<?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/29586?offset=1220</link>
	<atom:link href="https://bioinformaticsonline.com/related/29586?offset=1220" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/8330/atlas-of-ancient-inter-ethnic-group</guid>
	<pubDate>Fri, 14 Feb 2014 13:16:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/8330/atlas-of-ancient-inter-ethnic-group</link>
	<title><![CDATA[Atlas of ancient inter-ethnic group !!!]]></title>
	<description><![CDATA[<p>Now a dayz, almost 3% of the world's population lived outside their country of origin. These migration is increasingly being perceived as a force that can contribute to development, and an integral aspect of the global development process.&nbsp; While migrants make important contributions to the economic prosperity of their host countries, the flow of financial, technological, social and human capital back to their countries of origin also is having a significant impact on poverty reduction and economic development.</p><p>However, the ancient invasions and migrations to slavery and trade, history is embroidered with events that led to interactions between previously separate populations. Early humans migrated due to many factors such as changing climate and landscape and inadequate food supply. Historical migration of human populations begins with the movement of Homo erectus out of Africa across Eurasia about a million years ago. Homo sapiens appear to have occupied all of Africa about 150,000 years ago, moved out of Africa 70,000 years ago, and had spread across Australia, Asia and Europe by 40,000 years BC. Indo-Aryan migration from the Indus Valley to the plain of the River Ganges in Northern India is presumed to have taken place in the Middle to Late Bronze Age, contemporary to the Late Harappan phase in India (ca. 1700 to 1300 BC). From 180 BC, a series of invasions from Central Asia followed, including those led by the Indo-Greeks, Indo-Scythians, Indo-Parthians and Kushans in the northwestern Indian subcontinent.</p><p><img src="http://upload.wikimedia.org/wikipedia/commons/3/37/Map-of-human-migrations.jpg" alt="image" style="border: 0px; border: 0px;"></p><p>Using the recent advance technologies researchers have created a historical atlas of instances of such mixing. They use a sophisticated statistical method for making inferences about human history and&nbsp;infer populations interbredings ( happen over the past 4,000 years) with an ease.<br /><br />The study published the findings and presented with an interactive map. http://admixturemap.paintmychromosomes.com/</p><p>These sort of genomic study have some limilation. It is hard to precisely define sources of mixing when it occurred between genetically similar groups, and scenarios involving multiple waves of mixing over time or between multiple groups can be difficult to tease apart. But it is believed that larger sample sizes will improve resolution. These high resolution will provide a deeper understanding of human history.</p><p>Reference:</p><p>http://www.sciencemag.org/content/early/2014/01/28/science.1245938</p><p>http://www.ncbi.nlm.nih.gov/pubmed/21390129?dopt=Abstract&amp;holding=npg</p><p>http://www.csulb.edu/~kmacd/paper-ethnicity.html</p><p>Image: Wikipedia</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/9055/computational-biologist-scientist-strand-life-sciences</guid>
  <pubDate>Fri, 14 Mar 2014 11:36:56 -0500</pubDate>
  <link></link>
  <title><![CDATA[Computational Biologist Scientist @ Strand Life Sciences]]></title>
  <description><![CDATA[
<p>We are looking for a motivated application scientist to help evaluate, compare, and develop next generation sequencing (NGS) data analysis methods. The successful candidate should be able to quickly understand the state-of-art computational biology techniques, prototype them and perform benchmarking studies. The candidate must also be comfortable working with people from different disciplines and be able to present data analysis results in a clear and effective manner. The candidate is also expected to interact with customers as needed, write technical reports and publish new methods and/or data analysis findings in public forums.</p>

<p>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.</p>

<p>Eligible and interested candidates can email your resumes to rohit at strandls dot com</p>

