arbitrary mated reads into an existing assembly and merge contigs and create scaffolds where possible. Source code and executables for AMOS-Hybrid are available here: AMOS-Hybrid v1.0 (142 MB tar.gz file).
Assembly and sequence-composition guided finishing
Contigs from a shotgun assembly are typically linked together in a graph structure that can serve to guide finishing and in some case close gaps in-silico. Also, in many cases, sequence composition of contigs can provide clues to fill gaps in scaffolds. A set of scripts to automate some of these tasks can be found here: Finishing Scripts v1.0 (63 MB tar.gz file).

http://www.cbcb.umd.edu/finishing/

Address of the bookmark: http://www.cbcb.umd.edu/finishing/

Software developed in pevsner lab

Robert M Willioms — Mon, 06 Oct 2014 12:41:26 -0500

DRAGON: Database Referencing of Array Genes Online

SNOMAD: Standardization and Normalization of Microarray Data

SNPduo: SNP Analysis Between Two Individuals

SNPtrio: Analyzing and Visualizing and Inheritance Patterns in Trios

SNPscan: Data Analysis and Visualization of SNP Data

pediSNP: Analyze SNP Data From a Pedigree of Two Generations

kcoeff: Calculate Cotterman Coefficients of SNP Genotype Data

triPOD: Detects chromosomal abnormalities in parent-child trio-based microarray data

Address of the bookmark: http://pevsnerlab.kennedykrieger.org/php/?q=software

PLAST: A fast, accurate and NGS scalable bank-to-bank sequence similarity search tool

Jit — Fri, 01 Dec 2017 04:10:54 -0600

PLAST is a fast, accurate and NGS scalable bank-to-bank sequence similarity search tool providing significant accelerations of seeds-based heuristic comparison methods, such as the Blast suite of algorithms.

Relying on unique software architecture, PLAST takes full advantage of recent multi-core personal computers without requiring any additional hardware devices.

PLAST stands for Parallel Local Sequence Alignment Search Tool and is was published in BMC Bioinformatics.

PLAST is a general purpose sequence comparison tool providing the following benefits:

PLAST is a high-performance sequence comparison tool designed to compare two sets of sequences (query vs. reference),
Reduces the processing time of sequences comparisons while providing highest quality results,
Contains a fully integrated data filtering engine capable of selecting relevant hits with user-defined criteria (E-Value, identity, coverage, alignment length, etc.),
Does not require any additional hardware, since it is a software solution. It is easy to install, cost-effective, takes full advantage of multi-core processors and uses a small RAM footprint,
Ready to be used on desktop computer, cluster, cloud as well as within distributed system running Hadoop.

https://plast.inria.fr/

Address of the bookmark: https://plast.inria.fr/

Research Fellows at CSIR - Institute of Himalayan Bioresource Technology, Palampur, Himachal Pradesh

Tue, 19 May 2015 07:17:32 -0500

CSIR - Institute of Himalayan Bioresource Technology 2 vacancies of Project Fellow

Name of the Post: Project Fellow

No. of the Post: 02 Two

Salary: Rs. 12000/- per month or Rs. 14000/- per month

Age Limit: Max. 28 years as on 10.06.2015 and relaxation as per rules

Required Job Profile:

Candidate must possess first class B.Tech. in bioinformatics or computational biology OR M.Sc. in bioinformatics or computational biology with fifty five percent marks OR M.Tech. in bioinformatics or computational biology with fifty five percent marks.

How to apply:

Eligible and interested candidates should need to appear for walk-in interview on 10.06.2015 at 9:00 am at the above mentioned address.

Refer to http://www.ihbt.res.in/recruit/AdvtNo7_2015.pdf

Porechop: tool for finding and removing adapters from Oxford Nanopore reads

Rahul Nayak — Tue, 29 May 2018 07:33:44 -0500

Porechop is a tool for finding and removing adapters from Oxford Nanopore reads. Adapters on the ends of reads are trimmed off, and when a read has an adapter in its middle, it is treated as chimeric and chopped into separate reads. Porechop performs thorough alignments to effectively find adapters, even at low sequence identity.

