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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44703?offset=380</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/17898/ensembl-77-has-been-released</guid>
	<pubDate>Sun, 05 Oct 2014 16:38:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/17898/ensembl-77-has-been-released</link>
	<title><![CDATA[Ensembl 77 has been released!]]></title>
	<description><![CDATA[<h3>New updates in e!77 !!</h3><ul>
<li>Updated&nbsp;<a href="http://e77.ensembl.org/Homo_sapiens/Info/Index" title="Human species page">human</a>&nbsp;gene set (GENCODE 21)</li>
<li>Updated <a href="http://e77.ensembl.org/Rattus_norvegicus/Info/Index">rat</a> gene set&nbsp;including manual annotation from HAVANA</li>
<li>New species:&nbsp;<a href="http://e77.ensembl.org/Chlorocebus_sabaeus/Info/Index">Vervet-African green monkey</a></li>
<li>Imported Transcript Support Levels (TSLs) from UCSC&nbsp;for&nbsp;<a href="http://e77.ensembl.org/Homo_sapiens/Info/Index">human</a>&nbsp;and&nbsp;<a href="http://e77.ensembl.org/Mus_musculus/Info/Index">mouse</a></li>
<li>Imported <a href="http://appris.bioinfo.cnio.es/" target="_blank" title="APPRIS">APPRIS</a> flag for&nbsp;<a href="http://e77.ensembl.org/Homo_sapiens/Info/Index">human</a> and <a href="http://e77.ensembl.org/Mus_musculus/Info/Index">mouse</a></li>
<li>Updated <a href="http://e77.ensembl.org/Poecilia_formosa/Info/Index" title="Amazon molly">Amazon molly</a> gene set</li>
</ul><p>Find more at http://www.ensembl.info/blog/2014/10/02/ensembl-77-has-been-released/</p>]]></description>
	<dc:creator>Seema Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41937/merqury-evaluate-genome-assemblies-with-k-mers</guid>
	<pubDate>Fri, 03 Jul 2020 19:29:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41937/merqury-evaluate-genome-assemblies-with-k-mers</link>
	<title><![CDATA[merqury: Evaluate genome assemblies with k-mers]]></title>
	<description><![CDATA[<p><span>Often, genome assembly projects have illumina whole genome sequencing reads available for the assembled individual. The k-mer spectrum of this read set can be used for independently evaluating assembly quality without the need of a high quality reference. Merqury provides a set of tools for this purpose.</span></p>
<p><span>More at&nbsp;<a href="https://www.biorxiv.org/content/10.1101/2020.03.15.992941v1.full">https://www.biorxiv.org/content/10.1101/2020.03.15.992941v1.full</a></span></p><p>Address of the bookmark: <a href="https://github.com/marbl/merqury" rel="nofollow">https://github.com/marbl/merqury</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/17926/orange-bioinformatics-2534</guid>
	<pubDate>Mon, 06 Oct 2014 12:51:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/17926/orange-bioinformatics-2534</link>
	<title><![CDATA[Orange-Bioinformatics 2.5.34]]></title>
	<description><![CDATA[<p>Orange Bioinformatics extends <a href="http://orange.biolab.si/">Orange</a>, a data mining software package, with common functionality for bioinformatics. The provided functionality can be accessed as a Python library or through a visual programming interface (Orange Canvas). The latter is also suitable for non-programmers.</p>
<p>Orange Bioinformatics provides access to publicly available data, like GEO data sets, Biomart, GO, KEGG, Atlas, ArrayExpress, and PIPAx database. As for the analytics, there is gene selection, quality control, scoring distances between experiments with multiple factors. All features can be combined with powerful visualization, network exploration and data mining techniques from the Orange data mining framework.</p><p>Address of the bookmark: <a href="https://pypi.python.org/pypi/Orange-Bioinformatics/2.5.34" rel="nofollow">https://pypi.python.org/pypi/Orange-Bioinformatics/2.5.34</a></p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42936/ancient-whole-genome-duplication-wgd-detection-tools</guid>
	<pubDate>Sun, 07 Mar 2021 00:32:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42936/ancient-whole-genome-duplication-wgd-detection-tools</link>
	<title><![CDATA[Ancient whole genome duplication (WGD) detection tools !]]></title>