<p>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.</p>

<p>http://www.avadis-ngs.com/careers</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/40789/complete-genome-sequence-of-wuhan-seafood-market-pneumonia-virus-is-out</guid>
	<pubDate>Fri, 31 Jan 2020 02:36:59 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/40789/complete-genome-sequence-of-wuhan-seafood-market-pneumonia-virus-is-out</link>
	<title><![CDATA[Complete genome sequence of Wuhan seafood market pneumonia virus is out !]]></title>
	<description><![CDATA[<p>Wuhan-Hu-1 claimed at least 40 lives and infected at least 1300 others in China. Cases are now being reported from Thailand, Singapore, Malaysia, South Korea, Japan, Vietnam, Nepal, France, Australia and even as far as the US.&nbsp;On Jan 10 2020, while news of the first fatality was barely trickling in, the <a href="https://www.ncbi.nlm.nih.gov/nuccore/MN908947">29,903 letters</a> constituting the viral genome from an affected individual in Wuhan had already been elucidated (even though a few corrections were made subsequently). All the viral genome sequences from affected individuals are very very close to each other. Several are identical and none has more than 5 differences (99.983% similarity). This strongly suggests that transmission into humans came from a single pointed source and happened very recently, between Sep-Dec 2019.</p><p>Check out the detail at https://www.ncbi.nlm.nih.gov/nuccore/MN908947</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41207/blobtoolkit-a-toolkit-for-genome-assembly-qc</guid>
	<pubDate>Fri, 21 Feb 2020 00:17:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41207/blobtoolkit-a-toolkit-for-genome-assembly-qc</link>
	<title><![CDATA[BlobToolKit: A toolkit for genome assembly QC]]></title>
	<description><![CDATA[<p>Filtering raw genomic datasets is essential to avoid chimeric assemblies and to increase the validity of sequence-based biological inference. BlobToolKit extends the BlobTools<span>1</span>/Blobology<span>2</span>&nbsp;approach to simplify interactive and reproducible filtering.</p>
<p>BlobToolKit is comprised of four components:</p>
<ol>
<li><a href="https://blobtoolkit.genomehubs.org/btk-viewer/">BlobToolKit Viewer</a>&nbsp;allows browser-based interactive visualisation and filtering of preliminary or published genomic datasets even for highly fragmented assemblies.</li>
<li><a href="https://blobtoolkit.genomehubs.org/blobtools2/">BlobTools2</a>&nbsp;is a command-line program to convert assemblies and analysis results into datasets that can be further processed using&nbsp;<a href="https://blobtoolkit.genomehubs.org/blobtools2/">BlobTools2</a>&nbsp;and/or visualised in the Viewer.</li>
<li>The&nbsp;<a href="https://blobtoolkit.genomehubs.org/specification/">BlobToolKit Specification</a>&nbsp;features a formal schema and validator for the JSON-based BlobDir format used by&nbsp;<a href="https://blobtoolkit.genomehubs.org/blobtools2/">BlobTools2</a>&nbsp;and the&nbsp;<a href="https://blobtoolkit.genomehubs.org/btk-viewer/">Viewer</a>.</li>
<li>The&nbsp;<a href="https://blobtoolkit.genomehubs.org/pipeline/">BlobToolKit Pipeline</a>&nbsp;is a configurable Snakemake pipeline that automates all steps from retrieving public datasets through running analyses and generating a BlobDir dataset with&nbsp;<a href="https://blobtoolkit.genomehubs.org/blobtools2/">BlobTools2</a>, ready for visualisation in the&nbsp;<a href="https://blobtoolkit.genomehubs.org/btk-viewer/">Viewer</a>.</li>
</ol>
<p>Paper&nbsp;<a href="https://www.biorxiv.org/content/10.1101/844852v1.full.pdf">https://www.biorxiv.org/content/10.1101/844852v1.full.pdf</a></p><p>Address of the bookmark: <a href="https://blobtoolkit.genomehubs.org/" rel="nofollow">https://blobtoolkit.genomehubs.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/9039/postdoc-position-in-computational-biology</guid>
  <pubDate>Fri, 14 Mar 2014 01:38:49 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoc Position in Computational Biology]]></title>
  <description><![CDATA[
<p>The Computational Biology Group of Interdisciplinary Center for<br />Clinical Research (IZKF) Aachen, RWTH Aachen University Hospital,<br />Aachen, invites applicants for PhD candidate or postdoctoral position<br />in computational biology in one of the following topics:</p>

<p>1) Statistical machine learning methods for the analysis of medical<br />epigenomics data.</p>

