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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36880?offset=810</link>
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	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34493/plast-a-fast-accurate-and-ngs-scalable-bank-to-bank-sequence-similarity-search-tool</guid>
	<pubDate>Fri, 01 Dec 2017 04:10:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34493/plast-a-fast-accurate-and-ngs-scalable-bank-to-bank-sequence-similarity-search-tool</link>
	<title><![CDATA[PLAST: A fast, accurate and NGS scalable bank-to-bank sequence similarity search tool]]></title>
	<description><![CDATA[<p><strong>PLAST is a fast, accurate and NGS scalable bank-to-bank sequence similarity search tool providing significant accelerations of seeds-based heuristic comparison methods, such as the Blast suite of algorithms.</strong></p>
<p><strong>Relying on unique software architecture, PLAST takes full advantage of recent multi-core personal computers without requiring any additional hardware devices.</strong></p>
<p>PLAST stands for&nbsp;<em>Parallel Local Sequence Alignment Search Tool&nbsp;</em>and is was&nbsp;<a href="http://www.biomedcentral.com/1471-2105/10/329" target="_blank">published in BMC Bioinformatics.</a></p>
<p>PLAST is a general purpose sequence comparison tool providing the following benefits:</p>
<ul>
<li>PLAST is a high-performance sequence comparison tool designed to compare two sets of sequences (query vs. reference),</li>
<li>Reduces the processing time of sequences comparisons while providing highest quality results,</li>
<li>Contains a fully integrated data filtering engine capable of selecting relevant hits with user-defined criteria (E-Value, identity, coverage, alignment length, etc.),</li>
<li>Does not require any additional hardware, since it is a software solution. It is easy to install, cost-effective, takes full advantage of multi-core processors and uses a small RAM footprint,</li>
<li>Ready to be used on desktop computer, cluster, cloud as well as within distributed system running Hadoop.</li>
</ul>
<p>https://plast.inria.fr/</p><p>Address of the bookmark: <a href="https://plast.inria.fr/" rel="nofollow">https://plast.inria.fr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22436/ra-bioinformatics-at-national-bureau-of-animal-genetic-resources</guid>
  <pubDate>Thu, 28 May 2015 19:25:33 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at NATIONAL BUREAU OF ANIMAL GENETIC RESOURCES]]></title>
  <description><![CDATA[
<p>NATIONAL BUREAU OF ANIMAL GENETIC RESOURCES</p>

<p>Near Basant Vihar G.T. Road Bypass P.O. Box No.129</p>

<p>Karnal - 132001 (Haryana)</p>

<p>WALK-IN-INTERVIEW</p>

<p>A walk-in-Interview is proposed to be held at National Bureau of Animal Genetic Resources, Karnal (Haryana)-132001 at 10:30 AM on 10.06.2015 to select One Research Associate as per details given below:</p>

<p>1. One post of Research Associate under National Fellow project entitled “Genome data mining to unravel molecular basis of thermotolerance and adaptation to diverse environments in native cattle and buffaloes”.</p>

<p>The post duration is Upto 22.05.2016 or earlier &amp; Co-terminus with the project.</p>

<p>Essential Qualifications: Master’s degree (M.Sc. / M.V.Sc.) in Biotechnology/ Animal Genetics and Breeding/ Life Sciences/ Bioinformatics with 2 Years research experience in relevant subject or Ph.D in any of the above subjects.</p>

<p>Desirable: Working Experience in molecular biology, gene expression/ microarray data analysis, SNP genotyping and sequence data analysis, mammalian cell-culture handling etc.</p>

<p>Emolument: Rs. 23,000/- per month + HRA as per admissibility</p>

<p>Research Associate: ONE</p>

<p>Duration of engagement: Upto 22.05.2016 or earlier Co-terminus with the project</p>

<p>Age Limit:  40 years for Men  45 years for women as on date of interview</p>

<p>Note: Relaxation in age will be admissible for SC/ST &amp; OBC candidates as per Govt. of India /ICAR norms</p>

<p>1. The applicants must bring with them original documents and brief of research work done during post graduation along with a set of photocopy and latest two passport size photographs. 2. A panel of selected candidates will also be made which may be utilized for filling of positions of shorter durations in future if demand arises. 3. Experience certificate in original, if any 4. The above positions are purely on temporary basis and are coterminus with the project. No TA/DA will be paid to attend the interview. 5. Any other clarifications can be had on the date of interview. 6. The Director’s decision will be final and binding on all respects.</p>

<p>Advertisement: http://210.212.93.85/RAadvertisiment.pdf</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22615/jrf-position-%E2%80%93-bioinformatics-department-aravind-medical-research-foundation-amrf-madurai</guid>
  <pubDate>Fri, 12 Jun 2015 05:42:12 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF Position – Bioinformatics Department, Aravind Medical Research Foundation (AMRF), Madurai.]]></title>
  <description><![CDATA[
<p>Applications are invited from eligible candidates for the post of Junior Research Fellow (JRF) to work at the Department of Bioinformatics, Aravind Medical Research Foundation in the following DST-SERB funded project “Clinical exome analysis pipeline for eye disease next-generation sequencing panel”.</p>

