<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/35534?offset=410</link>
	<atom:link href="https://bioinformaticsonline.com/related/35534?offset=410" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/30889/phd-program-in-computer-science-at-university-of-essex</guid>
  <pubDate>Sat, 11 Feb 2017 13:11:36 -0600</pubDate>
  <link></link>
  <title><![CDATA[PhD program in Computer Science at University of Essex]]></title>
  <description><![CDATA[
<p>As part of the PhD program in Computer Science at University of Essex, I am looking for a PhD student in computational and synthetic biology.<br />The ideal candidate is interested in designing new biological design automation methods for genome scale projects and/or network modelling of genomic, transcriptomic and proteomic data.<br />Candidates interested in developing optimization algorithms for biological problems are encouraged to apply as well.<br />A summary of the research work in the lab can be found on o this page.</p>

<p>Candidates interested in the position should contact me in advance by email to: g.stracquadanio@essex.ac.uk</p>

<p>The deadline for the application is 28/02/2017; info about the application can be found on the Essex CSEE website.</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30966/maftools</guid>
	<pubDate>Thu, 16 Feb 2017 11:16:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30966/maftools</link>
	<title><![CDATA[MafTools]]></title>
	<description><![CDATA[<p>maftools - An R package to summarize, analyze and visualize MAF files. <a href="https://github.com/PoisonAlien/maftools#introduction"></a>Introduction.</p>
<p>With advances in Cancer Genomics, Mutation Annotation Format (MAF) is being widley accepted and used to store variants detected. <a href="http://cancergenome.nih.gov">The Cancer Genome Atlas</a> Project has seqenced over 30 different cancers with sample size of each cancer type being over 200. The <a href="https://wiki.nci.nih.gov/display/TCGA/TCGA+MAF+Files">resulting data</a> consisting of genetic variants is stored in the form of <a href="https://wiki.nci.nih.gov/display/TCGA/Mutation+Annotation+Format+%28MAF%29+Specification">Mutation Annotation Format</a>. This package attempts to summarize, analyze, annotate and visualize MAF files in an efficient manner either from TCGA sources or any in-house studies as long as the data is in MAF format. Maftools can also handle ICGC Simple Somatic Mutation format.</p>
<p>maftools is on <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f449.png" alt=":point_right:" width="20" height="20" style="border: 0px;"> <a href="http://biorxiv.org/content/early/2016/05/11/052662">bioRxiv</a> <img src="https://assets-cdn.github.com/images/icons/emoji/bowtie.png" alt=":bowtie:" title=":bowtie:" width="20" height="20" style="border: 0px; text-align: absmiddle;"></p>
<p>Please cite the below if you find this tool useful for you.</p>
<p>Mayakonda, A. and H.P. Koeffler, Maftools: Efficient analysis, visualization and summarization of MAF files from large-scale cohort based cancer studies. bioRxiv, 2016. doi: <a href="http://dx.doi.org/10.1101/052662">http://dx.doi.org/10.1101/052662</a></p><p>Address of the bookmark: <a href="https://github.com/PoisonAlien/maftools" rel="nofollow">https://github.com/PoisonAlien/maftools</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31123/biodownloader</guid>
	<pubDate>Sat, 25 Feb 2017 17:52:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31123/biodownloader</link>
	<title><![CDATA[BioDownloader]]></title>
	<description><![CDATA[<p><strong><em>BioDownloader</em></strong> is a program for downloading and/or updating files from ftp/http servers. The program has unique features that are specifically designed to deal with bioinformatics data files and servers:</p>
<ul>
<li>optimized to work with vast amount of data and very large file sets (~ 10,000 - 100,000).</li>
<li>allows the selective retrieval of only the required files (file masks, ls-lR parsing, recursive search, updates)</li>
<li>has a built-in repository containing the settings for the most common bioinformatics download needs</li>
<li>built-in wizard for batch post-processing of downloaded files (archive extraction, file conversion, etc.)</li>
<li>capable of performing multiple download or update tasks simultaneously</li>
</ul>
<p>BioDownloader has a built-in repository containing the settings for common bioinformatics file-synchronization needs, including the Protein Data Bank (PDB) and National Center for Biotechnology Information (NCBI) databases. It can post-process downloaded files, including archive extraction and file conversions.</p>
<p>http://dunbrack.fccc.edu/BioDownloader/</p><p>Address of the bookmark: <a href="http://dunbrack.fccc.edu/BioDownloader/" rel="nofollow">http://dunbrack.fccc.edu/BioDownloader/</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31024/dagchainer-computing-chains-of-syntenic-genes-in-complete-genomes</guid>
	<pubDate>Fri, 17 Feb 2017 16:13:35 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31024/dagchainer-computing-chains-of-syntenic-genes-in-complete-genomes</link>
	<title><![CDATA[DAGchainer: Computing Chains of Syntenic Genes in Complete Genomes]]></title>
	<description><![CDATA[<p>The DAGchainer software computes chains of syntenic genes found within complete genome sequences. As input, DAGchainer accepts a list of gene pairs with sequence homology along with their genome coordinates. Using a scoring function which accounts for the distance between neighboring genes on each DNA molecule and the BLAST E-value score between homologs, maximally scoring chains of ordered gene pairs are computed and reported. This algorithm can be used to mine large evolutionary conserved regions of genomes between two organisms. Alternatively, by examining colinear sets of homologous genes found within a single genome, segmental genome duplications can be revealed.</p>
