Candidate Requirements: A PhD in computer science, computational biology, Bioinformatics, or a related field, along with sufficient programming skills for prototyping. Experience with next generation sequencing data analysis is required. Candidates with MS degree but with relevant work experience can also be considered. The successful candidate must be motivated and capable of working independently as well as in team environment.

Eligible and interested candidates can email your resumes to rohit at strandls dot com

About Strand Life Sciences: Strand was founded in 2000 by computer science and mathematics professors who recognized the need to automate and integrate life science data analysis through an algorithmic and computational approach. Strand’s solutions for life sciences research are robust and easy to use by the most novice user while powerful and configurable for the bioinformatician. Using its award-winning application development platform, AVADIS®, Strand builds innovative products that enable fast and cutting-edge analysis for basic and clinical research, drug discovery and development.

http://www.avadis-ngs.com/careers

Address of the bookmark: https://github.com/andrewgull/MGERT

Current computational interests:

Systematic analysis of genetic epistasis to identify redundant or compensatory systems and to reveal order of action in genetic pathways.
Using knockout, knockdown, or overexpression, or other perturbation experiments in combinations of genes in S. cerevisiae, C. elegans or mouse.
Using genome-scale genotyping of natural polymorphisms in S. cerevisiae and human populations.
Alternative splicing and its relationship to protein interaction networks.
Integrating large-scale studies including phenotype, genetic epistasis, protein-protein and transcription-regulatory interactions and sequence patterns to quantitatively assign function to genes and guide experimentation.

More at http://llama.mshri.on.ca/index.html

Address of the bookmark: https://rpubs.com/Devashish13/PCAGenomics

1) Statistical machine learning methods for the analysis of medical
epigenomics data.

2) Sequence analysis algorithms for detection of RNA-DNA interactions.

Applicants should hold a M.Sc . or PhD in Computer Science or related
areas. Experience in the analysis of biological sequences, gene
expression and gene regulation is desirable. The candidate should have
solid programming skills (C, Python and/or R) and acquaintance with
Linux. Experience with high performance computing is a plus. The
working language of the group is English.

The position is based on the German TV-L 13 salary scale, including
all German social benefits (health insurance and pension scheme). The
expected starting date is September 2014. Interested candidates should
send a CV, statement of research interests and the names of three
references to jobs@costalab.org.

More at http://costalab.org/wp/phd-and-postdoc-position-in-computational-biology/

FIGENO is a
  FIGure
    GENerator
for GENOmics

With figeno, you can plot various types of sequencing data along genomic coordinates. Video overview: https://www.youtube.com/watch?v=h1cBeXoSYTA.

Address of the bookmark: https://github.com/CompEpigen/figeno

2. In some perl script I found this
 . . . . . .
 . . . . . .
# It works for me, only God understood how it is working
while (/(<\/[^>]+>)|(<[^>]+>)|(<[^>]+>)$|([^><]+)/go) {
            $startGene=$1;
            $beginChromosome=$2;
    
. . . . . .
 .. . . . . .
}

3. One more interesting message in Perl found …. It will must tickle you bone :)
open(my $fh, "<", "gene.txt")    or kill " Me if you think this is a mistake :$!";

4. From the Perl

  while () {  # "The Mothership Connection is here!"
    print “$_\n”; # Printing the offspring :)

5. Perl message
if ($1) { print “Just found a the error in chromosome !!!, yahoo…”; else { “That is not error, but mutation you moron!”;

6. One genome database curator walk in wine bar asked the bartender:
CREATE TABLE gene IF NOT EXISTS SexOnTheBeach;

Common uses of the tool include:

• Displaying the sequence and/or genes in a GenBank flat file.
• Highlighting differences and/or similarities in gene content between related organisms.
• Comparing SNPs and indels between closely-related strains or serovars.
• Comparing gene expression values across multiple samples or timepoints.
• Visualizing coverage plots of RNA-Seq read alignments.

Key Features

Circleator...

• Builds on BioPerl and the input file formats that it supports, including:
  • GenBank flat files, GFF, FASTA
• Accepts a number of other commonly-used datatypes and file formats:
  • BSR and TRF output, SAM/BAM files, VCF-encoded SNPs, tab-delimited files
• Outputs publication-ready figures in the SVG (Scalable Vector Graphics) format.
• Requires only a single configuration file whose layout mirrors that of the figure itself.
  • Predefined configuration files and "track" types are supplied for common datasets.
  • Advanced features allow limited analyses to be performed as a figure is drawn.
• Includes an extensive set of regression tests.
• Offers a prototype web-based GUI (under the "Ringmaster" project.)

https://github.com/jonathancrabtree/Circleator

Address of the bookmark: https://github.com/jonathancrabtree/Circleator

Lab page: http://jarvislab.net/

Background

The identification of chromosomal homologous segments (CHS) within and between genomes is essential for comparative genomics. Various processes including insertion/deletion and inversion could cause the degeneration of CHSs.

Address of the bookmark: https://almob.biomedcentral.com/articles/10.1186/1748-7188-4-2