Genomes and genomics:

Bioinformatics and Genomics:

Structural genomics tutorial:

Comparative Genomics Tutorial:

GENOME TUTORIAL:

Tools and resources for identifying protein families, domains and motifs

Bioinformatics Tools 
Tips, Tutorials, and Terminology for Using Selected Resources in Genome Database Guide:

A Web-Based Comparative Genomics Tutorial for Investigating Microbial Genomes:

Free Online Tutorials Teach Anyone How to Use Genome Databases:

Circos to create concise, explanatory, unique and print-ready visualizations of your data:

Genomics and Comparative Genomics Learning Module:

Computational Challenges in Comparative Genomics

A Tutorial:

A Comparative Genomics Resource for Grains:

PLAZA: A Comparative Genomics Resource to Study Gene and Genome Evolution in Plants:

VISTA:

Software for Genomics

1. Artemis Artemis is a free genome viewer and annotation tool that allows visualization of sequence features and the results of analyses within the context of the sequence, and its six-frame translation.
2. Chromas It will display and prints chromatogram files from ABI automated DNA sequencers, and Staden SCF files which the analysis programs for ALF, Li-Cor and Visible Genetics OpenGene sequencers can create.
3. Glimmer A system for finding genes in microbial DNA, especially the genomes of bacteria and archaea.Glimmer (Gene Locator and Interpolated Markov Modeler) uses interpolated Markov models (IMMs) to identify the coding regions and distinguish them from noncoding DN
4. Glimmer HMM A fast and accurate gene finder based on a GHMM architecture, developed specifically for eukaryotes. It incorporates splice site models adapted from the GeneSplicer program and uses interpolated Markov models for evaluating the coding regions.
5. Glimmer M A gene finder derived from Glimmer, but developed specifically for eukaryotes. It is based on a dynamic programming algorithm that considers all combinations of possible exons for inclusion in a gene model and chooses the best of these combinations. The d
6. MUMmer MUMmer is a system for rapidly aligning entire genomes, whether in complete or draft form.
7. pDRAW pDRAW32 is being developed as a free time hobby project. It is far from finished, but as it has reached a point where it could be helpful for many labs, it is now available to the scientific community.
8. Sequin Sequin is a stand-alone software tool developed by the NCBI for submitting and updating entries to the GenBank, EMBL, or DDBJ sequence databases. It is capable of handling simple submissions that contain a single short mRNA sequence, and complex submissio
9. Staden The Staden Package consists of a series of tools for DNA sequence preparation (pregap4), assembly (gap4), editing (gap4) and DNA/protein sequence analysis (spin).

For more software @ http://bioinformaticsonline.com/bookmarks/view/926/list-of-popular-bioinformatics-softwaretools

CABOG is one of many software programs called genome assemblers. These programs exist to overcome the fundamental limitation of all sequencing machines, namely, that they read out very few DNA letters at a time. These programs reconstruct genomes that are billions of letters long from the hundreds of letters per read that modern sequencers provide. What these programs do is often described as a scaled up version of a family solving a jigsaw puzzle.

The CABOG software was the first to accomplish many scientific goals. It was the first to assemble the genome of a multicellular organism (Drosophila melanogaster, 2000). It was the first to assemble both parental haplotypes of one human genome (J. Craig Venter, 2007). It was the first to assemble environmental sequence from the oceans (Sargasso Sea in 2004 and Global Ocean Sampling in 2007). It was first to combine reads from first-generation Sanger sequencing machines and second-generation pyrosequencing machines (Marine microbes, 2006). Today, CABOG is one of the leading assembly programs for data sets that include paired end data from the Roche 454 line of sequencing machines.

Address of the bookmark: http://www.jcvi.org/cms/research/projects/cabog/overview/

Genomics England will play a key role in building on the UK’s long track record as leader in medical science advances to push the boundaries by unlocking the power of DNA data. The UK will become the first ever country to introduce this technology in its mainstream health system – leading the global race for better tests, better drugs and above all better, more personalised care.

http://www.genomicsengland.co.uk/100k-genome-project/

SciGenom Research Foundation (SGRF) and Institute of Genomics and Integrative Biology (IGIB) are pleased to host the Next-Generation Sequencing and Bioinformatics for Genomics & Healthcare conference.