<p>This software distribution includes both the DAGchainer utility and a Java-based graphical interface that allows the inputs and outputs to be navigated and interrogated dynamically.</p><p>Address of the bookmark: <a href="http://dagchainer.sourceforge.net/" rel="nofollow">http://dagchainer.sourceforge.net/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31089/conpade-genome-assembly-ploidy-estimation-from-next-generation-sequencing-data</guid>
	<pubDate>Fri, 24 Feb 2017 04:55:41 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31089/conpade-genome-assembly-ploidy-estimation-from-next-generation-sequencing-data</link>
	<title><![CDATA[ConPADE: Genome Assembly Ploidy Estimation from Next-Generation Sequencing Data]]></title>
	<description><![CDATA[<p><span>ConPADE (Contig Ploidy and Allele Dosage Estimation), a probabilistic method that estimates the ploidy of any given contig/scaffold based on its allele proportions. In the process, they report findings regarding errors in sequencing. The method can be used for whole genome shotgun (WGS) sequencing data. They also show applicability of the method for variant calling and allele dosage estimation. Results for simulated and real datasets are discussed and provide evidence that ConPADE performs well as long as enough sequencing coverage is available, or the true contig ploidy is low.&nbsp;</span></p>
<p><span>https://github.com/microsoftgenomics</span></p><p>Address of the bookmark: <a href="https://github.com/microsoftgenomics" rel="nofollow">https://github.com/microsoftgenomics</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42921/run-bash-script-in-perl-program</guid>
	<pubDate>Sat, 27 Feb 2021 01:42:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42921/run-bash-script-in-perl-program</link>
	<title><![CDATA[Run bash script in Perl program !]]></title>
	<description><![CDATA[<p>BioPerl is a compilation of Perl modules that can be used to build bioinformatics-related Perl scripts. It is used, for example, in the development of source codes, standalone software/tools, and algorithms in bioinformatics programmes. Different modules are easy to instal and include, making it easier to perform different functions. Despite the fact that Python is commonly favoured over Perl, some bioinformatics software, such as the standalone version of 'alienomics', is written in Perl. Often it's a major problem for beginners to execute certain Unix/shell commands in Perl script, so it's hard to determine which feature is unique to a situation.</p><div style="background-color: white;">Perl provides various features and operators for the execution of external commands (described as follows), which are unique in their own way.</div><div style="background-color: white;">&nbsp;</div><div style="background-color: white;">They vary slightly from one another, making it difficult for Perl beginners to choose between them.</div><div style="background-color: white;">&nbsp;</div><div style="background-color: white;"><strong>1. IPC::Open2</strong></div><p>More at https://bioinformaticsonline.com/snippets/view/42919/perl-ipcopen2-module</p><p><strong>2. exec&rdquo;&rdquo;</strong></p><p><em>&nbsp;syntax:&nbsp;</em><code>exec "command";</code></p><div style="background-color: #edfbff;">It's a Perl function (perlfunc) that executes a command but never returns, similar to a function's return statement.</div><div style="background-color: white;">While running the command, it keeps processing the script and does not wait until it finishes first, returns false when the command is not found, but never returns true.</div><p><strong>3. Backticks &ldquo; or qx//</strong></p><p><em>syntax:&nbsp;</em><code>`command`;</code></p><p><em>syntax:&nbsp;</em><code>qx/command/;</code></p><div style="background-color: white;">It's a Perl operator (perlop) that executes a command and then resumes the Perl script once the command has ended, but the return value is the command's STDOUT.</div><p><strong>4. IPC::Open3</strong></p><p><em>syntax:&nbsp;</em><code>$output =&nbsp;open3(\*CHLD_IN, \*CHLD_OUT, \*CHLD_ERR,&nbsp;'command arg1 arg2', 'optarg',...);</code></p><p style="text-align: justify;"><code></code>It is very similar to <code>IPC::Open2</code> with the capability to capture all three file handles of the process, i.e., STDIN, STDOUT, and STDERR. It can also be used with or without the shell. You can read about it more in the documentation: <a href="https://perldoc.perl.org/IPC/Open3.html" target="_blank">IPC::Open3</a>.</p><p><code>$output = open3(my $o ut,&nbsp;my $in, 'command arg1 arg2');</code></p><p>OR without using the shell</p><p><code>$output = open3(my $out,&nbsp;my $in, 'command', 'arg1', 'arg2');</code></p><p><strong>5.a2p</strong></p><p><em>syntax:&nbsp;</em><code>a2p [options] [awkscript]</code></p><p>There is a Perl utility known as <code>a2p</code> which translates <code>awk</code> command to Perl. It takes awk script as input and generates a comparable Perl script as the output. Suppose, you want to execute the following <code>awk</code> statement</p><p><code>awk '{$1 = ""; $2 = ""; print}' f1.txt</code></p><p>This statement gives error sometimes even after escaping the variables (\$1, \$2) but by using <code>a2p</code> it can be easily converted to Perl script:</p><p>For further information, you can read it&rsquo;s documentation: <code><a href="https://perldoc.perl.org/a2p.html" target="_blank">a2p</a></code></p><p>More help at https://bioinformaticsonline.com/snippets/view/42920/perl-script-to-run-awk-inside-perl</p><p><strong>6. system()</strong></p><p><em>syntax:&nbsp;</em><code>system( "command" );</code></p><p>It is also a Perl function (<a href="https://perldoc.perl.org/functions/system.html" target="_blank">perlfunc</a>) that executes a command and waits for it to get finished first and then resume the Perl script. The return value is the exit status of the command. It can be called in two ways:</p><p><code>system( "command arg1 arg2" );</code></p><p>OR</p><p><code>system( "command", "arg1", "arg2" );</code></p><p>HELP</p><p>Here are some useful Perl cheat sheets that can be used as a quick reference guide.