http://www.thestreet.com/story/13151062/1/affymetrix-acquires-assets-of-eureka-genomics-corporation-to-provide-high-throughput-and-economical-crop-and-animal-genotyping.html

#Find all occurrences of a pattern in a string.
#Given: Strings Pattern and Genome.
#Return: All starting positions in Genome where Pattern appears as a substring. Use 0-based indexing.

use strict;
use warnings;

my $string="GATATATGCATATACTT";
my $subStr="ATAT";
my $kmer=length($subStr);

kmerMatch ($string, $subStr, $kmer);

sub kmerMatch { #Check the exact matching kmers with sliding window
my ($string, $myStr, $kmer)=@_;
for (my $aa=0; $aa<=(length($string)-$kmer); $aa++) {
    my $myWin=substr  $string, $aa,$kmer;
    if ($myWin eq $myStr) {
        #print "$myWin eq $myStr\n";
        print $aa;
    }
}
}

http://www.stratosgenomics.com/stratos-genomics-technology

The next-generation sequencing included whole genome sequencing(WGS), transcriptome sequencing (whole cDNA sequencing, RNA-seq), digital gene expression sequencing (Tag-Seq), ChIP-Seq, and so on. And there are many sequencing platform to generate sequece, as well know Sanger/ABi(the frist generation), Solexa/illumina, SOLiD/ABi, 454/Roche. But thier sequence format is different, also they have different error type. High quality data is very important for further analysis or data mining. There are many pipeline for raw sequence quality analysis and control with few of process for reporting reads quality statistical details, trimming, filtering, and error correction. Please bookmarks them for the benefits of bioinformatics community.

https://code.google.com/p/biowiki/

https://code.google.com/p/ngs-pipeline/source/browse/#svn%2Ftrunk

NGSand Perl scripts https://code.google.com/hosting/search?q=NGS+perl&projectsearch=Search+projects

NGS and Python scripts https://code.google.com/hosting/search?q=NGS+Python&projectsearch=Search+projects

Address of the bookmark: https://code.google.com/hosting/search?q=bioinformatics&sa=Search

While your PhD or PostDoc application, it is more common that you got rejected by many professors. Don't disappoint reply it calmly.

In grad school, I shared a house with three Bioinformatics PhD students. One, when he applied to a particular professor, received a letter that said, essentially, "If you are applying because you want to enrich yourself, great. If you are applying because you want a job, you should know that you won't get one." I am trying to tell you this is because if you, with a good background in Bioinformatics, are passing up opportunities, you must be a strong candidate in many areas. Enrich yourself.

So, my suggestion is take a deep breath, forgot about all. Don’t take it personally. It's been usual processes while hunting for a good lab and professor. Take is positive, I am not sure why they reject, but don't worry perhaps the lab don't deserve you. Always remember there are billions of reasons not to hire someone for projects, especially in a research sector.

My suggestion, please do not whine about how you were a great research candidate for the post, and you just can't understand why they were so stupid as to have rejected you! This feeling will not win you any points in research, community. Especially, when in todays socially connected era everyone is linked. Remember, a nice E-mail saying, "I really wished to working with you on this project and I hope we cross paths again," is all you need to send to the professor. Send a thank you note to the professor. Thank them for the time they spend to judge you. In the future, If you and the professor (of your dream) are attending a bioinformatics conference, invite him/her to lunch (please remember to pay the bill). In today evolving scientific ere, always remember to build your solid network in order to get a job of interest. Join all possible networking sites like LinkedIn, ResearchGate, Acamedia, FB for the same reason. You as a researcher always build a bridge with student/researcher/colleague/professor who have the research potential to lead in research and hire you. Just because you didn't get this project, doesn't mean there isn't another that will open up in couple of month.

Mostly, jobs that are hard to get are hard to get. Only you can decide if the continued sacrifices are worth the expected payout. If it is, keep on plowing. Build relationships. Attend conferences.

Image ref @ JaSonYa

Bioinformatics supports to researchers
Customized training in Bioinformatics for researchers and faculty members
Support in Installing, implementing and maintaining software on computer.
Create awareness for taking preventive measure against data security
Organize workshops on thrust ares of Bioinformatics
Research Training to students of Biotechnology and Bioinformatics

More at http://bioinfo.bisr.res.in/index.php

The Laboratory of Statistics and Computational tools for Bioinformatics (BioinfoLab) is hosted at the Istituto per le Applicazioni del Calcolo "Mauro Picone" - CNR . The laboratory has been officially opened in 2012 with the support of Programma Operativo Nazionale "Ricerca e Competitività" 2007-2013 (PON "R&C"), and it incorporates several expertise and research activities started since 2007, and supported by several CNR projects. Main interest of BioinfoLab is to develop novel statistical methods and computational tools for the analysis of high dimensional data arising from "Multi-omics" applications. In particular, current activities involve the analysis of ChIP-seq and RNA-seq experiments.

More at http://bioinfo.na.iac.cnr.it/BioinfoLab/index.html

More at http://catchenlab.life.illinois.edu/stacks/

Address of the bookmark: http://catchenlab.life.illinois.edu/stacks/

Visualization and quality assessment of de novo genome assemblies

Citation

This software is fully described in the paper:
Riba-Grognuz, Keller, Falquet, Xenarios & Wurm (2011) Visualization and quality assessment of de novo genome assemblies.

In brief, our scripts create Cytoscape files to visualize transcript evidence that suggests adjacency between scaffolds and contigs.

Software requirements

BLAT (tested with Standalone BLAT v. 32×1). Source Binaries .
Cytoscape (tested with versions 2.7.0, 2.8.2)
a UNIX machine (tested on Mac OS X 10.6 and CentOS 4.6)

Address of the bookmark: https://github.com/ksanao/TGNet

Address of the bookmark: https://www.bioconductor.org/packages/devel/bioc/vignettes/Sushi/inst/doc/Sushi.pdf