BOL: Related items

Understanding PacBio

Jitendra Narayan — Fri, 24 Feb 2017 10:17:36 -0600

This tutorial includes resources for learning more about PacBio data and bioinformatics analysis, and includes content suitable for both beginners and experts. Below are links to training modules (webinars and PowerPoint presentations) to help you get started with your data processing, as well as information for specialized applications.

Training Resources:

Specialized Applications:

Address of the bookmark: https://github.com/PacificBiosciences/Bioinformatics-Training/wiki

sockeye

Jit — Fri, 17 Feb 2017 08:51:16 -0600

This sockeye software uses the Ensembl database project to import sequence and annotation information from several eukaryotic species. A user can additionally import their own custom sequence and annotation data. Individual annotation objects are displayed in Sockeye by using custom 3D models. Ensembl-derived and imported sequences can be analyzed by using a suite of multiple and pair-wise alignment algorithms. The results of these comparative analyses are also displayed in the 3D environment of Sockeye. By using the Java3D API to visualize genomic data in a 3D environment, we are able to compactly display cross-sequence comparisons. This provides the user with a novel platform for visualizing and comparing genomic feature organization.

Address of the bookmark: http://www.bcgsc.ca/platform/bioinfo/software/sockeye/releases/1.3

Multi-metagenome assembly

Radha Agarkar — Fri, 03 Mar 2017 10:14:18 -0600

This project contains scripts and tutorials on how to assemble individual microbial genomes from metagenomes, as described in:

Genome sequences of rare, uncultured bacteria obtained by differential coverage binning of multiple metagenomes

Mads Albertsen, Philip Hugenholtz, Adam Skarshewski, Gene W. Tyson, Kåre L. Nielsen and Per .H. Nielsen

Nature Biotechnology 2013, doi: 10.1038/nbt.2579

Address of the bookmark: https://github.com/MadsAlbertsen/multi-metagenome

COCACOLA (binning metagenomic contigs using sequence COmposition, read CoverAge, CO-alignment, and paired-end read LinkAge)

Jit — Tue, 07 Mar 2017 08:50:57 -0600

COCACOLA is a general framework that combines different types of information: sequence COmposition, CoverAge across multiple samples, CO-alignment to reference genomes and paired-end reads LinkAge to automatically bin contigs into OTUs. Furthermore, COCACOLA seamlessly embraces customized prior knowledge to facilitate binning accuracy.

News: Python version of COCACOLA is available now!

Address of the bookmark: https://github.com/younglululu/COCACOLA

Selecting between Python 2 and Python 3?

Rahul Agarwal — Wed, 10 Jul 2013 16:30:58 -0500

Which version is best for bioinformatician to work on?

Research Fellow

Sat, 13 Jul 2013 11:23:20 -0500

UNIVERSITY OF CALCUTTA

A walk-in-interview will be held on 15.7.2013 at 12 noon in the Department of Biophysics, Molecular Biology and Bioinformatics, 92 A.P.C Road, Kolkata-700 009 to select one trainee research fellow and two students under DIC. The positions are purely temporary and would be for a period of six months from the date of joining which may be extended by another six months subject to successful performance.

Qualification:

For the Trainee Research Fellow: Should have a master degree in Bioinformatics or allied subjects and should have biological database development experience. Must have at least one publication.

For the Students: Should have a master degree in Bioinformatics or allied subjects and should be proficient in C-programming language. Must be familiar with techniques of Developmental Biology.

The Trainee Research Fellow would be paid a consolidated sum of Rs 10000/- per month and the students would be paid a sum amount Rs. 7000/- per month during the tenure of the project.

Advertisement:
www.caluniv.ac.in/News%20&%20Announcement/trainee_rf_DIC.pdf

Structural polymorphism analysis from NGS data

Sat, 13 Jul 2013 17:12:47 -0500

The LabEx BASC (Biodiversity, Agroecosystems, Society, Climate), a network of 13 laboratories of the Paris-Saclay Scientific Cluster, is seeking a bioinformatician to analyze Next Generation Sequencing (NGS) data analysis. In the context of a flagship project aiming at understanding and improving the adaptive capacity of agroecosystems it will be critical to establish a link between sequence variation, functional variation, gene/protein expression and phenotypic adaptation.

