BOL: Related items

The Institute for Molecular Bioscience (IMB), Bailey Lab

Sun, 14 Jul 2013 11:53:08 -0500

Pattern recognition and computational biology

MEME Suite software development; gene expression; mathematical modelling; gene regulation and transcription

Specialization:
Pattern recognition and modelling in computational biology

Link @ http://www.imb.uq.edu.au/tim-bailey

Tetra-Nucleotide Analysis

Jit — Thu, 04 May 2017 05:07:41 -0500

A tetra-nucleotide is a fragment of DNA sequence with 4 bases (e.g. AGTC or TTGG). Pride et al. (2003) showed that the frequency of tetra-nucleotides in bacterial genomes contain useful, albeit weak, phylogenetic signals. Even though tetra-nucleotide analysis (TNA) utilizes the information of whole genome, it is evident that it cannot replace other alignment-based phylogenetic methods such as OrthoANI or 16S rRNA phylogeny. However, TNA can be useful for phylogenetic characterization when whole genome or 16S rRNA gene information is not available. For example, a partial genomic fragment obtained from a metagenome can be identified by TNA (Teeling et al., 2004). TNA is also fast enough that it can be used as a search engine against a large genome database.

Address of the bookmark: https://chunlab.wordpress.com/tetra-nucleotide-analysis/

The Centre for Bioinformatics, Biomarker Discovery and Information-Based Medicine (CIBM)

Sun, 14 Jul 2013 12:31:38 -0500

The Centre for Bioinformatics, Biomarker Discovery and Information-Based Medicine (CIBM) is committed to shortening the process of obtaining novel discoveries to achieve distinctively better outcomes in clinical practice and translational individualised medicine.

Link @ http://www.newcastle.edu.au/research-and-innovation/centre/cibm/about-us

Bioinformatician at 23andMe

Sat, 06 May 2017 17:57:39 -0500

23andMe’s mission is to help people access, understand, and benefit
from the human genome. We are a group of passionate individuals excited
to push the boundaries of what’s possible to help turn genetic insight
into better health and personal understanding.

Our Research Team prides itself on driving cutting edge, industrial-scale
science to make an impact that belies the team’s size, in an environment
and culture that fosters creativity, innovation, collaboration, and fun.

More than 80% of our customers consent to participate in research, and as
a result of their participation, we have one of the largest recontactable,
genotyped, and phenotyped research cohorts in the world. The scope and
breadth of our vision means that most of the methods and tools necessary
to unlock the potential of this unique resource for discovery have yet
to be developed.

Our science has garnered the respect of many members of the
broader scientific community. For a list of our publications, see
www.23andme.com/publications/for-scientists/.

Join us! Visit our Careers page (www.23andMe.com/careers) to learn more
about these open positions:

• Scientist, Research Communications
• Bioinformaticist
• Computational Biologist, Ancestry R&D
• Scientist/Senior Scientist, Statistical Genetics
• Scientist/Senior Scientist, Survey Methodology
• Scientist/Senior Scientist, Health R&D
• Senior Computational Biologist
• Biostatistician

pfontanillas@23andme.com

BioRuby :Ruby packages for biologist

Jitendra Narayan — Mon, 15 Jul 2013 01:36:28 -0500

BioRuby is a package of Open Source Ruby code, with classes for DNA and protein sequence analysis, alignment, database parsing, and other Bioinformatics tools.
BioRuby project provides an integrated environment in bioinformatics for the Ruby language. This project is supported by University of Tokyo (Human Genome Center), Kyoto University(Bioinformatics Center) and the Open Bio Foundation. The project was supported by Information-technology Promotion Agency (IPA) as an Exploratory Software Project in 2005
RubyForge is a home for open source Ruby projects: RubyForge is a home for open source Ruby projects. BioRuby project was started in late 2000, and is still in progress. Currently, there are over 80 files and 15,000 lines (except comment-only lines) in our source code. This might be equivalent to twice or more lines of other languages because of Ruby's extremely high descriptive power.

Classes for
Multiple alignment (Bio::Alignment),
Gene Ontology(Bio::GO),
PDB (Bio::PDB),
FANTOM database(Bio::FANTOM),
GFF (Bio::GFF) and KEGG
Orthology (Bio::KEGG::KO).

They also added support for many applications such as PSORT, SOSUI, TargetP, TMHMM, GenScan, ClustalW, MAFFT, and KEGG API.

