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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/22807?offset=40</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/poll/view/22906/at-what-age-did-you-gain-passion-in-bioinformatics</guid>
	<pubDate>Tue, 23 Jun 2015 10:39:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/poll/view/22906/at-what-age-did-you-gain-passion-in-bioinformatics</link>
	<title><![CDATA[At what age did you gain passion in Bioinformatics?]]></title>
	<description><![CDATA[<p>Most of the bioinformatician were biologist ( yeah ... not all ;), and at later stage they gain a passion in Bioinformatics and learn it. When did you get inclined towards computational analysis of biological data?</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/23892/bioinformatics-made-easy-search-bioinformatics-tools-and-run-genomic-analysis-in-the-cloud</guid>
	<pubDate>Thu, 20 Aug 2015 02:21:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/23892/bioinformatics-made-easy-search-bioinformatics-tools-and-run-genomic-analysis-in-the-cloud</link>
	<title><![CDATA[Bioinformatics Made Easy Search: Bioinformatics tools and run genomic analysis in the cloud]]></title>
	<description><![CDATA[<p>InsideDNA makes hundreds of bioinformatics tools immediately available to run via an easy-to-use web interface and allows an accurate search across all functions, tools and pipelines.</p>
<p>With InsideDNA, you can upload and store your own genomic/genetic datasets in a limitless cloud space, and instantly analyze it with a powerful compute instance, without any tool installation or set up hassle.</p>
<p>More at https://insidedna.me/</p><p>Address of the bookmark: <a href="https://insidedna.me/" rel="nofollow">https://insidedna.me/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/24264/cancer-research-database</guid>
	<pubDate>Tue, 01 Sep 2015 17:36:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/24264/cancer-research-database</link>
	<title><![CDATA[Cancer research database]]></title>
	<description><![CDATA[<p>Researchers in Andhra Pradesh have developed a database to identify genes that are common in tumours to provide their colleagues with easy access to insights into the genetic alterations in cancer.<br /> &nbsp;<br /> The database, hosted at the Sri Venkateswara University (SVU) in Tirupati, will integrate information on cancer genes and markers with experimental data.<br /> &nbsp;<br /> The <a href="http://cgmd.in/" target="_blank">Cancer Gene Markers Database</a> (CGMD) is meant to help scientists better understand tumour genes and markers at a molecular level by combining data with literature on treatment regimen and recent advances in cancer therapy.<br /> <br /> The database is free to access, and already includes 309 genes and 206 markers that correspond to 40 different human cancers. Accompanying literature comes from databases such as the United States&rsquo; <a href="http://www.ncbi.nlm.nih.gov/" target="_blank">National Center for Biotechnology Information</a> and the <a href="http://www.genome.jp/kegg/" target="_blank">Kyoto Encyclopedia of Genes and Genomes</a>. It also includes experimental data from <a href="http://www.ncbi.nlm.nih.gov/pubmed" target="_blank">PubMed</a>.<br /> <br /> In a paper <a href="http://dx.doi.org/10.1038/srep12035" target="_blank">published</a> last month in <em>Nature Scientific Reports</em>, the researchers from SVU&rsquo;s department of animal biotechnology, describes the need for a database for different genes and markers along with their molecular characteristics and pathway associations.</p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26525/ensembl-comparative-genomics-resources</guid>
	<pubDate>Sun, 28 Feb 2016 17:10:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26525/ensembl-comparative-genomics-resources</link>
	<title><![CDATA[Ensembl comparative genomics resources]]></title>
	<description><![CDATA[<div>
<p>The Ensembl comparative genomics resources are one such reference set that facilitates comprehensive and reproducible analysis of chordate genome data. Ensembl computes pairwise and multiple whole-genome alignments from which large-scale synteny, per-base conservation scores and constrained elements are obtained. Gene alignments are used to define Ensembl Protein Families, GeneTrees and homologies for both protein-coding and non-coding RNA genes. These resources are updated frequently and have a consistent informatics infrastructure and data presentation across all supported species. Specialized web-based visualizations are also available including synteny displays, collapsible gene tree plots, a gene family locator and different alignment views. The Ensembl comparative genomics infrastructure is extensively reused for the analysis of non-vertebrate species by other projects including Ensembl Genomes and Gramene and much of the information here is relevant to these projects. The consistency of the annotation across species and the focus on vertebrates makes Ensembl an ideal system to perform and support vertebrate comparative genomic analyses. We use robust software and pipelines to produce reference comparative data and make it freely available.</p>
<p><strong>Database URL:</strong> <a href="http://www.ensembl.org" target="pmc_ext">http://www.ensembl.org</a>.</p>
</div><p>Address of the bookmark: <a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4761110/" rel="nofollow">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4761110/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26325/crossmap</guid>
	<pubDate>Mon, 08 Feb 2016 15:47:00 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26325/crossmap</link>
	<title><![CDATA[CrossMap]]></title>
	<description><![CDATA[<p>CrossMap is a program for convenient conversion of genome coordinates (or annotation files) between <em>different assemblies</em> (such as Human <a href="http://www.ncbi.nlm.nih.gov/assembly/2928/">hg18 (NCBI36)</a> &lt;&gt; <a href="http://www.ncbi.nlm.nih.gov/assembly/2758/">hg19 (GRCh37)</a>, Mouse <a href="http://www.ncbi.nlm.nih.gov/assembly/165668/">mm9 (MGSCv37)</a> &lt;&gt; <a href="http://www.ncbi.nlm.nih.gov/assembly/327618/">mm10 (GRCm38)</a>).</p>
<p>It supports most commonly used file formats including SAM/BAM, Wiggle/BigWig, BED, GFF/GTF, VCF.</p>
<p>CrossMap is designed to liftover genome coordinates between assemblies. It&rsquo;s <em>not</em> a program for aligning sequences to reference genome.</p>
<p>We <em>do not</em> recommend using CrossMap to convert genome coordinates between species.</p>
<p>More at http://crossmap.sourceforge.net/</p><p>Address of the bookmark: <a href="http://crossmap.sourceforge.net/" rel="nofollow">http://crossmap.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26409/ucsc-genome-browser-and-blat-software</guid>
	<pubDate>Thu, 18 Feb 2016 03:18:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26409/ucsc-genome-browser-and-blat-software</link>
	<title><![CDATA[UCSC Genome Browser and Blat software !]]></title>
	<description><![CDATA[<p>This directory contains Genome Browser and Blat application binaries built for standalone <br>command-line use on various supported Linux and UNIX platforms. To determine which set of binaries <br>to download, type "uname -a" on the command line to display your machine type. In most cases the <br>usage statement for the application can be viewed by running the binary with no arguments. <br><br>The UCSC Genome Browser and Blat software are free for academic, nonprofit, and personal use. A <br>license is required for commercial download and installation of these binaries, with the exception <br>of items built from the following source code directories, which are freely available for all uses:<br><br>&nbsp;- kent/src/utils (includes big* tools)<br>&nbsp;- kent/src/lib<br>&nbsp;- kent/src/hg/autoSql<br>&nbsp;- kent/src/hg/autoXml<br><br>For information about commercial licensing of the Genome Browser software, see <br>http://genome.ucsc.edu/license/. The Blat and In-Silico PCR software may be commercially<br>licensed through Kent Informatics (http://www.kentinformatics.com).</p>
<p>More at http://hgdownload.cse.ucsc.edu/admin/exe/</p><p>Address of the bookmark: <a href="http://hgdownload.cse.ucsc.edu/admin/exe/" rel="nofollow">http://hgdownload.cse.ucsc.edu/admin/exe/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/26432/summer-2016</guid>
  <pubDate>Sun, 21 Feb 2016 06:17:55 -0600</pubDate>
  <link></link>
  <title><![CDATA[Summer 2016]]></title>
  <description><![CDATA[
<p>REU at Fordham University- Summer 2016</p>