--&nbsp;<a href="https://www.pcwdld.com/perl-cheat-sheet" target="_blank">https://www.pcwdld.com/perl-cheat-sheet</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31139/pbsuite-software-for-long-read-sequencing-data-from-pacbio</guid>
	<pubDate>Mon, 27 Feb 2017 09:54:47 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31139/pbsuite-software-for-long-read-sequencing-data-from-pacbio</link>
	<title><![CDATA[PBSuite: Software for Long-Read Sequencing Data from PacBio]]></title>
	<description><![CDATA[<p><span>PBJelly - the genome upgrading tool.&nbsp;</span><br><span>PBHoney - the structural variation discovery tool&nbsp;</span><br><br><span>Both are contained within the PBSuite code found in downloads.</span><br><br><span>----- PBJelly -----</span><br><span>Read The Paper&nbsp;</span><br><a href="http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0047768" target="_blank">http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0047768</a><br><br><span>PBJelly is a highly automated pipeline that aligns long sequencing reads (such as PacBio RS reads or long 454 reads in fasta format) to high-confidence draft assembles. PBJelly fills or reduces as many captured gaps as possible to produce upgraded draft genomes.&nbsp;</span><br><br><span>----- PBHoney -----</span><br><span>Read The Paper</span><br><a href="http://www.biomedcentral.com/1471-2105/15/180/abstract" target="_blank">http://www.biomedcentral.com/1471-2105/15/180/abstract</a><br><br><span>PBHoney is an implementation of two variant-identification approaches designed to exploit the high mappability of long reads (i.e., greater than 10,000 bp). PBHoney considers both intra-read discordance and soft-clipped tails of long reads to identify structural variants.</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/pb-jelly/" rel="nofollow">https://sourceforge.net/projects/pb-jelly/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/14302/bioinformatician-at-work</guid>
	<pubDate>Sat, 23 Aug 2014 04:44:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/14302/bioinformatician-at-work</link>
	<title><![CDATA[Bioinformatician at work !!!]]></title>
	<description><![CDATA[<p>Yet another peep up view of a bioinformatician research laboratory ...</p>]]></description>
	<dc:creator>Neel</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/14302" length="232751" type="image/png" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31295/mycc-accurate-binning-of-metagenomic-contigs-via-automated-clustering-sequences-using-information-of-genomic-signatures-and-marker-genes</guid>
	<pubDate>Fri, 03 Mar 2017 08:34:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31295/mycc-accurate-binning-of-metagenomic-contigs-via-automated-clustering-sequences-using-information-of-genomic-signatures-and-marker-genes</link>
	<title><![CDATA[MyCC: Accurate binning of metagenomic contigs via automated clustering sequences using information of genomic signatures and marker genes]]></title>
	<description><![CDATA[<p><span>MyCC, an automated binning tool that combines genomic signatures, marker genes and optional contig coverages within one or multiple samples, in order to visualize the metagenomes and to identify the reconstructed genomic fragments.</span></p>
<p><span>More at&nbsp;http://www.nature.com/articles/srep24175</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/sb2nhri/files/MyCC/" rel="nofollow">https://sourceforge.net/projects/sb2nhri/files/MyCC/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42803/bioinformatician-purdue-cancer-center</guid>
  <pubDate>Wed, 03 Feb 2021 22:54:14 -0600</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatician - Purdue Cancer Center]]></title>
  <description><![CDATA[
<p>The Center for Cancer Research is an NCI-designated cancer center. The center is a catalyst for collaborative cancer research around Purdue University. In this role, the selected individual will have the opportunity to cooperate with Purdue faculty and students in performing cutting-edge research and analyses, with opportunities for professional development, and the possibility of co-authorship in faculty research publications. <br />Projects will be challenging, including various model organisms, and we are looking for an individual who is excited about interacting with multi-disciplinary cancer research groups and the development of new tools, techniques, and workflows. Independently perform both routine and project-specific analyses, advise faculty on the design of experiments, writing manuscripts for publication, and writing grant proposals. Interact and collaborate with bioinformatics services (i.e. Statistical Consulting Center to provide relevant services to the campus research community), where applicable. Support all of the bioinformatics activities of the Center for Cancer Research at Purdue University<br />Required:</p>