Wiki Links
http://bioruby.open-bio.org/wiki/BioRubyOnRails
http://dev.bioruby.org/en/

BioRuby in Anger
http://dev.bioruby.org/en/?BioRuby+in+Anger

BioRuby RDocs
http://bioruby.org/rdoc/

BioRuby Tutorial Website
http://dev.bioruby.org/en/?Tutorial.rd

Why BioRuby Hub for BioRuby
http://www.linuxjournal.com/article/5915

Social Coding Hub for BioRuby
http://www.linuxjournal.com/article/5915

Bioinformatics on Rails: BioRuby Tutorial
http://bioinforuby.blogspot.com/2008/02/bioruby-tutorial.html

RRA BioRuby
http://raa.ruby-lang.org/project/bioruby/

BioRuby Project Discussion Group
http://portal.open-bio.org/mailman/listinfo/bioruby

BioRuby related Projects: Project tree
http://rubyforge.org/softwaremap/trove_list.php?form_cat=252

Reference
http://www.jsbi.org/journal/GIW03/GIW03P191.pdf

CABOG: Celera Assembler with Best Overlap Graph

Abhimanyu Singh — Mon, 15 May 2017 05:04:39 -0500

CABOG (Celera Assembler with Best Overlap Graph) is scientific software for DNA research. CABOG has been a critical component of many genome sequencing projects. CABOG operates on small genomes such as bacterial as well as large genomes such as mammalian. CABOG is an extension of the Celera Assembler software that was originally developed at Celera for the 2001 publication of the first draft human genome sequence. The software was released to the public domain in 2004. Its open source repository on Source Forge is an internet resource for scientists around the world.

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/

Postdoctoral position in bioinformatics @ Sweden

Sun, 14 Jul 2013 13:49:57 -0500

Information about the department
The Department of Mathematical Sciences at Chalmers University of Technology and the University of Gothenburg has about 170 faculty and staff and is the largest department of mathematical sciences in the Nordic countries. The department belongs to both Chalmers University of Technology and the University of Gothenburg (for more information see http://www.chalmers.se/math/).

Job description
We are looking for a motivated, self-driven post-doctoral researcher to work with large-scale sequence data analysis. The position is for 24 months and located at Mathematical Statistics, Department of Mathematical Sciences in Erik Kristiansson’s research group. We are focused on methods development for and analysis of next generation DNA sequencing, in particular comparative metagenomics and gene expression analysis (RNA-seq). We have strong interdisciplinary profile and are actively collaborating with several experimental groups, especially within the environmental sciences, ecology, infectious diseases and cancer genomics. More information is available at http://bioinformatics.math.chalmers.se.

The Post-doctoral position is an appointment that offers an opportunity to qualify for further research positions within academia or industry. The majority of your working time is devoted to your own research, normally as a member of a research group. Included in your work is also to take part in supervision of Ph.D. students and M.Sc thesis students. Teaching of undergraduate students may also be included to a small extent.

The employment is limited to a maximum of 2 years (1+1).

Qualifications
The applicant should have Ph.D. degree preferably in bioinformatics, mathematics, statistics, computer science or equivalent by the start of the appointment. Experience from analysis of large-scale data, in particular from next generation DNA sequencing, is highly valued. The applicant should also be proficient in programming (e.g. Python/Java/C) and comfortable with Unix/Linux systems. Interaction with experimental biologists is central and good collaborative skills are therefore important. Fluency in written and spoken English is a strong requirement. As a post-doctoral researcher you are expected to work independently and to be able to supervise/co-supervise PhD and Master’s students.

Application procedure
The application should be marked with Ref 20130126 and written in English. The application should be sent electronically via Chalmers webpage.

Application deadline: September 8, 2013.

For questions, please contact:
Ass prof. Erik Kristiansson, Matematiska Vetenskaper, erik.kristiansson@chalmers.se, +46 31-772 3521, +46 70-5259751.

Chalmers continuously strive to be an attractive employer. Equality and diversity are substantial foundations in all activities at Chalmers.

NCBI Prokaryotic Genome Annotation Pipeline

Jit — Tue, 16 May 2017 08:56:03 -0500

NCBI Prokaryotic Genome Annotation Pipeline is designed to annotate bacterial and archaeal genomes (chromosomes and plasmids).

