Genome Annotation and Functional Genomics

Bergman Lab is actively engaged in the development and application of computational methods to improve the annotation of functional biological features in genome sequences. Bergman Lab work focuses on improving annotation of non-protein-coding regions of the genome including conserved noncoding sequences (CNSs), cis-regulatory modules (CRMs), transcription factor binding sites (TFBSs), transposable elements (TEs) and noncoding RNA (ncRNA) genes. Current projects include improving the (i) annotation of TEs in the fly and yeast genomes, (ii) annotation of CRMs and TFBSs in the fly genome, and (iii) analysis of transposon knockout collections in flies. Research in this area is supported by the EC FP7 programme.

Genome and Molecular Evolution
Text and Data Mining

More @ http://bergmanlab.smith.man.ac.uk/

Research Interest
Genomic Data Integration

Microarray Analysis

Gene and Protein Function Prediction

Detection and Analysis of Chromosomal Abnormalities and Functional Evolution

Integration of Computation and Experiments

Identification of Biological Networks and Pathways

Evaluation and Validation of Computational Predictions

Scalable Visualization-Based Data Analysis

More @ http://reducio.princeton.edu/cm/
PI page @ http://reducio.princeton.edu/cm/ogt

The postdoctoral researcher will contribute to this project using
a combination of evolutionary and comparative genomics, as well as a
diverse set of bioinformatic approaches for data analysis and integration
(e.g., transcriptomics, genomics, phenotypic data). This position offers
a unique opportunity to integrate diverse state-of-the-art genomic and
phenotypic datasets across different model organisms to understand the
role of genes, molecular pathways in the origin of complex diseases.

CINV provides a highly collaborative and multidisciplinary environment
using a variety of computational and experimental approaches,
including genetically tractable animal models as well as expertise in
genetics, behavior, glia-neuron communication, metabolism, biophysics,
genomics, bioinformatics, host-microbe communication, and biomolecular
modelling. The new postdoc will be part of one of our labs which focuses
more generally on the intersection between molecular evolution and
disease biology.

Required qualifications are a PhD in evolutionary biology, computational
biology, bioinformatics, or closely related fields. Candidates must have
excellent verbal and written communication skills (working language
is English), as well as an established record of productivity (e.g.,
at least one previous peer-reviewed publication). Candidates with a
past record of publications in bioinfomatics, computational biology,
population genetics or evolutionary genomics are strongly preferred. Ideal
candidates should have experience in analyzing genomic and phenomic
data, performing comparative evolution or population genomic analyses,
as well as in collaborating with experimentalists.

Interested candidates should first contact Evandro Ferrada at
. Please include the following: (1) a cover
letter addressing your interest in the position and how your expertise
meets the position requirements, (2) a CV, (3) contact information of
at least 2 references. A short online interview will follow to discuss
specific proposals. Candidate materials will be reviewed as soon as
possible until the position is filled.

For further information, please visit:
https://cinv.uv.cl/cinv-postdoctoral-fellowship-program-2026/

Dr. Evandro Ferrada
Associate Profesor

Centro Interdisciplinario de Neurociencia (CINV)

Facultad de Ciencias, Universidad de Valpara�so.

Pasaje Harrington 287, Playa Ancha, Valpara�so, Chile.

Tel. +56 (32) 250 8453

www.cinv.cl

Source:  Igor Ulitsky & Ron Shamir

Address of the bookmark: http://acgt.cs.tau.ac.il/guides/LiteratureGuide.htm

This is a fixed term post for 36 months.

We wish to recruit a highly motivated, postdoctoral scientist to carry out a BBSRC funded project in the laboratory of Dr. Denis Larkin. The project is focused on developing and applying new algorithms to study genome and chromosome evolution in birds, mammals and other vertebrate species using whole-genome sequences and existing algorithms. The post holder will use cutting edge computational and laboratory approaches to generate chromosomal assemblies for sequenced genomes, study chromosomal structures and genome differences between bird and other vertebrate species in attempt to identify species- and clade-specific genome signatures.

Applicants must have a Ph.D. and a track record of success, as indicated by first-author publications in international journals. They must possess excellent organisation skills and be capable of individual initiative and of interacting as part of a team. Applicants with extensive practical experience in bioinformatics or computer science, programming, visualization, handling of large data sets, high-performance computing are encouraged to apply. The post will involve collaboration with a wide range of academic partners both within the UK, EU and worldwide. In addition to leading their own project the post holder will have opportunities to contribute to multiple international genome initiatives.

Experience in programming, bioinformatics and comparative genome analysis is essential. Applicants should have a minimum of a degree and preferably a higher degree in a relevant subject.

The Royal Veterinary College has the largest range of veterinary, para-veterinary and animal science undergraduate and postgraduate courses of any veterinary school in the world and is one of the largest veterinary schools in Europe.

Prospective applicants are encouraged to contact Dr. Denis Larkin, Comparative Biomedical Sciences Department on +442071211906 or email: dlarkin@rvc.ac.uk

We offer a generous reward package.

For further information and to apply on-line please visit our website: www.rvc.ac.uk
Job reference CBS-0025-14A

Closing date: 4 July 2014
Interviews are likely to be held in July 2014

We promote equality of opportunity and diversity within the workplace and welcome applications from all sections of the community.

