Ever since a monk called Mendel started breeding pea plants we've been learning about our genomes. In 1953, Watson, Crick and Franklin described the structure of the molecule that makes up our genomes: the DNA double helix. Then, in 2001, scientists wrote down the entire 3-billion letter code contained in the average human genome. Now they're trying to interpret that code; to work out how it's used to make different types of cells and different people. The ENCODE project, as it's called, is the latest chapter in the story of you. To read the ENCODE research papers and more, visit http://www.nature.com/ENCODE

1.Stupid for biologist: Biology is so complex that it will make bioinformatician feel stupid. There are no any universal fixed rules; it can surprise you any time. So be nice to biologists who ask questions and resolve your biological puzzles. Sometime you will have no idea what the hell you were doing either.

2.Puzzling why: Do not hesitate to ask question. Especially. at the beginning of project you will have to ask a lot of questions. Instead of puzzling it out at end check out and clear your doubt even for a single error. It may can leads to wrong conclusion.

3.Running marathon: The most of the biological software’s documentation is always incomplete. In other word they are no more than 95 percent complete. Sometime a single problem can halt your entire project for months. Compilation and running the pipelines in tedious because almost all are interdependent and need proper configuration. I face the same kind of problem with Evolver :( …

4.Folders missing: The pipelines generate lots of data, and we keep them in several folders for future use. But sometime we delete them by mistake and move to recovery…

5.Digging deeper: Digging deeper is fruitful, but some time it can be catastrophic. You may get frustrated or direction less. So keep a biologist with you for rescue …. Sometime an expert computer programmer to handle your server. Remember, the server will always go down when you need it the most.

The most common frustrating  common line: Why do we do this again?

Job Description: We are interested in finding an excellent postdoc with interests in protein functional annotation, machine learning and computer grids. The position is open for 3.5 years at the Université Pierre et Marie Curie, in the heart of paris.

Research topic: Protein function annotation, multiple probabilistic models, domain architecture, machine learning, combinatorial optimization, computer grid.

Title: A novel integrative platform for large scale protein annotation that exploits a multitude of diversified probabilistic models in several protein signature databases.

We propose a novel integrated approach for large scale protein annotation that will exploit an unprecedented amount of genomic data as well as sophisticated machine learning techniques and combinatorial optimization approaches taking advantages of High Performance Computing (HPC) environments. The idea is to uncover as much as possible the evolutionary processes of protein sequences that took place throughout the whole tree of life and that affected the evolution of a protein family. We have already demonstrated in a previous work that the problem of functional annotation is inherent to the ability of uncovering such paths. Now, we shall extend this approach to large scale genome annotation by considering 11 different protein databases, constituted by about 10^9 protein sequences, and by producing a large pool of diversified probabilistic models coding for about 10^7 evolutionary protein pathways. Such models will be used to search for specific domains in genomes to be annotated. Our previous methodology needs to be fundamentally improved to deal with this large amount of biological data. In this project, we shall work on the algorithms to reduce the space of models and the search complexity, and we shall implement some important algorithmic changes towards the realization of a powerful integrated annotation tool.

Where: This project is run on the Laboratoire de Biologie Computationnelle et Quantitative UMR7238 CNRS-UPMC – Analytical Genomics team, headed by A.Carbone. It is co-advised with Pierre-Henri Wuillemin, Laboratoire d’Informatique de Paris 6 – Equipe DECISION.

Start date: September 1st, 2014
Contact Person: Alessandra Carbone
Contact: alessandra.carbone@lip6.fr

The image summarise all in one.

More at http://users.rcn.com/jkimball.ma.ultranet/BiologyPages/C/Codons.html

Applications are invited for the post of Junior Research Fellow (JRF) in a DBT funded IYBA project entitled “Generatingaprotein-ncRNA interactome for Dorsal mediated gene regulation and dorso-ventral patterning genes in Drosophila” in the Lab. Of Molecular Biology at the Faculty of Life Sciences and Biotechnology, South Asian University, New Delhi. The project requires extensive use of molecular, genetic and genomic approaches.

POST: Junior Research Fellow (JRF)

NO. OF VACANCIE(S) - (01)

FELLOWSHIP: Rs. 16,000/- plus HRA

PROJECT DURATION: 2014-2016 (Two years)

LAST DATE FOR APPLICATION: Aug 18, 2014.

Eligibility criteria:

M.Sc./M.Tech./ in Biological Sciences/Biotechnology/Bio-Informatics. Candidates with research experience in the field of Drosophila/Yeast genetics will be preferred.

Application Procedure:

A covering letter along with your CV, copy of prior publications (if any) and proof of experience should be e-mailed to lmb_sau@aol.com. Hardcopy of the application should be brought on the day of interview along with other testimonials and marks statements for verification purpose.

IMPORTANT NOTE:

-No TA/DA will be paid for attending the interview.

-SAU may select candidates against the post depending upon qualification and experience of candidates and reserves the right to relax any of the qualifications in case the candidate is found otherwise well qualified by the Selection Committee

-The abovementioned post is temporary and will be initially offered for a period of one year and can be extended, on satisfactory performance.

More at http://www.sau.ac.in/recruitment/vacancy.html

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/

Eligibility : MSc, M Phil / Phd, BE/B.Tech
Location : Himachal Pradesh-other
Job Category : Govt Jobs, Research, Walkin
Last Date : 20 Aug 2014

Advertisement No.6/2014

Post : Project Fellow
Research Associate/ Project Fellow Jobs opportunity in CSIR-Institute of Himalayan Bioresource Technology
M.Sc. in Bioinformatics/Computer Science with 55% marks and (ii) M.Sc. Bioinformatics/ Computational biology/ P.G. Diploma in Bioinformatics/B.Tech. or higher Degree in Bioinformatics with 55% marks

Date of Interview: 29.08.2014.

More at http://www.ihbt.res.in/recruit/AdvtNo6_2014.pdf

Address of the bookmark: http://schatzlab.cshl.edu/data/nanocorr/