Genome annotation is a multi-level process that includes prediction of protein-coding genes, as well as other functional genome units such as structural RNAs, tRNAs, small RNAs, pseudogenes, control regions, direct and inverted repeats, insertion sequences, transposons and other mobile elements.

NCBI has developed an automatic prokaryotic genome annotation pipeline that combines ab initio gene prediction algorithms with homology based methods. The first version of NCBI Prokaryotic Genome Automatic Annotation Pipeline (PGAAP; see Pubmed Article) developed in 2005 has been replaced with an upgraded version that is capable of processing a larger data volume. You can find a more detailed description of the new version of the pipeline in NCBI Handbook chapter. NCBI's annotation pipeline depends on several internal databases and is not currently available for download or use outside of the NCBI environment.

https://www.ncbi.nlm.nih.gov/genome/annotation_prok/

Address of the bookmark: https://www.ncbi.nlm.nih.gov/genome/annotation_prok/

STUDENTSHIP and TRAINEESHIP @ University of Madras

Sat, 16 Nov 2013 19:27:40 -0600

Bioinformatics Infrastructure Facility
University of Madras
Chennai 600 025

Applications are invited for the STUDENTSHIP and TRAINEESHIP vacancies to carry out project/research work in the DBT - Bioinformatics Infrastructure Facility with consolidated stipend of Rs.5,000/- per month.

Essential Qualification

Student Trainee: Those who have completed M.Sc., Bioinformatics/Biophysics/Life sciences or Pursuing M.Tech., Bioinformatics/Biotechnology

Duration : 3-4 Months

Student Trainee: Those who are pursuing M.Sc Bioinformatics/Biophysics/ Life sciences/others

Duration : 2-3 Months

Mail your CV on or before 25th November 2013 to shirai2011@gmail.com and hard copy to "Dr. D. Velmurugan, Professor & Head, CAS in Crystallography and Biophysics, University of Madras, Guindy Campus, Chennai 600 025". Also, the applicants are requested to attend the interview on 29th November, 2013 at 11 A.M.

www.unom.ac.in/uploads/announcements/bifadvertisement_20131114080003_23240.pdf

Senior Bioinformatics Software Developer, Hyderabad, Telangana

Mon, 03 Jul 2017 10:10:31 -0500

DuPont Pioneer is the world leader in plant biotechnology area including discovery, development and delivery of elite crop genetics. DuPont Pioneer is aggressively building Big Data and Predictive Analytics capabilities in order to deliver improved services to our customers. We are currently seeking Senior Bioinformatics Software Developer at the DuPont Knowledge Center in Hyderabad, India for our global Data Science and Informatics group. At DuPont Pioneer, you’ll become part of a work environment that nurtures your interests, ignites your passion, creates opportunities to serve and helps you attain success–both personally and professionally. The hiring level will be commensurate with the level of experience. This is a critical position with the potential to make immediate, significant impact on our business.
The successful candidate will have an extensive background in computer science and bioinformatics through courses or academic degrees, and proven experience in bioinformatics software development. We are looking for those creative, smart, model driven, agile individuals who enjoy giving their all to tackle diverse software needs.
Duties / Responsibilities

Job Qualifications
Education and Experience
• Master Degree in Bioinformatics, Computational biology, Scientific Computing or related field
• 3-5 years of Post-Master’s experience in Bioinformatics software development
• Proven experience developing high throughput bioinformatics applications
Required Competencies
• Strong proven experience in Python programming language in Linux environment
• Proven High Performance computing experience (LSF/SGE/OGE)
• Exposure in code versioning and repository management (GIT/SVN)
• Proven experience in Bioinformatics algorithm development
• Deep understanding in Bioinformatics tools, data types
Desired Competencies
• Familiarity working in a scientific computing environment (NumPy, SciPy, Pandas etc.)
• Familiarity working with Cloud technologies (AWS, Azure)
• Ability to demonstrate solid analytical skills and exceptional attention to detail.
• Experience in relational databases and data structures
• Proven experience working with teams using agile software development methodologies and processes
• Familiarity with Service Oriented Architecture (SOA)
• Familiarity with build tools (Jenkins, make, ANT, Maven)
• Exposure to project management tools (JIRA, Confluence, RED MINE, etc.)

More at http://careers.dupont.com/jobsearch/job-details/senior-bioinformatics-software-developer/012939W-01/