<?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/32465?offset=690</link>
	<atom:link href="https://bioinformaticsonline.com/related/32465?offset=690" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34569/ksnp30-snp-detection-and-phylogenetic-analysis-of-genomes-without-genome-alignment-or-reference-genome</guid>
	<pubDate>Fri, 08 Dec 2017 16:48:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34569/ksnp30-snp-detection-and-phylogenetic-analysis-of-genomes-without-genome-alignment-or-reference-genome</link>
	<title><![CDATA[kSNP3.0: SNP detection and phylogenetic analysis of genomes without genome alignment or reference genome]]></title>
	<description><![CDATA[<p><span>Sept. 20, 2017 Version 3.1 released. Major upgrade. Version 3.1 fixes the problems with SNP annotation that arose when NCBI discontinued use of GI numbers. Please read carefully the Preface (page 3) and the File of annotated genomes section (pages 9-10) in the version 3.1 User Guide. Thanks to Tom Slezak for revsing the get_genbank_file3 script and to Tod Stuber (USDA) for testing version 3.1 even though he doesn't need the annotation feature. All users are encouraged to upgrade to version 3.1.&nbsp;<br></span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/ksnp/files/" rel="nofollow">https://sourceforge.net/projects/ksnp/files/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42308/icmr-scientist-jobs-for-biotechlife-sciencebiology-bioinformatics</guid>
  <pubDate>Tue, 10 Nov 2020 18:45:49 -0600</pubDate>
  <link></link>
  <title><![CDATA[ICMR Scientist Jobs For Biotech/Life Science/Biology &amp; Bioinformatics]]></title>
  <description><![CDATA[
<p>CMR welcomes on-line applications up to 5th December 2020 till 5:30 PM to fill out the vacancies of 42 Scientist’ E’ (Medical), 01 Scientist ‘E’ (Non-Medical), 16 Scientist ‘D’ (Medical) and also 06 Scientist ‘D’ (Non-Medical) from Indian Citizens for appointment on regular basis under Direct Recruitment with all India transfer liability under the Council.</p>

<p>Post I</p>

<p>Name of the Post: Scientist-E (Non-Medical)</p>

<p>Number of positions: One</p>

<p>Upper Age limit: 50 years</p>

<p>Post II</p>

<p>Name of the Post: Scientist-D (Non-Medical)</p>

<p>Number of positions: Six</p>

<p>Upper Age limit: 45 years</p>

<p>Fee:</p>

<p>Application Fee of Rs. 1500/- (Rupees one thousand five hundred only) is needed. SC / ST / Women/ PWD/ EWS applicants are exempted from application fee. Application Fee is to be paid by candidates through online web link given up the application. Application fees when paid will certainly not be reimbursed under any situations.</p>

<p>How to apply:</p>

<p>i) Candidates should apply online on https://recruit.icmr.org.in. A separate application needs to be submitted for every post, with the required application fee.</p>

<p>ii) Following self-attested documents are required to be uploaded together with the application:<br />a) Proof of Date of Birth.<br />b) Educational qualifications.<br />c) Experience.</p>