The C-DAC will launch Param Bio Blaze, a supercomputing facility, to address the challenges in bioinformatics on Tuesday at a three-day symposium, titled: 'Accelerating biology: Computing life'. The supercomputing facility will be inaugurated on Tuesday by Ramakrishna Ramaswamy, vice-chancellor, Central University of Hyderabad at the Yashada. The new C-DAC's facility will have a capacity of 10 teraflop and will be able to analyse human cells and its functions.

Param Bio Blaze will help have a larger storage space and better computing facility for the bioinformatics sector. The facility will help capture the movement of molecules and also interaction between two molecules and the effects.

Applications of Param BioBlaze

- Collaboration with National Centre for Cell Science for research on Malaria and understanding how the disease spreads

- Collaborative work with Tata Memorial hospital on breast cancer and find out the difference between normal tissues and tissues from breast cancer patients

- Designing anti-cancer molecules, a collaborative research with the University of Pune

Reference:

Times of India

Image:datacenterjournal.com

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

Current computational interests:

Systematic analysis of genetic epistasis to identify redundant or compensatory systems and to reveal order of action in genetic pathways.
Using knockout, knockdown, or overexpression, or other perturbation experiments in combinations of genes in S. cerevisiae, C. elegans or mouse.
Using genome-scale genotyping of natural polymorphisms in S. cerevisiae and human populations.
Alternative splicing and its relationship to protein interaction networks.
Integrating large-scale studies including phenotype, genetic epistasis, protein-protein and transcription-regulatory interactions and sequence patterns to quantitatively assign function to genes and guide experimentation.

More at http://llama.mshri.on.ca/index.html

Lab page: http://jarvislab.net/

Basic Galaxy Tutorial

• RNA-Seq tutorial based on Trapnell et al. (2012) Nature Protocols

In this tutorial we cover the concepts of RNA-Seq differential gene expression (DGE) analysis using a very small synthetic dataset from a well studied organism.

Advanced Galaxy Tutorial

• RNA-Seq (Advanced) Tutorial

In this tutorial we compare the performance of three statistically-based differential expression tools:

* CuffDiff

* EdgeR

* DESeq2

Advanced Command Line Tutorial

• Graphical Output with CummeRbund introduces some basic commands using the cummeRbund package of the R programming language

You will need to install R, RStudio and cummeRbund on your PC (explained in the Tutorial). You will learn how to produce graphical output from RNA-Seq analysis previously done using a Cuffdiff analysis.

Variant Detection

Basic Galaxy Tutorial

• Variant Detection tutorial

In this tutorial we cover the concepts of detecting small variants (SNVs and indels) in human genomic DNA using a small set of reads from chromosome 22.

Advanced Galaxy Tutorial

• Variant Detection (Advanced) Tutorial

In this tutorial we compare the performance of three statistically-based variant detection tools:

* SAMtools: Mpileup

* GATK: Unified Genotyper

* FreeBayes

Each of these tools takes as its input a BAM file of aligned reads and generates a list of likely variants in VCF format

Pipelines are for those who are comfortable with using the UNIX command line; and often allow more control over branching and iteration logic.

• WGS/exome GATK-based variant calling pipeline

This is a basic variant-calling and annotation pipeline developed at the Victorian Life Sciences Computation Initiative (VLSCI), University of Melbourne. It is based around BWA, GATK and ENSEMBL and was originally designed for human (or similar) data. The master branch is configured for WGS data; there is an exome branch configured for variant calling in exome data.

To run the pipeline you will need Rubra: https://github.com/bjpop/rubra. Rubra uses the python Ruffus library: http://www.ruffus.org.uk/.

Protocols

• Familial Variant Calling

In this protocol we discuss and outline the process of calling familial related mutations.

• Somatic Variant Calling

In this protocol we discuss and outline the process of identifying somatic variants or mutations.

Assembly

Basic Galaxy Tutorial

• Genome assembly tutorial

In this tutorial we carry out de novo assembly of a microbial genome. We have also written a De novo Genome Assembly for Illumina Data Protocol for a more generic description of the method.

Protocol

• De novo Genome Assembly for Illumina Data

In this protocol we discuss and outline the process of de novo assembly for small to medium sized genomes. Use our Genome assembly tutorial to learn a specific case of using Galaxy to carry out de novo assembly of a microbial genome.

Small RNAs

Basic Galaxy Tutorial

• Quality control for small RNA

This tutorial covers initial steps of the workflow for analysis of short RNA expression such as a quality control of the raw reads, processing of the raw reads for the subsequent analysis and initial quality assessment of the library.

ChIP Seq

Protocol

• ChIP-Seq

In this protocol we discuss ChIP-Seq: a method to analyze the interaction between proteins and DNA.

Amplicons

Protocol

• Amplicon Alignment

In this protocol we discuss and outline the process of aligning custom amplicons using primers for high precision.

Learn Galaxy

Introduction to Galaxy, for those who are very new to Galaxy.

Using Histories and Workflows, for those with some Galaxy knowledge.

The Galaxy project website has many tutorials and screencasts about using Galaxy and the tools, and developing new tools.

Address of the bookmark: https://genome.edu.au/wiki/Learn