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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37820?offset=120</link>
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	<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>
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	<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/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/bookmarks/view/42568/breedbase-is-a-comprehensive-breeding-management-and-analysis-software</guid>
	<pubDate>Wed, 06 Jan 2021 19:45:21 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42568/breedbase-is-a-comprehensive-breeding-management-and-analysis-software</link>
	<title><![CDATA[Breedbase is a comprehensive breeding management and analysis software]]></title>
	<description><![CDATA[<p><span>Breedbase is a comprehensive breeding management and analysis software. It can be used to design field layouts, collect phenotypic information using tablets, support the collection of genotyping samples in a field, store large amounts of high density genotypic information, and provide Genomic Selection related analyses and predictions. Breedbase supports the BrAPI standard.</span></p><p>Address of the bookmark: <a href="https://breedbase.org/" rel="nofollow">https://breedbase.org/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44541/powerful-books-for-learning-data-analysis-with-r</guid>
	<pubDate>Tue, 28 May 2024 07:42:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44541/powerful-books-for-learning-data-analysis-with-r</link>
	<title><![CDATA[Powerful books for learning data analysis with R]]></title>
	<description><![CDATA[<p><span>R is powerful tool for data analysis, visualization, and machine learning. And it costs $0 to use! Here are six FREE books you can use to learn R today:</span></p>
<p><span>https://csgillespie.github.io/efficientR/</span></p>
<p><span>https://r-graphics.org/</span></p>
<p><span>https://rstudio-education.github.io/hopr/</span></p>
<p><span>https://r-pkgs.org/</span></p>
<p><span>https://r4ds.had.co.nz/</span></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://r-graphics.org/" rel="nofollow">https://r-graphics.org/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/9429/srf-vacancy-at-nipgr</guid>
  <pubDate>Tue, 25 Mar 2014 19:20:44 -0500</pubDate>
  <link></link>
  <title><![CDATA[SRF Vacancy at NIPGR]]></title>
  <description><![CDATA[
<p>Applications are invited from suitable candidates for filling up the purely temporary position of one Senior Research Fellow in DST’s Indo-Australian Joint project (with ICRISAT) entitled “Genomic Approach for Stress Tolerant Chickpea” under the guidance of Dr. Mukesh Jain, Scientist, NIPGR.</p>

<p>(A) Senior Research Fellow (One Post):    Emoluments as per DST/DBT norms.</p>

<p>Candidates having M.Sc. degree (with minimum of 55% marks) or equivalent in Life Sciences/Biotechnology/Bioinformatics/ Molecular Biology or any other related field with minimum of two years of post M.Sc. research experience are eligible to apply. The candidate having computer skill (Linux, Perl, Java, MySQL) and/or experience in advanced molecular biology, next generation sequencing data analysis and molecular markers analysis will be preferred.</p>

<p>The position is completely on temporary basis and co-terminus with the project. The initial appointment will be for one year, which can be curtailed/extended on the basis of assessment of the candidate’s performance and discretion of the Competent Authority. NIPGR reserves the right to select the candidate against the above posts depending upon the qualifications and experience of the candidates. Reservation of posts shall be as per Govt. of India norms.</p>

<p>Eligible candidates may apply by sending hard copy of completed application in the given format with a cover letter showing interest and attested copies of the certificates and proof of research experience. The applications should reach at the address given below within 15 days from the date of the advertisement. The subject line on envelope must be superscribed by “Application for the Post of SRF in DST - AISRF project”.</p>

<p>Note: ONLY hard copy of the application in the given format will be accepted.</p>

<p>Last date April 03, 2014</p>

<p>Dr. Mukesh Jain<br />Staff Scientist<br />National Institute of Plant Genome Research<br />Aruna Asaf Ali Marg, P.O. Box NO. 10531,<br />New Delhi - 110067</p>

<p>Advertisement: http://www.nipgr.res.in/careers/vacancies_latest.php#</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41678/gridss-the-genomic-rearrangement-identification-software-suite</guid>
	<pubDate>Sun, 17 May 2020 10:27:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41678/gridss-the-genomic-rearrangement-identification-software-suite</link>
	<title><![CDATA[GRIDSS: the Genomic Rearrangement IDentification Software Suite]]></title>
	<description><![CDATA[<p>GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements. GRIDSS includes a genome-wide break-end assembler, as well as a structural variation caller for Illumina sequencing data. GRIDSS calls variants based on alignment-guided positional de Bruijn graph genome-wide break-end assembly, split read, and read pair evidence.</p><p>Address of the bookmark: <a href="https://github.com/PapenfussLab/gridss" rel="nofollow">https://github.com/PapenfussLab/gridss</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33506/bedops-v2426-high-performance-genomic-feature-operations</guid>
	<pubDate>Mon, 12 Jun 2017 10:11:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33506/bedops-v2426-high-performance-genomic-feature-operations</link>
	<title><![CDATA[BEDOPS v2.4.26: high-performance genomic feature operations]]></title>
	<description><![CDATA[<p><strong>BEDOPS v2.4.26</strong> is a suite of tools to address common questions raised in genomic studies &mdash; mostly with regard to overlap and proximity relationships between data sets. It aims to be scalable and flexible, facilitating the efficient and accurate analysis and management of large-scale genomic data.</p>
<p>The <a href="https://bedops.readthedocs.io/en/latest/content/overview.html#overview">overview</a> section of the <strong>BEDOPS v2.4.26</strong> documentation summarizes the toolkit, functionality and performance enhancements. The <a href="https://bedops.readthedocs.io/en/latest/index.html#reference">reference</a> table offers documentation for all applications and scripts.</p><p>Address of the bookmark: <a href="https://github.com/bedops/bedops" rel="nofollow">https://github.com/bedops/bedops</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34549/kraken-a-universal-genomic-coordinate-translator-for-comparative-genomics</guid>
	<pubDate>Thu, 07 Dec 2017 04:45:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34549/kraken-a-universal-genomic-coordinate-translator-for-comparative-genomics</link>
	<title><![CDATA[kraken: A universal genomic coordinate translator for comparative genomics]]></title>
	<description><![CDATA[<p><span>If you planning on conducting a study involving dozens of large genomes, then you do not have to run all pairwise synteny alignments .. simply try&nbsp;kraken: A universal genomic coordinate translator for comparative genomics</span></p><p>Address of the bookmark: <a href="https://github.com/nedaz/kraken" rel="nofollow">https://github.com/nedaz/kraken</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36907/higlass-a-tool-for-exploring-genomic-contact-matrices-and-tracks</guid>
	<pubDate>Mon, 11 Jun 2018 09:44:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36907/higlass-a-tool-for-exploring-genomic-contact-matrices-and-tracks</link>
	<title><![CDATA[HiGlass: a tool for exploring genomic contact matrices and tracks.]]></title>
	<description><![CDATA[HiGlass is a tool for exploring genomic contact matrices and tracks. Please take a look at the examples and documentation for a description of the ways that it can be configured to explore and compare contact matrices. To load private data, HiGlass can be run locally within a Docker container. The HiC data in the examples below is from Rao et al. (2014)

http://higlass.io/<p>Address of the bookmark: <a href="http://higlass.io/" rel="nofollow">http://higlass.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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