Candidates having the below mentioned qualifications may appear for Walk in Interview at ICPO on 5th Feb 2014 between 10.00 AM and 12.00 PM under the NIF project entitled "Prediction of drug tragets of chemical constituents present within non-codified medicinal plants" under Dr Subhash M.Agarwal, Scientist C

Position : JRF
No of Post : One
Pay : Rs 12000/- + 30% HRA

Desired Profile : M.Sc in Bioinformatics with good academic record. Candidate with experience in database development and scripting would be preferred
Age Limit : Below 28 years
Period : 2 months

Interested candidates may send their applications with bio-data by email (smagarwal@gmail.com) or post addressed to Dr Subhash M Agarwal, Scientist C, Bioinformatics Division, Institute of Cytology and Preventive Oncology (ICPO) I-7, Sector 39, Noida-201301 so as to reach latest by 04.02.14

Deadline : 04.02.14

http://icmr.nic.in/icmrnews/icpo_jrf.pdf

The program utilizes tBLASTn and BLASTn algorithms to map genes from the reference genome (the annotated strain) to the new sequence (the unannotated strain). The goal is to annotate the majority of the new genome’s genes in a single step. ORFs present in the target genome and absent from the reference genome are also identified; these ORFs can be further analyzed using BLAST, VGO and BBB. Afterwards, they can either be accepted for/rejected from annotation. GATU can handle multiple-exon genes as well as mature peptides. Although it was designed for use with viral genomes, GATU can also be used to help annotate larger genomes (ie. bacterial genomes).

The output is saved in GenBank, XML, or EMBL file format.

Address of the bookmark: https://virology.uvic.ca/help/tool-help/help-books/genome-annotation-transfer-utility-gatu-documentation/

* Analysis of Gene Expression Pattern Images: high-performance image analysis and mining for different model organisms, such as fruitfly, C. elegans, and mouse;
* Feature/Model Learning: developing algorithms and software

Location :Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA.

http://research.janelia.org/peng/

Address of the bookmark: http://www.mdpi.com/2073-4425/3/3/423

This position will have a significant focus on providing analytical support for next generation sequencing data analysis – Exome-sequencing, Targetted sequencing as well as high-throughput genotyping on Illumina platform.

Job location:

Genome Research Chair
King Saud University, Riyadh-11451
KSA

Interested candidate may forward their CV to grcksu@gmail.com

Required Qualifications: Masters in physics/chemistry/mathematics (or) MTech in bioengineering, chemical (or) Masters in any traditional field of science with outstanding performance throughout the program. Candidate should have cleared GATE/UGC-CSIR examinations. Applicant should have done basic mathematics courses like calculus, differential equations, numerical analysis etc in their degree program and have obtained good grades in those courses. Knowledge of MATLAB and C or at least one traditional programming language is absolutely necessary. Strong inclination to understand biological concepts is a must for this research work as this project is about modeling biological systems.

Salary: A fixed salary of Rs 18000 PM including HRA will be paid.

Last date for application: This advertisement is open until suitable candidate is found for the project.

Preferred Qualifications: - Expertise in dynamical systems theory, bifurcation theory, numerical simulations, parameter estimation.

Independence and high motivation for carrying out interdisciplinary research. - Excellent communication skills and ability to work independently. - Good working habits.

Interested candidates should submit both curriculum vitae and statement of interest in PDF format to sriramk@iiitd.ac.in and should clearly mention in the subject "Application for SRF".

Given the potential relevance of efficient haplotyping in several analysis pipelines, we have designed and engineered pWhatsHap, a parallel, high-performance version of WhatsHap. pWhatsHap is embedded in a toolkit developed in Python and supports genomics datasets in standard file formats. Building on WhatsHap, pWhatsHap exhibits the same complexity exploring a number of possible solutions which is exponential in the coverage of the dataset. The parallel implementation on multi-core architectures allows for a relevant reduction of the execution time for haplotyping, while the provided results enjoy the same high accuracy as that provided by WhatsHap, which increases with coverage.

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1170-y

Address of the bookmark: https://bitbucket.org/whatshap/whatshap

Our research is at the crossroad between cell biology, ecological genomics, systems biology, molecular evolution and population genetics. We study the architecture and evolution of protein and signalling networks.

More at http://landrylab.ibis.ulaval.ca/

Address of the bookmark: https://gvolante.riken.jp/analysis.html