1 Asst. Professor (on Pre-Ph.D. Contract)

2 Asst. Professor (on Contract)

3 Asst. Professor

4 Associate Professor

5 Professor

Life Sciences:-

i)Biochemistry and Molecular Biology; ii)Cell and Developmental Biology; iii)Immunology and Molecular Medicine; (iv) Microbiology and Ecology (v)Bioinformatics Group; vi)Biophysical Sciences

HOW TO APPLY:-

a. Candidates willing to apply for one or more posts are requested to apply online at “http://www.nitrkl.ac.in/ JOBS & TENDERS /Faculty Position” .
b. Persons employed in Government and Semi-Government organizations may apply directly against the standing advertisement. For this the application should be completed online. The printout of the application generated online should be submitted through employer if shortlisted for interview.
c. The online application can be filled in multiple sessions.
d. Candidates are required to check the Institute website from time to time for latest information, application status call for interview, change of dates and final results.
e. Applications shall be received online only. Please do not send application or CV against this advertisement by email or letter mail.

More Info: http://nitrkl.ac.in/Jobs_Tenders/1FacultyPosition/Default.aspx

Address of the bookmark: http://pevsnerlab.kennedykrieger.org/php/?q=software

• hist: Create an histogram of k-mer occurrences from a sequence file. Adds metadata in output for easy plotting.
• gcp: K-mer GC Processor. Creates a matrix of the number of K-mers found given a GC count and a K-mer count.
• comp: K-mer comparison tool. Creates a matrix of shared K-mers between two (or three) sequence files or hashes.
• sect: SEquence Coverage estimator Tool. Estimates the coverage of each sequence in a file using K-mers from another sequence file.
• blob: Given, reads and an assembly, calculates both the read and assembly K-mer coverage along with GC% for each sequence in the assembly.SEquence Coverage estimator Tool.
• filter: Filtering tools. Contains tools for filtering k-mer hashes and FastQ/A files:
  • kmer: Produces a k-mer hash containing only k-mers within specified coverage and GC tolerances.
  • seq: Filters a sequence file based on whether or not the sequences contain k-mers within a provided hash.
• plot: Plotting tools. Contains several plotting tools to visualise K-mer and compare distributions. The following plot tools are available:
  • density: Creates a density plot from a matrix created with the "comp" tool. Typically this is used to compare two K-mer hashes produced by different NGS reads.
  • profile: Creates a K-mer coverage plot for a single sequence. Takes in fasta coverage output coverage from the "sect" tool
  • spectra-cn: Creates a stacked histogram using a matrix created with the "comp" tool. Typically this is used to compare a jellyfish hash produced from a read set to a jellyfish hash produced from an assembly. The plot shows the amount of distinct K-mers absent, as well as the copy number variation present within the assembly.
  • spectra-hist: Creates a K-mer spectra plot for a set of K-mer histograms produced either by jellyfish-histo or kat-histo.
  • spectra-mx: Creates a K-mer spectra plot for a set of K-mer histograms that are derived from selected rows or columns in a matrix produced by the "comp".

In addition, KAT contains a python script for analysing the mathematical distributions present in the K-mer spectra in order to determine how much content is present in each peak.

This README only contains some brief details of how to install and use KAT. For more extensive documentation please visit: https://kat.readthedocs.org/en/latest/

https://academic.oup.com/bioinformatics/article/33/4/574/2664339 

Address of the bookmark: https://github.com/TGAC/KAT

Name of the Post: Project Fellow

No. of the Post: 02 Two

Salary: Rs. 12000/- per month or Rs. 14000/- per month

Age Limit: Max. 28 years as on 10.06.2015 and relaxation as per rules

Required Job Profile:

Candidate must possess first class B.Tech. in bioinformatics or computational biology OR M.Sc. in bioinformatics or computational biology with fifty five percent marks OR M.Tech. in bioinformatics or computational biology with fifty five percent marks.

How to apply:

Eligible and interested candidates should need to appear for walk-in interview on 10.06.2015 at 9:00 am at the above mentioned address.

Refer to http://www.ihbt.res.in/recruit/AdvtNo7_2015.pdf

minimap -t 24 assembly.fasta long_reads.fastq.gz | racon -t 24 long_reads.fastq.gz - assembly.fasta racon_assembly.fasta
nucmer -p nucmer assembly.fasta racon_assembly.fasta
show-snps -C -T -r nucmer.delta

This reports Racon's changes in a table. You can exclude indels with the -I option in show-snps. 

This process (Racon -> MUMmer -> SNP table) solves the problem I originally raised in this issue. So as far as I'm concerned, you can close this issue (or keep it open if you still want to implement some kind of variant table).

Source code, executables and the testing dataset are freely available at https://github.com/mapleforest/HaploMerger2/releases/.

Address of the bookmark: https://github.com/mapleforest/HaploMerger2/releases/

Applications are invited for pre-selection of candidates for Ministry of Science and Technology, Department of Science and Technology INSPIRE Faculty Scheme: a component of “Assured Opportunity for Research Career (AORC)” under INSPIRE in the area of computational Biology/Systems Biology/Bioinformatics.

Candidates having done their B.Tech/B.E. and or M.Sc./M.Tech in Computer Science or Biotechnology and Ph.D. in Systems/ Computational Biology or Bioinformatics may apply in the following format prescribed by DST to the Director, Cluster Innovation Center, University Stadium, GC Narang Marg, University of Delhi, Delhi -11107. Detials of other qualification, age limits etc., please visit www.inspire-dst.gov.in.

Application on the prescribed format may be submitted by email to director@cic.du.ac.in before October 25, 2014. Selected candidates shall be called for an interview. The date, time and venue of the interview shall be informed by email/telephone. For more information about Cluster Innovation Center, please visit https://ducic.ac.in.

AVAILABILITY AND IMPLEMENTATION:

http://cab.spbu.ru/software/quast-lg

Address of the bookmark: http://cab.spbu.ru/software/quast-lg/

These notebooks are normal files that can be shared with colleagues, converted to other formats such as HTML or PDF, etc. You can share any publicly available notebook by using the IPython Notebook Viewer service which will render it as a static web page. This makes it easy to give your colleagues a document they can read immediately without having to install anything.

To learn more about using the IPython Notebook, you can visit our example collection, and you can read the documentation for all the details on how to use and configure the system. The Notebook Gallery showcases many interesting notebooks covering a variety of topics, from basic programming to advanced scientific computing.

More http://www.nature.com/news/interactive-notebooks-sharing-the-code-1.16261

http://ipython.org/ipython-doc/1/interactive/notebook.html

Reference http://ipython.org/notebook.html