BOL: Related items

Comparative genomics educational material and papers bookmarks

Jit — Wed, 09 Nov 2016 16:23:30 -0600

Alignment of the porcine genome against seven other mammalian genomes (Supplementary Information) identified homologous synteny blocks (HSBs). Using porcine HSBs and stringent filtering criteria, 192 pig-specific evolutionary breakpoint regions (EBRs) were located. The number of porcine EBRs is comparable to the number of bovine-lineage-specific EBRs (100) reported earlier using a slightly lower resolution (500 kilobases (kb)), indicating that both lineages evolved with an average rate of ~2.1 large-scale rearrangements per million years after the divergence from a common cetartiodactyl ancestor ~60 Myr ago². This rate compares to ~1.9 rearrangements per million years within the primate lineage (Supplementary Table 11). A total of 20 and 18 cetartiodactyl EBRs (shared by pigs and cattle) were detected using the pig and human genomes as a reference, respectively.

Address of the bookmark: http://www.nature.com/nature/journal/v491/n7424/abs/nature11622.html

RA Bioinformatics at NATIONAL INSTITUTE OF CANCER PREVENTION & RESEARCH (ICMR)

Thu, 17 Nov 2016 04:11:09 -0600

NATIONAL INSTITUTE OF CANCER PREVENTION & RESEARCH (ICMR)

Noida 201301 (U.P)

Applications are invited upto 21.11.2016 from interested candidates as per details available on NICPR website (www.nicpr.res.in)/ ICMR website (www.icmr.nic.in) to fill up following temporary position in the time bound DHR Project entitled “Next generation EGFR inhibitor identification using ligand based QSAR technique” under Dr. Subhash M. Agarwal, Scientist-D, Division of Bioinformatics.

Research Assistant (One)

Rs.27000/- p.m. (Fixed/temporary)

Essential: M.Sc. in Bioinformatics or related field.

Desirable: Experience in QSAR and structure based drug designing.

More Info : www.icmr.nic.in/icmrnews/NICPR_Advertisement%20for%20RA.pdf

Professor (all levels) in Bioinformatics and Computational Biology

Tue, 22 Nov 2016 05:43:38 -0600

King Abdullah University of Science and Technology (KAUST) (kaust.edu.sa) is seeking a highly motivated and skilled faculty member for the Bioinformatics track whose research focuses on development of methods and tools for Bioinformatics and Computational Biology.
KAUST is an international, graduate-level research university dedicated to advancing science and technology through interdisciplinary research, education, and innovation. Located on the shores of the Red Sea in Saudi Arabia, KAUST offers superb research facilities, generous assured research funding, and internationally competitive salaries, attracting top international faculty, scientists, engineers, and students to conduct fundamental and goal-oriented research to address the world’s pressing scientific and technological challenges in the areas of food, water, energy, and the environment.
The successful applicant is expected to develop world-leading research in domain of bioinformatics/computational biology with focus on development of novel computational approaches for efficient and accurate methods of analyzing biological phenomena at molecular level. The faculty member will be part of the Computational Bioscience Research Center (CBRC) within the Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division. The position will remain open until filled.

Requirements:

PhD or equivalent in a Computer Science, Mathematics or Engineering discipline. Candidates should be well-established within the research field relevant to the position grade. They should demonstrate original research and experience at the highest international level.

Responsibilities and tasks:

Research competence in the following areas is preferred:
Analysis of next generation sequencing (NGS) and other ‘omics’ data (e.g. CAGE, ChIP-Seq, DHS, RNA-Seq, Ribo-Seq, proteomic, metabolic and NMR spectra, etc.).
Signaling, regulatory and metabolic pathways analysis.
Development of tools (web-based and standalone) suited for efficient computational biology/bioinformatics.

Visit cemse.kaust.edu.sa to apply.

EXCAVATOR2tool

Bulbul — Wed, 30 Nov 2016 04:09:19 -0600

EXCAVATOR2 is a collection of bash, R and Fortran scripts and codes that analyses Whole Exome Sequencing (WES) data to identify CNVs. EXCAVATOR2 enhances the identification of all genomic CNVs, both overlapping and non-overlapping targeted exons by integrating the analysis of In-targets and Off- targets reads. Specifically, it improves the precision of calling CNVs overlapping targeted exons from WES data and enlarges the spectrum of detectable CNVs to off-target events.
EXCAVATOR2 can be effectively employed for the identification of CNVs in small as well as large-scale re-sequencing population and cancer studies. Lastly, it’s of particular interest that all WES experiments can be re-analysed using our method with the beneficial effect to identify novelCNVs in extra-exonic regions by having the full-genome CN profile.

Address of the bookmark: https://sourceforge.net/projects/excavator2tool/

DBT India

Jit — Sun, 04 Dec 2016 22:30:37 -0600

Latest announcement on DBT India.

Calls

Events

Projects

Jobs

Address of the bookmark: http://www.dbtindia.nic.in/out-reach/latest-announcements/

Venkatesh Lab

Tue, 20 Dec 2016 04:38:01 -0600

We are using a comparative genomics approach to better understand the structure, function and evolution of the human genome. Our group is one of the pioneers in the field of comparative genomics. We proposed the compact genome of the fugu (Takifugu rubripes) as a model vertebrate genome in 1993 (Nature 366: 265-268, 1993) and determined its whole genome sequence in 2002 (Science 297: 1301-1310, 2002).