<p>More at https://recruit.icmr.org.in/assets/uploads/advertisement/ICMR_Advertisement_06112020.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35292/pgap-x-extension-on-pan-genome-analysis-pipeline</guid>
	<pubDate>Tue, 23 Jan 2018 11:41:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35292/pgap-x-extension-on-pan-genome-analysis-pipeline</link>
	<title><![CDATA[PGAP-X: Extension on pan-genome analysis pipeline]]></title>
	<description><![CDATA[<p>PGAP-X is a microbial comparative genomic analysis platform with graphic interface. Serials of algorithms and methodologies have been developed and integrated to analyze and visualize genomics structure variation, gene distribution with different conservative levels, and genetic variation from pan-genome sight. At the same time, analytical result data from many other programs, including genome alignment result and orthologs clusters, are also supported to be further analyzed or visualized in PGAP-X. The workflow and feature snapshot in PGAP-X were shown as Fig.1 and Fig.2.</p>
<div><img src="https://pgapx.ybzhao.com/image/f1.jpg" alt="image" style="border: 0px; border: 0px;"></div>
<div>&nbsp;</div>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://pgapx.ybzhao.com/" rel="nofollow">https://pgapx.ybzhao.com/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42499/galaxy-training-resources</guid>
	<pubDate>Sun, 27 Dec 2020 05:28:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42499/galaxy-training-resources</link>
	<title><![CDATA[Galaxy Training Resources !]]></title>
	<description><![CDATA[<p>Welcome to Galaxy Training!</p>
<p>Collection of tutorials developed and maintained by the worldwide Galaxy community</p>
<table>
<thead>
<tr><th>Topic</th><th>Tutorials</th></tr>
</thead>
<tbody>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/introduction/">Introduction to Galaxy Analyses</a></td>
<td>10</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/assembly/">Assembly</a></td>
<td>6</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/climate/">Climate</a></td>
<td>3</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/computational-chemistry/">Computational chemistry</a></td>
<td>6</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/ecology/">Ecology</a></td>
<td>6</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/epigenetics/">Epigenetics</a></td>
<td>6</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/genome-annotation/">Genome Annotation</a></td>
<td>3</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/imaging/">Imaging</a></td>
<td>3</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/metabolomics/">Metabolomics</a></td>
<td>4</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/metagenomics/">Metagenomics</a></td>
<td>7</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/proteomics/">Proteomics</a></td>
<td>18</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/sequence-analysis/">Sequence analysis</a></td>
<td>2</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/statistics/">Statistics and machine learning</a></td>
<td>8</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/transcriptomics/">Transcriptomics</a></td>
<td>23</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/variant-analysis/">Variant Analysis</a></td>
<td>8</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/visualisation/">Visualisation</a></td>
<td>2</td>
</tr>
</tbody>
</table>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://training.galaxyproject.org/training-material/" rel="nofollow">https://training.galaxyproject.org/training-material/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36730/bprna-large-scale-automated-annotation-and-analysis-of-rna-secondary-structure</guid>
	<pubDate>Wed, 23 May 2018 03:24:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36730/bprna-large-scale-automated-annotation-and-analysis-of-rna-secondary-structure</link>
	<title><![CDATA[bpRNA: large-scale automated annotation and analysis of RNA secondary structure]]></title>
	<description><![CDATA[<p>bpRNA, a novel annotation tool capable of parsing RNA structures, including complex pseudoknot-containing RNAs, to yield an objective, precise, compact, unambiguous, easily-interpretable description of all loops, stems, and pseudoknots, along with the positions, sequence, and flanking base pairs of each such structural feature.</p>
<p>The bpRNA code is written in perl and requires the Graph perl module. Several additional scripts for analysis are included. The source code is available at http://github.com/hendrixlab/bpRNA.</p><p>Address of the bookmark: <a href="http://github.com/hendrixlab/bpRNA" rel="nofollow">http://github.com/hendrixlab/bpRNA</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42801/scientist-position-in-structural-bioinformatics-at-lonza</guid>
  <pubDate>Wed, 03 Feb 2021 21:38:06 -0600</pubDate>
  <link></link>
  <title><![CDATA[Scientist position in Structural Bioinformatics at Lonza]]></title>
  <description><![CDATA[
<p>Lonza (https://www.lonza.com/) are seeking a highly motivated and skilled (Senior) Scientist with experience in Structure-based Protein Engineering and Bioinformatics to join Lonza's Applied Protein Services (APS) Bioinformatics team based in Cambridge, UK.</p>

