http://www.bccs.uni.no/units/cbu/research/rehmsmeier/

Address of the bookmark: http://bioinformatics.oxfordjournals.org/content/23/14/1713.full

Candidate Requirements:
A PhD in computer science, computational biology, Bioinformatics, or a related field, along with sufficient programming skills for prototyping. Experience with next generation sequencing data analysis is required. Candidates with MS degree but with relevant work experience can also be considered.

To Apply
To apply, please send your updated CV and cover letter to Dr. Rohit Gupta (rohit@strandls.com).

Source: http://www.strandls.com/application-scientist

CENTRE FOR BIOINFORMATICS

PUDUCHERRY

Applications are invited for one Project Assistant to work in the UGC sponsored Research Award "Molecular Docking and Dynamics studies to understand the interacting mechanism of oncogenic 101 protein with its cellular proteins".

The duration for the fellowship is 12months only with consolidated pay ofRs. 5,000 per month.

Application on plain paper with following details: Name, Address, Data of Birth, Father's Name, Nationality, Educational Qualification (SSLC onwards-enclose attested copies of certificate) and Researcb Experience may be addressed to Dr. R. Krishna, Principle Investigator (PI), UGC Research Award, Centre for Bioinformatics, Pondicherry University, Pondicherry - 605 014.

Application should reach in January 261h , 2013.

Essential Qualification: M.Sc. in Bioinformatics/Biophysics with good academic record.

Qualification for Project Fellow:

M.Sc in Bioinformatics/Biophysics.

The person to be considered for appointment as Project Fellow must have second class master degree with a minimum of 55% marks in the subject concerned or a related subject.

The candidate to be appointed as Project Fellows should be below thc age of40 years at the time of appointment.

Desirable Qualification for this Project: Research Experience in Small/Macromolecule Crystallography and Structural Bioinformatics.

For more details, refer the web site: www.pondiuni.edu.in/sites/default/files/BIC-311213.pdf

- Budapest Reference Connectome: View a parametrizable connectome (brain graph).
- AmphoraNet: The webserver implementation of the AMPHORA2 workflow for phylogenetic analysis of metagenomic shotgun sequencing data.
- AmphoraVizu: Chart visualization for metagenomics analysis tools AMPHORA2 and AmphoraNet.
- SCARF: Free online association rule mining tool.

More at: http://pitgroup.org

Source : https://www.coursera.org/course/ads1

Address of the bookmark: https://www.coursera.org/course/ads1

Dr. Rawal and his US based collaborators have recently secured grant for development of vaccine against an infectious disease agent. For this project, applications are invited for the posts of Post Doctoral Fellow/Research Scientist (One Position) for the following time-bound sponsored projects as per the details given below:

PI: Dr. Kamal Rawal, Biotechnology Department, JIIT, Noida.

Essential Qualification(s) for Post Doctoral Fellow/ Research Scientist:

We are seeking an individual with expertise in analyzing literature information, text mining, network biology, data integration, and modeling. Competitive candidates would also have programming experience in scripting languages with perl, C, C++, and R programming. This position requires a PhD in Computational Biology, Bioinformatics, Biostatistics, Physics or related fields, and evidence of scientific productivity through publications in international journals. Motivation to gain an in-depth understanding of biological phenomena is required. Applications should include a current CV and names of at least three references. Application packages and inquiries regarding this position can be sent to Dr. Kamal Rawal (bioinfocvatgmaildotcom and kamaldotrawalatgmaildotcom). Screening of applications will commence immediately and the position will remain open until filled. Candidates having master’s degree with extensive experience in IT industry or research can also be considered for this post.

Salary: Rs 50000 per month.

Duration: 2 years or upto the project duration.

Number of position: 1

Candidate may also fill the following form:

https://docs.google.com/…/1FAIpQLSdZoZ21ZoNRStEeL5…/viewform

http://tinyurl.com/bioinfocv2017

However, the ancient invasions and migrations to slavery and trade, history is embroidered with events that led to interactions between previously separate populations. Early humans migrated due to many factors such as changing climate and landscape and inadequate food supply. Historical migration of human populations begins with the movement of Homo erectus out of Africa across Eurasia about a million years ago. Homo sapiens appear to have occupied all of Africa about 150,000 years ago, moved out of Africa 70,000 years ago, and had spread across Australia, Asia and Europe by 40,000 years BC. Indo-Aryan migration from the Indus Valley to the plain of the River Ganges in Northern India is presumed to have taken place in the Middle to Late Bronze Age, contemporary to the Late Harappan phase in India (ca. 1700 to 1300 BC). From 180 BC, a series of invasions from Central Asia followed, including those led by the Indo-Greeks, Indo-Scythians, Indo-Parthians and Kushans in the northwestern Indian subcontinent.

Using the recent advance technologies researchers have created a historical atlas of instances of such mixing. They use a sophisticated statistical method for making inferences about human history and infer populations interbredings ( happen over the past 4,000 years) with an ease.

The study published the findings and presented with an interactive map. http://admixturemap.paintmychromosomes.com/

These sort of genomic study have some limilation. It is hard to precisely define sources of mixing when it occurred between genetically similar groups, and scenarios involving multiple waves of mixing over time or between multiple groups can be difficult to tease apart. But it is believed that larger sample sizes will improve resolution. These high resolution will provide a deeper understanding of human history.

Reference:

http://www.sciencemag.org/content/early/2014/01/28/science.1245938

http://www.ncbi.nlm.nih.gov/pubmed/21390129?dopt=Abstract&holding=npg

http://www.csulb.edu/~kmacd/paper-ethnicity.html

Image: Wikipedia

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.