https://academic.oup.com/nar/article/47/11/e63/5377471

Address of the bookmark: https://github.com/linzhi2013/MitoZ

Date: Nov 11th. 2016 Last Date: Nov 25th. 2016

PROJECT ID: 632

The following posts are urgently required to be filled for the Department of Biotechnology, Government of India funded project entitled "Computational Core for Plant Metabolomics" administrated by Prof Indira Ghosh, School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi-110 067

NB:For all Bioinformatics posts, preference will be given to candidates with a good knowledge of Python and/or R. Knowledge of JAVA will also get a special consideration.

RA / Research Associate (Metabolic engineering/Computational Biologist)

Salary: Rs. 36000/- + HRA
Vacancy: 1
Essential Qualifications: PhD in Bioinformatics /Mathematics/Computer Science with experience in analyzing high throughput omics-based data/ system Biology/ Analysis of Network Biology. Published paper in the field is a must to prove the experience.
Desired Skills: Prior experience in handling and guiding bioinformatics, metabolomics data, planning of new research area in metabolic driven network , managing the project portal, preparing and filing reports etc. Will be expected to communicate with user groups and coordinate with LIMS group in Hyderabad and the Cheminformatics group in Delhi.

RA / Research Associate (Chemo-informatics/Computational Biologist)

Salary: Rs. 36000/- + HRA
Vacancy: 1
Essential Qualifications: PhD in Bioinformatics/ computational biology/ Biophysics/Computer Science. Computational and Chemical structure related experience is a necessary qualification proven by paper published and program developed.
Desired Skills: Research experience in Chemical scaffold mapping, in silico Spectral analysis, Biological Database Designing & Integration is required. Individual is responsible to develop methods related to metabolite identification, Testing and refining and integrate LIMS with IIIT Hyderabad and will be expected to communicate with user groups.

Project SRF (Bioinformatics/Programming)

Salary: As per DBT rules
Vacancy: 1
Essential Qualifications: Masters/B Tech in Basic Sciences with at least 2yrs of research experience in Bioinformatics/Computational Biology related to Database /portal building & maintenance ,high throughput data handling and analysis etc. For M.Sc/B.Tec, Published paper in peer-reviewed Journal and for M.Tech, thesis submission in computational biology is a must.

More at http://www.jnu.ac.in/Career/currentjobs.htm

Careful encoding of graph entities allows odgi to efficiently compute and transform pangenomes with minimal overheads. odgi implements a dynamic data structure that leveraged multi-core CPUs and can be updated on the fly.

The edges and path steps are recorded as deltas between the current node id and the target node id, where the node id corresponds to the rank in the global array of nodes. Graphs built from biological data sets tend to have local partial order and, when sorted, the deltas be small. This allows them to be compressed with a variable length integer representation, resulting in a small in-memory footprint at the cost of packing and unpacking.

The RAM and computational savings are substantial. In partially ordered regions of the graph, most deltas will require only a single byte.

Address of the bookmark: https://github.com/pangenome/odgi

GoJS offers many advanced features for user interactivity such as drag-and-drop, copy-and-paste, in-place text editing, tooltips, context menus, automatic layouts, templates, data binding and models, transactional state and undo management, palettes, overviews, event handlers, commands, and an extensible tool system for custom operations.

GoJS is pure JavaScript, so users get interactivity without requiring round-trips to servers and without plugins. GoJS normally runs completely in the browser, rendering to an HTML5 Canvas element or SVG without any server-side requirements. GoJS does not depend on any JavaScript libraries or frameworks, so it should work with any HTML or JavaScript framework or with no framework at all.          

More at http://gojs.net/latest/index.html

Address of the bookmark: http://gojs.net/latest/index.html

• AssemblyMapper : reference-guided genome assembly
• GapFiller : long-reads based gap filling
• TeloExplorer : telomere identification
• CentroMiner : centromere candidate prediction

https://academic.oup.com/hr/article/10/8/uhad127/7197191?login=false 

Address of the bookmark: http://www.atcgn.com:8080/quarTeT/home.html

Availability: Genomicus is freely available for online use at http://www.dyogen.ens.fr/genomicus while data can be downloaded at ftp://ftp.biologie.ens.fr/pub/dyogen/genomicus

Contact: rf.sne.eigoloib@crh

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2853686/

The MEME Suite allows the biologist to discover novel motifs in collections of unaligned nucleotide or protein sequences, and to perform a wide variety of other motif-based analyses.

The MEME Suite supports motif-based analysis of DNA, RNA and protein sequences. It provides motif discovery algorithms using both probabilistic (MEME) and discrete models (MEME), which have complementary strengths. It also allows discovery of motifs with arbitrary insertions and deletions (GLAM2). In addition to motif discovery, the MEME Suite provides tools for scanning sequences for matches to motifs (FIMO, MAST and GLAM2Scan), scanning for clusters of motifs (MCAST), comparing motifs to known motifs (Tomtom), finding preferred spacings between motifs (SpaMo), predicting the biological roles of motifs (GOMo), measuring the positional enrichment of sequences for known motifs (CentriMo), and analyzing ChIP-seq and other large datasets (MEME-ChIP).

The MEME Suite is comprised of a collection of tools that work together, as shown below. Not all the tools are available as webservices, so to get the full power of the MEME Suite you will need to download and install a local copy of the software. To see what has changed recently you can peruse the release notes.

http://meme-suite.org/

Address of the bookmark: http://meme-suite.org/

Address of the bookmark: https://hpcugent.github.io/easybuild/

Pondicherry University, Puducherry has been identified as a nodal agency by the Department of Biotechnology, Govt. of India to coordinate this examination along with nine centres namely,

Pune University, Pune;

Anna University, Chennai;

Bose Institute, Kolkata;

Institute of Bioinformatics & Applied Biotechnology, Bangalore;

North-Eastern Hill University, Shillong, University of Hyderabad, Hyderabad;

University of Kerala, Thiruvananthapuram;

Jawaharlal Nehru University, New Delhi and

Assam Agricultural University, Guwahati. 

In the BINC 2015 and 2016 examination, 23 candidates and five candidates were certified respectively. DBT has agreed to fund Research fellowships for all the BINC qualified Indian nationals to pursue Ph.D. in Indian Institutes/Universities.

Note that the candidate must possess a postgraduate degree(or equivalent) & meet the criteria of the institutes/universities in order to avail research fellowship.

In addition, cash prize of Rs. 10,000/- will be awarded to the top 10 BINC qualifiers.

More at http://www.pondiuni.edu.in/exams/binc/

FSA brings the high accuracies previously available only for small-scale analyses of proteins or RNAs to large-scale problems such as aligning thousands of sequences or megabase-long sequences. FSA introduces several novel methods for constructing better alignments:

• FSA uses machine-learning techniques to estimate gap and substitution parameters on the fly for each set of input sequences. This "query-specific learning" alignment method makes FSA very robust: it can produce superior alignments of sets of homologous sequences which are subject to very different evolutionary constraints.
• FSA is capable of aligning hundreds or even thousands of sequences using a randomized inference algorithm to reduce the computational cost of multiple alignment. This randomized inference can be over ten times faster than a direct approach with little loss of accuracy.
• FSA can quickly align very long sequences using the "anchor annealing" technique for resolving anchors and projecting them with transitive anchoring. It then stitches together the alignment between the anchors using the methods described above.
• The included GUI, MAD (Multiple Alignment Display), can display the intermediate alignments produced by FSA, where each character is colored according to the probability that it is correctly aligned (see the picture and movie at the top of the page).

You can see more information on the FAQ. 

Address of the bookmark: http://fsa.sourceforge.net/