<p>An NSF-funded REU to study Y-chromosome diversity and sex-biased dispersal in wild brown rats (Rattus norvegicus) is available in the Munshi-South Lab at Fordham University. Our lab is currently investigating rat evolution at scales ranging from landscape genetics of individual cities to global patterns of diversity. Development of resources for investigating Y-chromosome diversity will support many of these studies. The REU student will work with the lab to bioinformatically identify Y-chromosome SNPs, design SNPtype assays,<br />extract DNA, genotype samples, and analyze data.</p>

<p>We seek applicants interested in bioinformatics, evolutionary biology, and related disciplines.  Applicants must have taken a college-level genetics course.  This REU will require attention to detail, reliability, independence, and critical thinking.</p>

<p>This position is based at Fordham University's field station, the Louis Calder Center, in Armonk, NY. The Calder Center is located approximately 25 miles north of New York City in a protected woodland area. Housing<br />will be provided at the Calder Center for the duration of the REU (May 23 to Aug 12, 2016). Additionally, the student will receive a $6,000 stipend. The selected student will participate in professional development activities through the Calder Centers REU program, including presentation of results at a research colloquium at the end of the summer.</p>

<p>To apply, please send a one page personal statement about your scientific interests and how this REU will support your professional goals, unofficial transcripts including a list of Spring 2016 courses, and names of two professional references (including title, address, phone number, and email address) as a single pdf (with your last name in the file name) to Dr. Jason Munshi-South (jmunshisouth@fordham.edu).</p>