<p>Post: Junior Research Fellow (1 Position)</p>

<p>Duration: Three years</p>

<p>Qualification: First class in M.Sc/M.tech in Bioinformatics/Life Sciences/Biophysics/ Biostatistics/Bioengineering. Experience in Database development, NGS data analysis, Systems Biology and Structural Bioinformatics is desired. Preference will be given to the candidates with good computer programming skills in C, C++, R, Perl, PHP, Unix Scripting etc.</p>

<p>Selected candidates will be paid fellowship as per existing DST norms.</p>

<p>How to apply:</p>

<p>Candidates are requested to apply through one of the two modes given below<br />1. Online application – Click here to submit the online application https://docs.google.com/forms/d/16h2GLnQ-Ny-tLtlgfY3Bx3sCjeHJE30cfhJaDqW_uRs/viewform?c=0&amp;w=1<br />2. Application forms can be downloaded from here.https://docs.google.com/file/d/0BwwJEudQStxFWXdNWXl4NWtDaWc/edit<br /> Filled in application form should be sent by post to Dr. D. Bharanidharan, Department of Bioinformatics, Aravind Medical Research Foundation No 1, Anna Nagar Madurai – 625 020,</p>

<p>Candidates should apply by online or submit their applications by post on or before 15th June, 2015. Only Short listed candidates will be called for an interview. No TA/DA will be paid.</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37233/rna-seq-analysis-workshop-course-materials</guid>
	<pubDate>Tue, 03 Jul 2018 08:14:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37233/rna-seq-analysis-workshop-course-materials</link>
	<title><![CDATA[RNA-seq Analysis Workshop Course Materials]]></title>
	<description><![CDATA[RNAseq can be roughly divided into two "types":

Reference genome-based - an assembled genome exists for a species for which an RNAseq experiment is performed. It allows reads to be aligned against the reference genome and significantly improves our ability to reconstruct transcripts. This category would obviously include humans and most model organisms but excludes the majority of truly biologically intereting species (e.g., Hyacinth macaw);

Reference genome-free - no genome assembly for the species of interest is available. In this case one would need to assemble the reads into transcripts using de novo approaches. This type of RNAseq is as much of an art as well as science because assembly is heavily parameter-dependent and difficult to do well.
In this lesson we will focus on the Reference genome-based type of RNA seq.

http://chagall.med.cornell.edu/RNASEQcourse/<p>Address of the bookmark: <a href="http://chagall.med.cornell.edu/RNASEQcourse/" rel="nofollow">http://chagall.med.cornell.edu/RNASEQcourse/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/22571/pattern-matching-problem-solution-with-perl</guid>
	<pubDate>Tue, 09 Jun 2015 23:58:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/22571/pattern-matching-problem-solution-with-perl</link>
	<title><![CDATA[Pattern Matching Problem Solution with Perl]]></title>
	<description><![CDATA[<p>Problem at http://rosalind.info/problems/1c/</p><p>#Find all occurrences of a pattern in a string.<br />#Given: Strings Pattern and Genome.<br />#Return: All starting positions in Genome where Pattern appears as a substring. Use 0-based indexing.<br /><br />use strict;<br />use warnings;<br /><br />my $string="GATATATGCATATACTT";<br />my $subStr="ATAT";<br />my $kmer=length($subStr);<br /><br />kmerMatch ($string, $subStr, $kmer);<br /><br />sub kmerMatch { #Check the exact matching kmers with sliding window<br />my ($string, $myStr, $kmer)=@_;<br />for (my $aa=0; $aa&lt;=(length($string)-$kmer); $aa++) {<br />&nbsp;&nbsp;&nbsp; my $myWin=substr&nbsp; $string, $aa,$kmer;<br />&nbsp;&nbsp;&nbsp; if ($myWin eq $myStr) {<br />&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; #print "$myWin eq $myStr\n";<br />&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; print $aa;<br />&nbsp;&nbsp;&nbsp; }<br />}<br />}</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/22769/ensembl-27</guid>
	<pubDate>Tue, 16 Jun 2015 16:10:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/22769/ensembl-27</link>
	<title><![CDATA[Ensembl 27]]></title>
	<description><![CDATA[<h3>What is new?</h3><ul>
<li>Expansion of Protists and Fungi with hundreds of annotated genomes</li>
<li>Variation data for bread wheat, rice, <em>Aedes aegypti</em>, and <em>Ixodes scapularis</em></li>
<li>Whole genome alignments for <em>O. longistaminata</em> and <em>T. cacao</em></li>
<li>Non-coding RNA gene models in <a href="http://bacteria.ensembl.org">Bacteria</a></li>
<li>New assembly of tomato (version 2.50)</li>
<li>Full support for UCSC Track Hub format for hosting your own data in Ensembl</li>
</ul><p>More at http://www.ensembl.info/blog/2015/06/16/ensembl-genomes-release-27-is-out/</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37993/platypus-a-haplotype-based-variant-caller-for-next-generation-sequence-data</guid>
	<pubDate>Thu, 25 Oct 2018 06:14:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37993/platypus-a-haplotype-based-variant-caller-for-next-generation-sequence-data</link>
	<title><![CDATA[Platypus: A Haplotype-Based Variant Caller For Next Generation Sequence Data]]></title>
	<description><![CDATA[<p><strong>Platypus</strong><span>&nbsp;is a tool designed for efficient and accurate variant-detection in high-throughput sequencing data. By using local realignment of reads and local assembly it achieves both high sensitivity and high specificity. Platypus can detect SNPs, MNPs, short indels, replacements and (using the assembly option) deletions up to several kb. It has been extensively tested on&nbsp;</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/?term=24463883">whole-genome</a><span>,&nbsp;</span><a href="http://www.nature.com/ng/journal/v45/n1/abs/ng.2492.html">exon-capture</a><span>, and&nbsp;</span><a href="http://www.nature.com/nature/journal/v493/n7432/abs/nature11725.html">targeted capture</a><span>&nbsp;data, it has been run on very large datasets as part of the&nbsp;</span><a href="http://www.1000genomes.org/">Thousand Genomes</a><span>&nbsp;and WGS500 projects, and is being used in clinical sequencing trials in the&nbsp;</span><a href="http://www.mcgprogramme.com/">Mainstreaming Cancer Genetics</a><span>&nbsp;programme.&nbsp;</span></p>
<p><span>Tutorial&nbsp;https://github.com/andyrimmer/Platypus/blob/master/misc/README.txt</span></p><p>Address of the bookmark: <a href="http://www.well.ox.ac.uk/platypus" rel="nofollow">http://www.well.ox.ac.uk/platypus</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22780/ra-bioinformatics-at-institution-centre-for-human-genetics-bangalore</guid>
  <pubDate>Wed, 17 Jun 2015 19:14:37 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at Institution: Centre for Human Genetics,  Bangalore]]></title>
  <description><![CDATA[
<p>Institution: Centre for Human Genetics, <br />Bangalore <br />Discipline: Molecular Genetics of Human Disease Biology </p>