<p>Master's degree in bioinformatics, computer science, molecular biology, or related field<br />One year of experience in analyzing RNA-Seq data <br />In lieu of a degree, consideration will be given to an equivalent combination of related education and required work experience.<br />Understanding of molecular biology, biochemistry, and genetics<br />Proficiency in writing scripts using Perl, Python, Java, or equivalent languages<br />Proficiency in R and UNIX/LINUX <br />Knowledge of genomics, alignment, annotation, bioinformatics, concepts of sequence assembly<br />Highly motivated and detail-oriented<br />Ability, interest, and curiosity to learn new skills<br />Must possess strong communication skills to work effectively with users across disciplines<br />Ability to work independently and as part of a multi-disciplinary team<br />Strong visual, verbal, and written communication skills<br />Excellent time organizational skills<br />Preferred:</p>

<p>Experience writing software or building software pipelines<br />Experience with oncology-specific public databases including TCGA<br />Experience with deploying and/or running software on high-performance computational systems<br />Statistical and experimental design knowledge<br />Additional Information: </p>

<p>This position is contingent on the availability of funding<br />Purdue will not sponsor employment authorization for this position  <br />A background check will be required for employment in this position<br />FLSA: Exempt (Not Eligible For Overtime)<br />Retirement Eligibility: Defined Contribution Waiting Period <br />Purdue University is an EOE/AA employer. All individuals, including minorities, women, individuals with disabilities, and veterans are encouraged to apply</p>

<p>More at https://careers.purdue.edu/job/West-Lafayette-Bioinformatician-Purdue-Cancer-Center-IN-47906/686617600/</p>
]]></description>
</item>

</channel>
</rss>