More at
https://zfin.org/ZDB-LAB-110408-1
http://www.imcb.a-star.edu.sg/php/venkatesh.php

Finding Patterns in Biological Sequences

Jit — Thu, 22 Dec 2016 10:30:49 -0600

In this report we provide an overview of known techniques for discovery of patterns of biological sequences (DNA and proteins). We also provide biological motivation, and methods of biological verification of such patterns. Finally we list publicly available tools and databases for pattern discovery. On-line supplement is available through http://genetics.uwaterloo.ca/∼tvinar/cs798g/motif.

Address of the bookmark: http://engr.case.edu/li_jing/papers/00798gpattern.pdf

Prodigal (Prokaryotic Dynamic Programming Genefinding Algorithm)

Abhimanyu Singh — Thu, 29 Dec 2016 03:26:45 -0600

Prodigal (Prokaryotic Dynamic Programming Genefinding Algorithm) is a microbial (bacterial and archaeal) gene finding program developed at Oak Ridge National Laboratory and the University of Tennessee. Key features of Prodigal include:

Speed: Prodigal is an extremely fast gene recognition tool (written in very vanilla C). It can analyze an entire microbial genome in 30 seconds or less.
Accuracy: Prodigal is a highly accurate gene finder. It correctly locates the 3' end of every gene in the experimentally verified Ecogene data set (except those containing introns). It possesses a very sophisticated ribosomal binding site scoring system that enables it to locate the translation initiation site with great accuracy (96% of the 5' ends in the Ecogene data set are located correctly).
Specificity: Prodigal's false positive rate compares favorably with other gene identification programs, and usually falls under 5%.
GC-Content Indifferent: Prodigal performs well even in high GC genomes, with over a 90% perfect match (5'+3') to the Pseudomonas aeruginosa curated annotations.
Metagenomic Version: Prodigal can run in metagenomic mode and analyze sequences even when the organism is unknown.
Ease of Use: Prodigal can be run in one step on a single genomic sequence or on a draft genome containing many sequences. It does not need to be supplied with any knowledge of the organism, as it learns all the properties it needs to on its own.
Open Source: Prodigal source code is freely available under the General Public License.

Download the latest version of Prodigal at the Prodigal github page.
or
Browse the wiki documenation.

Address of the bookmark: http://prodigal.ornl.gov/

YAHA

Jit — Fri, 20 Jan 2017 05:38:05 -0600

YAHA, a fast and flexible hash-based aligner. YAHA is as fast and accurate as BWA-SW at finding the single best alignment per query and is dramatically faster and more sensitive than both SSAHA2 and MegaBLAST at finding all possible alignments. Unlike other aligners that report all, or one, alignment per query, or that use simple heuristics to select alignments, YAHA uses a directed acyclic graph to find the optimal set of alignments that cover a query using a biologically relevant breakpoint penalty. YAHA can also report multiple mappings per defined segment of the query. We show that YAHA detects more breakpoints in less time than BWA-SW across all SV classes, and especially excels at complex SVs comprising multiple breakpoints.

Availability: YAHA is currently supported on 64-bit Linux systems. Binaries and sample data are freely available for download from http://faculty.virginia.edu/irahall/YAHA.

Contact:

http://genome.wustl.edu/people/groups/detail/hall-lab/

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3463118/

SRF Bioinformatics at JNU

Tue, 24 Jan 2017 07:34:35 -0600

School of Life Sciences
Jawaharlal Nehru University
New Delhi 110067

Positions available

Applications were invited from for the following posts in an industry sponsored project. The project entitled "OsHK3b technology and Know How", valid for a period upto February, 2018.

Post 3: Senior Research Fellow (Computational Biologist / Metabolic engineering)

Salary: As per DBT rule.

Duration: All the above posts are purely temporary and liable to be terminated at any time without prior notice or ceased/withdrawn by the funding agency.

Age limit: The upper age limit for SRF shall be 32 years, which is relaxed upto 5 years in the case of candidates belonging to Schedule Castes/Schedule Tribes, Women, Physically Handicapped and OBC applicants.

Essential Qualifications: Masters/B Tech/Mtech in Basic Sciences with at least 2yrs of research experience in Bioinformatics/Computational Biology related to Database /portal building & maintenance, high throughput data handling and analysis etc. For M.Sc/B.Tech, Published paper in peer-reviewed Journal and for M.Tech, thesis submission in computational biology is a must. Selection preference will be given to candidates with a good knowledge of Python and/or R. Knowledge of JAVA will also get a special consideration.

Desired Skills: Will be expected to manage ongoing research activities in the project, interact with Experimental group, manage the project data analysis, prepare file reports and associated project work etc. Familiarity with plant systems biology and genomics /metabolite resources related to plant metabolomics is desirable.

1. The post applied for must be clearly written on the Envelope containing the application
2. Applications received after last date shall not be entertained, School will not be responsible for any postal delay.
3. No application will be accepted via hand delivery or via e-mail. Please send printed & signed applications with detailed CV on or before 31st January, 2017 by post to the following address:

Prof. Ashwani Pareek
(Project Investigator)
Stress Physiology and Molecular Biology Laboratory (Room No-413),
School of Life Sciences,
Jawaharlal Nehru University,
New Delhi, India – 110067
Email: ashwanipareek@gmail.com