<p>More at https://instruct-eric.eu/jobs/scientist-position-in-structural-bioinformatics-at-lonza-cambridge-uk/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40298/environment-for-tree-exploration-ete-is-a-python-programming-toolkit-that-assists-in-the-recontruction-manipulation-analysis-and-visualization-of-phylogenetic-trees</guid>
	<pubDate>Wed, 27 Nov 2019 05:32:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40298/environment-for-tree-exploration-ete-is-a-python-programming-toolkit-that-assists-in-the-recontruction-manipulation-analysis-and-visualization-of-phylogenetic-trees</link>
	<title><![CDATA[Environment for Tree Exploration (ETE) is a Python programming toolkit that assists in the recontruction, manipulation, analysis and visualization of phylogenetic trees]]></title>
	<description><![CDATA[<p><span>The Environment for Tree Exploration (ETE) is a Python programming toolkit that assists in the recontruction, manipulation, analysis and visualization of phylogenetic trees (although clustering trees or any other tree-like data structure are also supported).</span></p>
<p><span>Other tools</span></p>
<p><span><a href="https://github.com/shenwei356/taxonkit">https://github.com/shenwei356/taxonkit</a></span></p>
<p>&nbsp;</p>
<ul>
<li>ETE, version:&nbsp;<a href="https://pypi.org/project/ete3/3.1.1/">3.1.1</a></li>
<li>BioPython, version:&nbsp;<a href="https://pypi.org/project/biopython/1.73/">1.73</a></li>
<li>taxadb, version:&nbsp;<a href="https://pypi.org/project/taxadb/0.9.0">0.10.1</a></li>
<li>TaxonKit, version:&nbsp;<a href="https://github.com/shenwei356/taxonkit/releases/tag/0.10.1">0.5.0</a></li>
</ul><p>Address of the bookmark: <a href="https://pypi.org/project/ete3/3.1.1/" rel="nofollow">https://pypi.org/project/ete3/3.1.1/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/42814/bioinformatics-in-africa-part6-sudan</guid>
	<pubDate>Sat, 06 Feb 2021 21:20:59 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/42814/bioinformatics-in-africa-part6-sudan</link>
	<title><![CDATA[Bioinformatics in Africa: Part6 - Sudan]]></title>
	<description><![CDATA[<p>Commission&nbsp;for&nbsp;Biotechnology&nbsp;&amp;&nbsp;Genetic&nbsp;Engineering&nbsp;&shy;&nbsp;Khartoum: The&nbsp;Commission&nbsp;for&nbsp;Biotechnology&nbsp;and&nbsp;Genetic&nbsp;Engineering&nbsp;was&nbsp;established&nbsp;in&nbsp;9/2/1993&nbsp;as&nbsp; research&nbsp;unit.&nbsp;In&nbsp;addition&nbsp;to&nbsp;research&nbsp;activities&nbsp;it&nbsp;acts&nbsp;as&nbsp;focal&nbsp;point&nbsp;for&nbsp;the&nbsp;International&nbsp;Center&nbsp;for&nbsp; Biotechnology&nbsp;and&nbsp;Genetic&nbsp;Engineering. The&nbsp;commission&nbsp;conducts&nbsp;researches&nbsp;in&nbsp;order&nbsp;to&nbsp;play&nbsp;a&nbsp;part&nbsp;in&nbsp;solving&nbsp;economical,&nbsp;environmental,&nbsp; health&nbsp;and&nbsp;nutritional&nbsp;problems&nbsp;using&nbsp;modern&nbsp;research&nbsp;techniques&nbsp;with&nbsp;an&nbsp;emphasis&nbsp;on&nbsp;the&nbsp;applied&nbsp; researches&nbsp;in&nbsp;these&nbsp;areas. The&nbsp;laboratories&nbsp;were&nbsp;well&nbsp;furnished&nbsp;with&nbsp;the&nbsp;essential&nbsp;equipments&nbsp;and&nbsp;the&nbsp;catalyst&nbsp;infrastructure&nbsp;to&nbsp; facilitate&nbsp;emergence&nbsp;of&nbsp;a&nbsp;successful&nbsp;for&nbsp;research.&nbsp;The&nbsp;Commission&nbsp;equipped&nbsp;with&nbsp;a&nbsp;computer&nbsp;center&nbsp; and&nbsp;information&nbsp;to&nbsp;serve&nbsp;as&nbsp;informatics&nbsp;and&nbsp;Digital&nbsp;library.</p><p>Research&nbsp;Interest&nbsp;and&nbsp;Activities: 1. Plant&nbsp;Genetic&nbsp;Transformations<br />2. Molecular&nbsp;Population&nbsp;Genetics 3. Detection&nbsp;of&nbsp;human&nbsp;and&nbsp;Animals&nbsp;diseases 4. Breast&nbsp;Cancer&shy;specific&nbsp;protein&nbsp;marker 5. Phytochemical 6. Genomic&nbsp;map 7. Bioremediation 8. Tissue&nbsp;Culture.</p><p>Web&nbsp;site&nbsp;and&nbsp;links: www.geocity.cbge.com</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41006/netgo-r-shiny-package-for-network-integrated-pathway-enrichment-analysis</guid>
	<pubDate>Wed, 12 Feb 2020 12:40:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41006/netgo-r-shiny-package-for-network-integrated-pathway-enrichment-analysis</link>
	<title><![CDATA[netGO: R-Shiny package for network-integrated pathway enrichment analysis]]></title>
	<description><![CDATA[<p>netGO is an R/Shiny package for network-integrated pathway enrichment analysis.<br>netGO provides user-interactive visualization of enrichment analysis results and related networks.</p>
<p>Currently, netGO supports analysis for four species (<em><a href="https://github.com/unistbig/netGO-Data/tree/master/Human">Human</a>,&nbsp;<a href="https://github.com/unistbig/netGO-Data/tree/master/Mouse">Mouse</a>,&nbsp;<a href="https://github.com/unistbig/netGO-Data/tree/master/Arabidopsis">Arabidopsis thaliana</a>,and&nbsp;<a href="https://github.com/unistbig/netGO-Data/tree/master/Yeast">Yeast</a></em>)<br>These data are available from&nbsp;<a href="https://github.com/unistbig/netGO-Data">netGO-Data</a>&nbsp;repository.</p>
<p><a href="https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa077/5728635">https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa077/5728635</a></p><p>Address of the bookmark: <a href="https://github.com/unistbig/netGO" rel="nofollow">https://github.com/unistbig/netGO</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43262/bioinformatics-research-scientist-oklahoma-state-university-osu</guid>
  <pubDate>Tue, 17 Aug 2021 13:24:39 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Research Scientist @ Oklahoma State University (OSU)]]></title>
  <description><![CDATA[
<p>This position is an early career research scientist in the area of Bioinformatics to support research projects involving faculty and staff, at Oklahoma State University (OSU). This is a highly technical position that requires a strong research background in biomedical or life sciences, including a high level of expertise with bioinformatics algorithms, databases, and analyses with a focus on next-generation sequence data. Although most of the projects will deal directly with the analysis of DNA and RNA sequence data the individual should be well versed in other types of data sources as well (i.e., microarrays) and handling of large datasets (using data analytics, machine learning, and deep learning techniques). </p>

<p>More at https://okstate.csod.com/ats/careersite/JobDetails.aspx?site=8&amp;id=9874</p>
]]></description>
</item>

</channel>
</rss>