In the ten years since the first human reference genome was completed for US$3 billion the sequencing technologies have radically changed leading to great reduction in sequencing cost. Today a human genome can be sequenced for under US$ 5000 in less than two weeks. It is expected that by the end of 2015 the cost of sequencing a human genome will drop to below thousand dollars. The next generation sequencing technologies over the past five years have enabled a large number of genomic studies that impact human health and disease. Also, this has made possible the growth of microbial, animal and plant genomics studies. While the data production has increased at a rapid pace challenges remain in analyzing and understanding the data. The conference will cover the next generation sequencing (NGS) technologies, bioinformatics for NGS and applications of NGS in many areas including personalized medicine.

For more info : http://www.scigenomconferences.com/2013/default.php

1. Must have basic understanding of molecular biology and Genomics.
2. Experience in application development or must have expertise in programming using either of Perl/Python.
3. Experience in statistical programming using R/Bioconductor/Matlab.
4. Strong concept in statistical and mathematical modelling.
5. Experience in designing and developing the bioinformatics pipeline.
6. Must have minimum 2+ years of hands on experience in NSG data analysis such as RNA-Seq,Exome-Seq ,Chip-Seq and downstream analysis.
7. Knowledge in WGS ,WES, Targeted re-sequencing,GWAS and population genomics will be preferred.
8. Must have experience working on opensource software/Framework and commercial software for NGS data analysis and reporting.
9. Should be aware of handling big data and guiding team members on multiple projects simultaneously.
10. Should have experience coordinating with different groups of clinical research scientist for various project requirements.
11. Ability to work as team as well as independently with minimal support.

More at http://www3.ocimumbio.com/

Candidates must have: a PhD degree in statistics, biostatistics or bioinformatics, extensive experience in analyzing high-dimensional data (microarray, SNP, CNVs) and of validation approaches. In addition, experience in penalized regression methods, data base manipulation; and strong programming skills in order to conduct Monte Carlo studies and applications (R). Candidate must have excellent communication skills (verbal, written and presentation), a strong proficiency in Linux system.

This position is available immediately and will be filled as soon as possible. Appointment could be extended beyond the first year based on additional funding.

For more information about the Department of Biostatistics and Bioinformatics, please visit our website: http://www.biostat.duke.edu.

For more info: http://biostat.duke.edu/sites/biostat.duke.edu/files/Halabi%20-%20Postdoc%20Job%20Posting%202013%20updated.pdf

Duke University is an Equal Opportunity/Affirmative Action Employer.

RASA offers faster, better and cost effective cutting edge technology solutions to chemical and life science research and industry. We provide our customers with A seamless model of wide expertise and comprehensive platforms. Our Value is to take our customers

The postdocs will join an international group and network of researchers at the University of Vienna studying a diverse range of species and questions in molecular evolution, development, morphology and genomics. Our group is also part of the large evolVienna network of more than 50 evolutionary biology labs in Vienna, across several universities and research institutes. Our Faculty will be relocating to a new campus at the Vienna Biocenter in summer 2021 (https://biologiezentrum.univie.ac.at/en/). Vienna is a vibrant historic European capital with a high QOL. Information about postdoctoral salaries in Austria can be found on this webpage: https://www.fwf.ac.at/en/research-funding/personnel-costs/

Earliest start date will be after July 2021. Initial term of employment is for two years with the possibility of extension. Remote working, at least initially, is a possibility.

Requirements:
- PhD degree or equivalent by the start date
- Publishing record in peer-reviewed journals or evidence thereof
- At least 2 letters of support

Applications including a letter of motivation should be submitted via the Job Center to the University of Vienna (https://personalwesen.univie.ac.at/en/jobs-recruiting/job-center/,
job reference number 11615).

Application deadline: January 15th 2021.
Application link: https://univis.univie.ac.at/ebewerbung

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/

More at http://pandeylab.igm.jhmi.edu/

http://scholar.google.com/citations?user=OhuG0FcAAAAJ&hl=en