The successful candidate will be in charge of the detection of polymorphisms including structural variants, of the comparison of multiple and diverse genomes of a same species and of the construction of pan- and core-genomes. These challenging tasks will require bioinformatics developments and implementation of methods for accommodating the high level of repetitiveness of complex genomes. The tools will be integrated into pipelines and made available to end-users through the Galaxy platform. The bioinformatician will therefore also have to provide researchers with advices on their experimental designs in order to ensure compliance of produced datasets with pipelines requirements. He/she will be hosted by a bioinformatics/informatics team (7 people) (http://moulon.inra.fr/index.php/fr/equipestransversales/atelier-de-bioinformatique) which has computational facilities and expertise in NGS data analysis, and will benefit as well from national and international collaborative networks (Aplibio http://www.renabi.fr/platforms/aplibio/, Transplant http://transplantdb.eu, AMAIZING http://www.amaizing.fr/).

The position requires a doctoral degree (PhD) in bioinformatics with strong expertise in script writing (Python/Perl) and pipeline development.

Applicants should send a CV and the names of 2 referees willing to provide a letter of recommendation to joets@moulon.inra.fr.

JSON

Abhimanyu Singh — Tue, 04 Apr 2017 08:02:39 -0500

JSON (JavaScript Object Notation) is a lightweight data-interchange format. It is easy for humans to read and write. It is easy for machines to parse and generate. It is based on a subset of the JavaScript Programming Language, Standard ECMA-262 3rd Edition - December 1999. JSON is a text format that is completely language independent but uses conventions that are familiar to programmers of the C-family of languages, including C, C++, C#, Java, JavaScript, Perl, Python, and many others. These properties make JSON an ideal data-interchange language.

JSON is built on two structures:

A collection of name/value pairs. In various languages, this is realized as an object, record, struct, dictionary, hash table, keyed list, or associative array.
An ordered list of values. In most languages, this is realized as an array, vector, list, or sequence.

These are universal data structures. Virtually all modern programming languages support them in one form or another. It makes sense that a data format that is interchangeable with programming languages also be based on these structures.

Address of the bookmark: http://json.org/

Dumontier Lab

Sun, 14 Jul 2013 12:51:42 -0500

Our research aims to better understand how living systems respond to chemical agents. A key aspect of our approach involves using computational frameworks that are powered by formal (i.e. machine understandable) semantics to make effectively use of vast and diverse amounts of biomedical knowledge. We are particularly interested in understanding how the response to chemical exposure is modulated by genetic and physiological variation among individuals and how this translates into altered capabilities at the molecular level.

Research Area

the discovery and on-demand use of biomedical data and services
the formulation, discovery and evaluation of scientific hypotheses
the simulation of biological systems at the level of individual molecules

Link @ http://dumontierlab.com/

Lifemap

Jit — Mon, 10 Apr 2017 05:42:37 -0500

Lifemap is an interactive tool to explore the WHOLE NCBI TAXONOMY. The concept used in Lifemap is similar to the one used in cartography with tools like Google Maps© or Open Street Maps: exploring is done by zooming and panning.

The current tree contains ALL species present in NCBI taxonomy as of October 18th, 2016: 1,135,169 species including 10,545 Archaea, 418,777 Bacteria and 705,847 Eukaryotes. The Lifemap tree is updated every two weeks.

All the nodes in the tree are clickable. This displays various information and options:

The species name (and the associated common name if there is one)
The rank (kingdom, family, class, species...)
Ability to go to the corresponding node/species on NCBI web site (displayed in a new window)
Possibility to download the corresponding subtree in newick extended format
Possibilty to get the whole lineage from the current node/tip to the root of the tree.

Address of the bookmark: http://lifemap-ncbi.univ-lyon1.fr/