Porechop also supports demultiplexing of Nanopore reads that were barcoded with the Native Barcoding Kit, PCR Barcoding Kit or Rapid Barcoding Kit.

Address of the bookmark: https://github.com/rrwick/Porechop

Big genomic data on Google Cloud Platform

Fri, 17 Oct 2014 02:16:00 -0500

As the cost of DNA sequencing has dropped, the volume of data produced has risen into the petabytes. Google is working with the genomics community to define a standard API for working with big genomic data sets in the cloud. Building on Google Cloud Platform, we show how to store, process, explore and share genomic data using technologies like BigQuery, AppEngine MapReduce, R and more.

Convert EnsEMBL GTF to Annotation table (Geneid, GeneSymbol, GeneWiseChrLocation, GeneClass, Strand) Raw

EagleEye — Fri, 24 Jun 2016 18:08:49 -0500

Bash Script source:

https://gist.github.com/santhilalsubhash/367befcf5216be4b1fd9

Information:

This script converts EnsEMBL GTF (Ex: https://gist.githubusercontent.com/santhilalsubhash/1e7cca357e52a181dc25/raw/cfb803e07900a2baefbb6534f1299fd30cb57a29/sample.GTF) file to annotation table format. It generated two files
1) Transcript wise chromosome location with information about transcripts (Ex: https://gist.githubusercontent.com/santhilalsubhash/c7dec516e0338503a4b6/raw/de0af1a39f0005c4ce7321c5ae57fc8b4a14c7f4/sample.GTF_enst_annotation.txt)
2) Gene wise chromosome location with information about genes (Ex: https://gist.githubusercontent.com/santhilalsubhash/c92006c5080f0333bec2/raw/d16e0b2440d73b09b486d3c9751cdb248a73fa0b/sample.GTF_ensg_annotation.txt)

Note: You can download GTF files from http://www.ensembl.org/info/data/ftp/index.html

CLUSTER INNOVATION CENTER @ UNIVERSITY OF DELHI

Wed, 22 Oct 2014 10:39:49 -0500

Applications for Pre-selection of candidates under ‘Institutions Mode’ for DST-ISPIRE Faculty in Computational Biology/ Systems Biology/ Bioinformatics

Applications are invited for pre-selection of candidates for Ministry of Science and Technology, Department of Science and Technology INSPIRE Faculty Scheme: a component of “Assured Opportunity for Research Career (AORC)” under INSPIRE in the area of computational Biology/Systems Biology/Bioinformatics.

Candidates having done their B.Tech/B.E. and or M.Sc./M.Tech in Computer Science or Biotechnology and Ph.D. in Systems/ Computational Biology or Bioinformatics may apply in the following format prescribed by DST to the Director, Cluster Innovation Center, University Stadium, GC Narang Marg, University of Delhi, Delhi -11107. Detials of other qualification, age limits etc., please visit www.inspire-dst.gov.in.

Application on the prescribed format may be submitted by email to director@cic.du.ac.in before October 25, 2014. Selected candidates shall be called for an interview. The date, time and venue of the interview shall be informed by email/telephone. For more information about Cluster Innovation Center, please visit https://ducic.ac.in.

nQuire: a statistical framework for ploidy estimation using next generation sequencing

Jit — Thu, 04 Oct 2018 05:23:59 -0500

nQuire provides a statistical framework to study organisms with intraspecific variation in ploidy. nQuire is likely to be useful in epidemiological studies of pathogens, artificial selection experiments, and for historical or ancient samples where intact nuclei are not preserved. It is implemented as a stand-alone Linux command line tool in the C programming language and is available at https://github.com/clwgg/nQuireunder the MIT license.

Address of the bookmark: https://github.com/clwgg/nQuireunder