An exciting opportunity exists for a highly motivated and enthusiastic bioinformatics researcher to work in the Exosome, Secretome and Systems Biology laboratory of Dr Suresh Mathivanan. This position is funded through the National Institutes of Health (NIH) USA, to study the role of extracellular RNA or ExRNA in intercellular communication.

The successful applicant will be involved in collaborative bioinformatics research with more than 30 American Universities/Institutes. The ExRNA consortium is a multi-institute USD 17 million funded program which has 5 primary aims: to understand the biogenesis of ExRNA (vesicles and non-vesicles), to explore the use of ExRNA in biomarker research, to establish a reference profile of ExRNA in various disease conditions, to explore the role of ExRNA in therapeutic purposes and to manage the generated data through a reference portal. The bioinformatics component is critical in managing and analysing the data generated by the entire consortium. The researcher is required to contribute to the management and perform the analysis of ExRNA data.

The candidate to succeed, you will possess:

Experience in the analysis and modelling of data, including the capacity to integrate data from a range of sources and of uneven quality.

Evidence of experience in research and of the ability to work effectively under limited supervision or independently.

A record of contribution to publications, conference papers and/or reports, or professional or technical contributions which provide evidence of research potential.

Completion of a doctoral degree in bioinformatics or biostatistics with a focus on transcriptomic data will be highly regarded.

Preference will be given to applicants with competence in programming (JavaScript, Perl/Python), any web-based applications (PHP, ZOPE) and relational databases (MySQL).

Closing date: 30 September 2013

Position Enquiries: Dr Suresh Mathivanan (s.mathivanan@latrobe.edu.au)

More at http://www.mathivananlab.org/

Lab page @ http://krishna.gs.washington.edu/index.html

More @ http://www.bioinf.manchester.ac.uk/dbbrowser/index.php

Lab page: http://www.oeb.harvard.edu/faculty/edwards/index.html

Translational recoding.

RNA editing.

Evolution of the genetic code and translation.

More at http://lapti.ucc.ie/research.html

Lab page http://lapti.ucc.ie/index.html

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

Personal Genome Variation: SVs
Human Genome Annotation: Processing Next-Gen Sequencing Data
Comparative Genomics: Pseudogenes as Molecular Fossils
Protein Structure and Function: Macromolecular Motions
Analysis of Diverse Networks
Genomics at the Forefront of Data Science

Lab page: http://www.gersteinlab.org/