<p>2) Sequence analysis algorithms for detection of RNA-DNA interactions.</p>

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

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

<p>More at http://costalab.org/wp/phd-and-postdoc-position-in-computational-biology/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41464/phytozome-v121-plant-science-community-hub-for-accessing-palnts-genomic-data</guid>
	<pubDate>Tue, 17 Mar 2020 07:30:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41464/phytozome-v121-plant-science-community-hub-for-accessing-palnts-genomic-data</link>
	<title><![CDATA[Phytozome  v12.1: plant science community hub for accessing palnts genomic data]]></title>
	<description><![CDATA[<p>Phytozome, the Plant Comparative Genomics portal of the Department of Energy's Joint Genome Institute, provides JGI users and the broader plant science community a hub for accessing, visualizing and analyzing JGI-sequenced plant genomes, as well as selected genomes and datasets that have been sequenced elsewhere. As of release v12.1.6, Phytozome hosts 93 assembled and annotated genomes, from 82 Viridiplantae species. More than half of these genomes have been sequenced, assembled and/or annotated with JGI Plant Science program resources. By integrating this large collection of plant genomes into a single resource and performing comprehensive and uniform annotation and analyses, Phytozome facilitates accurate and insightful comparative genomics studies.</p><p>Address of the bookmark: <a href="https://phytozome.jgi.doe.gov/pz/portal.html" rel="nofollow">https://phytozome.jgi.doe.gov/pz/portal.html</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/fun/view/9207/biogeek-fun</guid>
	<pubDate>Sun, 16 Mar 2014 06:33:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/fun/view/9207/biogeek-fun</link>
	<title><![CDATA[BioGeek Fun]]></title>
	<description><![CDATA[<p>1. A futuristic computational biology student was told to write "It is in my gene!!!" on the board 100 times as a punishment. here's his response -<br /><br />use warnings;<br />for ($count=1; $count &lt;=100; $count++) { print "It is in my gene!!!";}<br /><br />I guess, he is gonna to be a real biogeek. Nice try though. Smart kid.</p><p>&nbsp;</p><p>2. In some perl script I found this <br />&nbsp;. . . . . .<br />&nbsp;. . . . . .<br /># It works for me, only God understood how it is working<br />while (/(&lt;\/[^&gt;]+&gt;)|(&lt;[^&gt;]+&gt;)|(&lt;[^&gt;]+&gt;)$|([^&gt;&lt;]+)/go) {<br />&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; $startGene=$1;<br />&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; $beginChromosome=$2;<br />&nbsp;&nbsp; &nbsp;<br />. . . . . .<br />&nbsp;.. . . . . .<br />}</p><p>&nbsp;</p><p>3. One more interesting message in Perl found &hellip;. It will must tickle you bone :) <br />open(my $fh, "&lt;", "gene.txt")&nbsp;&nbsp; &nbsp;or kill " Me if you think this is a mistake :$!";<br /><br /></p><p>&nbsp;</p><p>4. From the Perl <br /><br />&nbsp; while () {&nbsp; # "The Mothership Connection is here!"<br />&nbsp;&nbsp; &nbsp;print &ldquo;$_\n&rdquo;; # Printing the offspring :)</p><p>&nbsp;</p><p>5. Perl message<br />if ($1) { print &ldquo;Just found a the error in chromosome !!!, yahoo&hellip;&rdquo;; else { &ldquo;That is not error, but mutation you moron!&rdquo;;</p><p>&nbsp;</p><p>6. One genome database curator walk in wine bar asked the bartender:<br />CREATE TABLE gene IF NOT EXISTS SexOnTheBeach;</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41896/kad-assessing-genome-assemblies-using-k-mer-copies-in-assemblies-and-k-mer-abundance-in-illumina-reads</guid>
	<pubDate>Fri, 19 Jun 2020 07:34:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41896/kad-assessing-genome-assemblies-using-k-mer-copies-in-assemblies-and-k-mer-abundance-in-illumina-reads</link>
	<title><![CDATA[KAD: Assessing genome assemblies using K-mer copies in assemblies and K-mer abundance in Illumina reads]]></title>
	<description><![CDATA[<p>KAD is designed for evaluating the accuracy of nucleotide base quality of genome assemblies. Briefly, abundance of k-mers are quantified for both sequencing reads and assembly sequences. Comparison of the two values results in a single value per k-mer, K-mer Abundance Difference (KAD), which indicates how well the assembly matches read data for each k-mer.</p>
<p><a href="https://render.githubusercontent.com/render/math?math=KAD=log_{2}\begin{pmatrix}\frac{c%2Bm}{m(n%2B1)}\end{pmatrix}" target="_blank"><img src="https://render.githubusercontent.com/render/math?math=KAD=log_{2}\begin{pmatrix}\frac{c%2Bm}{m(n%2B1)}\end{pmatrix}" alt="image" style="border: 0px;"></a></p>
<p>where,&nbsp;<em>c</em>&nbsp;is the count of a k-mer from reads,&nbsp;<em>m</em>&nbsp;is the mode of counts of read k-mers, and&nbsp;<em>n</em>&nbsp;is the copy of the k-mer in the assembly.</p><p>Address of the bookmark: <a href="https://github.com/liu3zhenlab/KAD" rel="nofollow">https://github.com/liu3zhenlab/KAD</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/9327/jarvis%E2%80%99-laboratory</guid>
  <pubDate>Tue, 18 Mar 2014 18:53:47 -0500</pubDate>
  <link></link>
  <title><![CDATA[Jarvis’ laboratory]]></title>
  <description><![CDATA[
<p>Dr. Jarvis’ laboratory studies the neurobiology of vocal communication. We want to know how the brain generates, perceives, and learns behavior. We use vocal communication as a model behavior. Emphasis is placed on the molecular pathways involved in the perception and production of learned vocalizations. We use an integrative approach that combines behavioral, anatomical, electrophysiological, and molecular biological techniques. The main animal model used is songbirds, one of the few vertebrate groups that evolved the ability to learn vocalizations. The overall goal of the research is to advance knowledge of the neural mechanisms for vocal learning and basic mechanisms of brain function.</p>

<p>Lab page: http://jarvislab.net/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42923/flanker</guid>
	<pubDate>Sat, 27 Feb 2021 22:04:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42923/flanker</link>
	<title><![CDATA[Flanker]]></title>
	<description><![CDATA[<p><span>Flanker, a Python package which performs alignment-free clustering of gene flanking sequences in a consistent format, allowing investigation of&nbsp;<span>mobile genetic elements (</span>MGEs) without prior knowledge of their structure.&nbsp;<span>Flanker can be flexibly parameterised to finetune outputs by characterising upstream and downstream regions separately and investigating variable lengths of flanking sequence.</span></span></p>
<p><span><img src="https://github.com/wtmatlock/flanker/raw/main/docs/frontpage.png" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="https://github.com/wtmatlock/flanker" rel="nofollow">https://github.com/wtmatlock/flanker</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

</channel>
</rss>