<p>Minimum qualification: MSc in any branch of life sciences</p>

<p>Applications are invited for the position of a Research Assistant in the Centre for Human Genetics, Bangalore. </p>

<p>The project involves identification of mutations in MPS (mucopolysaccharidosis) patients, and study of their predicted effects to understand how the mutations lead to disease. </p>

<p>Techniques used will be genomic DNA isolation, PCR, DNA sequencing and sequence analysis. Computational tools would also be used to analyse and interpret data. </p>

<p>Candidates may be assigned work in the ongoing project or in new ones. </p>

<p>The candidate who is selected and joins would acquire hands-on experience in research and the capability to conduct insightful research. </p>

<p>Candidates applying for the position should have an MSc in any branch of life sciences. Those with research experience in cell and molecular biology, and high NET/ GATE score would be preferred. </p>

<p>The successful applicant is expected to stay for at least one and a half years. </p>

<p>Please apply with CV to Sudha Srinivasan (sudha@ibab.ac.in), stating where you saw this ad.</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40604/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output</guid>
	<pubDate>Fri, 24 Jan 2020 06:04:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40604/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output</link>
	<title><![CDATA[gapFinisher: A reliable gap filling pipeline for SSPACE-LongRead scaffolder output]]></title>
	<description><![CDATA[<p><span>gapFinisher is based on the controlled use of a previously published gap filling tool FGAP and works on all standard Linux/UNIX command lines. They compare the performance of gapFinisher against two other published gap filling tools PBJelly and GMcloser. </span></p>
<p><span>gapFinisher can fill gaps in draft genomes quickly and reliably.</span></p><p>Address of the bookmark: <a href="https://github.com/kammoji/gapFinisher" rel="nofollow">https://github.com/kammoji/gapFinisher</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/22961/bioscripts</guid>
	<pubDate>Sun, 28 Jun 2015 07:46:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/22961/bioscripts</link>
	<title><![CDATA[BioScripts]]></title>
	<description><![CDATA[<p>You are requested to please bookmark collection of bioinformatics tools, scripts, codes that can be pieced together in a very easy and flexible manner to perform both simple and complex bioinformatics tasks.</p>
<p>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.</p>
<p>https://code.google.com/p/biowiki/</p>
<p>https://code.google.com/p/ngs-pipeline/source/browse/#svn%2Ftrunk</p>
<p>NGSand Perl scripts https://code.google.com/hosting/search?q=NGS+perl&amp;projectsearch=Search+projects</p>
<p>NGS and Python scripts https://code.google.com/hosting/search?q=NGS+Python&amp;projectsearch=Search+projects</p><p>Address of the bookmark: <a href="https://code.google.com/hosting/search?q=bioinformatics&amp;sa=Search" rel="nofollow">https://code.google.com/hosting/search?q=bioinformatics&amp;sa=Search</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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