<p>Applications are due March 4th, 2016.</p>

<p>Jason Munshi-South</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27696/methylkit</guid>
	<pubDate>Fri, 03 Jun 2016 10:09:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27696/methylkit</link>
	<title><![CDATA[methylKit]]></title>
	<description><![CDATA[<p><em>methylKit</em> is an <a href="http://en.wikipedia.org/wiki/R_%28programming_language%29">R</a> package for DNA methylation analysis and annotation from high-throughput bisulfite sequencing. The package is designed to deal with sequencing data from <a href="http://www.nature.com/nprot/journal/v6/n4/abs/nprot.2010.190.html">RRBS</a> and its variants, but also target-capture methods such as <a href="http://www.halogenomics.com/sureselect/methyl-seq">Agilent SureSelect methyl-seq</a>. In addition, methylKit can deal with base-pair resolution data for 5hmC obtained from Tab-seq or oxBS-seq. It can also handle whole-genome bisulfite sequencing data if proper input format is provided.</p><p>Address of the bookmark: <a href="https://github.com/al2na/methylKit" rel="nofollow">https://github.com/al2na/methylKit</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30236/pyscaf</guid>
	<pubDate>Mon, 19 Dec 2016 14:20:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30236/pyscaf</link>
	<title><![CDATA[pyScaf]]></title>
	<description><![CDATA[<p>pyScaf orders contigs from genome assemblies utilising several types of information:</p>
<ul>
<li>paired-end (PE) and/or mate-pair libraries (<a href="https://github.com/lpryszcz/pyScaf#ngs-based-scaffolding">NGS-based mode</a>)</li>
<li>long reads (<a href="https://github.com/lpryszcz/pyScaf#scaffolding-based-on-long-reads">NGS-based mode</a>)</li>
<li>synteny to the genome of some related species (<a href="https://github.com/lpryszcz/pyScaf#reference-based-scaffolding">reference-based mode</a>)</li>
</ul>
<p>Scaffolding&nbsp;</p>
<p>In reference-based mode, pyScaf uses synteny to the genome of closely related species in order to order contigs and estimate distances between adjacent contigs.</p>
<p>Contigs are aligned globally (end-to-end) onto reference chromosomes, ignoring:</p>
<ul>
<li>matches not satisfying cut-offs (<code>--identity</code>&nbsp;and&nbsp;<code>--overlap</code>)</li>
<li>suboptimal matches (only best match of each query to reference is kept)</li>
<li>and removing overlapping matches on reference.</li>
</ul>
<p>In preliminary tests, pyScaf performed superbly on simulated heterozygous genomes based on&nbsp;<em>C. parapsilosis</em>&nbsp;(13 Mb; CANPA) and&nbsp;<em>A. thaliana</em>&nbsp;(119 Mb; ARATH) chromosomes, reconstructing correctly all chromosomes always for CANPA and nearly always for ARATH (<a href="https://www.dropbox.com/sh/bb7lwggo40xrwtc/AAAZ7pByVQQQ-WhUXZVeJaZVa/pyScaf?dl=0">Figures in dropbox</a>,&nbsp;<a href="https://docs.google.com/spreadsheets/d/1InBExy-qKDLj-upd8tlPItVSKc4mLepZjZxB31ii9OY/edit#gid=2036953672">CANPA table</a>,&nbsp;<a href="https://docs.google.com/spreadsheets/d/1InBExy-qKDLj-upd8tlPItVSKc4mLepZjZxB31ii9OY/edit#gid=1920757821">ARATH table</a>).<br>Runs took ~0.5 min for CANPA on&nbsp;<code>4 CPUs</code>&nbsp;and ~2 min for ARATH on&nbsp;<code>16 CPUs</code>.</p>
<p><span>Important remarks:</span></p>
<ul>
<li>Reduce your assembly before (fasta2homozygous.py) as any redundancy will likely break the synteny.</li>
<li>pyScaf works better with contigs than scaffolds, as scaffolds are often affected by mis-assemblies (no&nbsp;<em>de novo assembler</em>&nbsp;/ scaffolder is perfect...), which breaks synteny.</li>
<li>pyScaf works very well if divergence between reference genome and assembled contigs is below 20% at nucleotide level.</li>
<li>pyScaf deals with large rearrangements ie. deletions, insertion, inversions, translocations.&nbsp;<span>Note however, this is experimental implementation!</span></li>
<li>Consider closing gaps after scaffolding.</li>
</ul><p>Address of the bookmark: <a href="https://github.com/lpryszcz/pyScaf" rel="nofollow">https://github.com/lpryszcz/pyScaf</a></p>]]></description>
	<dc:creator>Bulbul</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37759/pandaseq-is-a-program-to-align-illumina-reads-optionally-with-pcr-primers-embedded-in-the-sequence-and-reconstruct-an-overlapping-sequence</guid>
	<pubDate>Fri, 21 Sep 2018 10:19:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37759/pandaseq-is-a-program-to-align-illumina-reads-optionally-with-pcr-primers-embedded-in-the-sequence-and-reconstruct-an-overlapping-sequence</link>
	<title><![CDATA[PANDASEQ is a program to align Illumina reads, optionally with PCR primers embedded in the sequence, and reconstruct an overlapping sequence.]]></title>
	<description><![CDATA[<p>Development packages for zlib and libbz2 are needed, as well as a standard compiler environment. On Ubuntu, this can be installed via:</p>
<pre><code>sudo apt-get install build-essential libtool automake zlib1g-dev libbz2-dev pkg-config
</code></pre>
<p>On MacOS, the Apple Developer tools and Fink (or MacPorts or Brew) must be installed, then:</p>
<pre><code>sudo fink install bzip2-dev pkgconfig</code></pre><p>Address of the bookmark: <a href="https://github.com/neufeld/pandaseq" rel="nofollow">https://github.com/neufeld/pandaseq</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

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