PNAS papers:
http://www.pnas.org/search?author1=Janet+Kelso&sortspec=date&submit=Submit

Jobs:
http://www.eva.mpg.de/genetics/bioinformatics/jobs.html

Contact:
Kelso Group
Department of Evolutionary Genetics
Max Planck Institute for Evolutionary Anthropology
Deutscher Platz 6
04103 Leipzig
Germany
Email: kelso@eva.mpg.de

Name of the fellowship: Junior Research Fellow (JRF) / Project Fellow

Title of the project: Genome-wide Mapping of Murine Specific Dengue T-cell Epitopes: Computational Prediction, Identification and use as Candidate Vaccines

Duration: 3 years

Fellowship: Rs. 18,000 for first 2 years and Rs. 20,000 for 3rdyear (for M.Tech. candidates)

Rs. 16,000 for first 2 years and Rs. 18,000 for 3rdyear (for M.Sc. candidates with NET qualification)

Rs. 8,000 for first 2 years and Rs. 10,000 for 3rdyear (for M.Sc. candidates without NET qualification)

Qualifications: M.Tech. in Biotechnology / M.Sc. in any branch of Life Sciences

Desirable Experience: Minimum of two years research experience in any of the following areas: Immunology / Microbiology / Gene Manipulation / Bioinformatics

Interested and eligible candidates may apply with their resume along with relevant documents and a passport size photograph to the Principal Investigator by post (or e-mail) on or before December 31, 2013. Only short listed candidates will be called for written test and/or interview. Selected candidate may register for PhD in Kalasalingam University. No TA/DA will be paid for attending interview.

Dr. K. Sundar
Principal Investigator (SERB Project)
Department of Biotechnology
Kalasalingam University
Krishnankoil – 626126, Tamil Nadu
sundarkr@klu.ac.in

• Bioconductor – A plethora of tools for analysis and comprehension of high-throughput genomic data, including 1500+ software packages. [ paper-2004 | web ]
• Biopython – Freely available tools for biological computing in Python, with included cookbook, packaging and thorough documentation. Part of the Open Bioinformatics Foundation. Contains the very useful Entrez package for API access to the NCBI databases. [ paper-2009 | web ]
• Bioconda – A channel for the conda package manager specializing in bioinformatics software. Includes a repository with 3000+ ready-to-install (with conda install) bioinformatics packages. [ paper-2018 | web ]
• BioJulia – Bioinformatics and computational biology infastructure for the Julia programming language. [ web ]
• Rust-Bio – Rust implementations of algorithms and data structures useful for bioinformatics. [ paper-2016 ]
• SeqAn – The modern C++ library for sequence analysis.

Address of the bookmark: https://academic.oup.com/bioinformatics/article/25/22/3005/179064

In this tutorial series article, I will explore features and packages of python which are widely used in the big data, NGS, and bioinformatics. I will also walk through a real biological example which shows NGS data processing with the help of python packages and programming.

Python has a couple of points to recommend it to biologists and scientists specifically:

• It's widely used in the scientific community
• It has a couple of very well designed libraries for doing complex scientific computing (although we won't encounter them in this book)
• It lend itself well to being integrated with other, existing tools
• It has features which make it easy to manipulate strings of characters (for example, strings of DNA bases and protein amino acid residues, which we as biologists are particularly fond of)

In general, following are some of the important features of python which makes it a perfect fit for rapid application development.

• Python is interpreted language so the program does not need to be compiled. Interpreter parses the program code and generates the output.
• Python is dynamically typed, so the variables types are defined automatically.
• Python is strongly typed. So the developers need to cast the type manually.
• Less code and more use makes it more acceptable.
• Python is portable, extendable and scalable.

There are two major Python versions, Python 2 and Python 3. Python 2 and 3 are quite different. This tutorial uses Python 3, because it more semantically correct and supports newer features.

I will post tutorial on daily basis on this page. Check the sub-pages on right side.

Address of the bookmark: https://github.com/carolzhou/multiPhATE

Seq is a programming language for computational genomics and bioinformatics. With a Python-compatible syntax and a host of domain-specific features and optimizations, Seq makes writing high-performance genomics software as easy as writing Python code, and achieves performance comparable to (and in many cases better than) C/C++.

Learn more by following the tutorial or from the cookbook.

Address of the bookmark: https://seq-lang.org

Address of the bookmark: https://bioinformatik.de/en/bioinformatics-in-germany/research/research-groups.html

More at https://rgcb.res.in/jobs.php