	<description><![CDATA[<p>There are two methods for ancient WGD detection, one is collinearity analysis, and the other is based on the Ks distribution map. Among them, Ks is defined as the average number of synonymous substitutions at each synonymous site, and there is also a Ka corresponding to it, which refers to the average number of non-synonymous substitutions at each non-synonymous site.</p><p>At present, some people have posted articles about the analysis process of WGD. I searched for the keyword "wgd pipeline" and found the following:</p><p><strong>GenoDup: https:// github.com/MaoYafei/GenoDup-Pipeline</strong><br /><strong>https://peerj.com/articles/6303/</strong><br /><strong>WGDdetector: https:// github.com/yongzhiyang2 012/WGDdetector</strong><br /><strong>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2670-3</strong><br /><strong>wgd: https:// github.com/arzwa/wgd</strong><br /><strong>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1142-2#Sec1</strong><br /><strong>https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-017-0399-x</strong><br /><strong>GeNoGAP https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1142-2</strong><br /><strong>https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-017-0399-x</strong><br /><strong>https://github.com/dfguan/purge_dups</strong><br /><strong>https://www.biorxiv.org/content/10.1101/2020.01.24.917997v1</strong></p><p>This article introduces the usage of wgd.</p><p>Wgd cannot be installed directly with bioconda at present, so it is a little troublesome to install, because it depends on a lot of software. wgd depends on the following software</p><p><strong>BLAST</strong><br /><strong>MCL</strong><br /><strong>MUSCLE/MAFFT/PRANK</strong><br /><strong>PAML</strong><br /><strong>PhyML/FastTree</strong><br /><strong>i-ADHoRe</strong></p><p>But the good news is that most of the software it depends on can be installed with bioconda</p><blockquote><p>conda create -n wgd python=3.5 blast mcl muscle mafft prank paml fasttree cmake libpng mpi=1.0=mpich<br />conda activate wgd</p></blockquote><p>Here mpi=1.0=mpich is selected, because i-adhore depends on mpich. If openmpi is installed, an error will appear while loading shared libraries: libmpi_cxx.so.40: cannot open shared object file: No such file or directory</p><p>After that, the installation is much simpler</p><blockquote><p>git clone https://github.com/arzwa/wgd.git<br />cd wgd<br />pip install .<br />pip install git+https://github.com/arzwa/wgd.git<br />For i-ADHoRe, you need to register at http:// bioinformatics.psb.ugent.be /webtools/i-adhore/licensing/Agree to the license to download i-ADHoRe-3.0</p></blockquote><p>Since my miniconda3 installed ~/opt/, the installation path is so~/opt/miniconda3/envs/wgd/</p><blockquote><p>tar -zxvf i-adhore-3.0.01.tar.gz<br />cd i-adhore-3.0.01<br />mkdir -p build &amp;&amp; cd build<br />cmake .. -DCMAKE_INSTALL_PREFIX=~/opt/miniconda3/envs/wgd/<br />make -j 4 <br />make insatall</p></blockquote><p>Take the sugarcane genome Saccharum spontaneum L as an example. The genome is 8-ploid with 32 chromosomes (2n = 4x8 = 32)</p><p><strong>Download the tutorial for CDS and GFF annotation files</strong></p><blockquote><p><strong>mkdir -p wgd_tutorial &amp;&amp; cd wgd_tutorial</strong><br /><strong>wget http://www.life.illinois.edu/ming/downloads/Spontaneum_genome/Sspon.v20190103.cds.fasta.gz</strong><br /><strong>wget http://www.life.illinois.edu/ming/downloads/Spontaneum_genome/Sspon.v20190103.gff3.gz</strong><br /><strong>gunzip *.gz</strong></p></blockquote><p>First conda activate wgdstart our analysis environment, and then start the analysis</p><p>Step 1 : Use to wgd mclidentify homologous genes in the genome</p><blockquote><p>wgd mcl -n 20 --cds --mcl -s Sspon.v20190103.cds.fasta -o Sspon_cds.out</p></blockquote><p>Step 2 : Use to wgd ksdbuild Ks distribution</p><blockquote><p>wgd ksd --n_threads 80 Sspon_cds.out/Sspon.v20190103.cds.fasta.blast.tsv.mcl Sspon.v20190103.cds.fasta</p></blockquote><p>Step 3 : If the quality of the genome is good, then wgd syncollinearity analysis can be used . It can help us find the collinearity block in the genome and the corresponding anchor point</p><blockquote><p>wgd syn --feature gene --gene_attribute ID \<br /> -ks wgd_ksd/Sspon.v20190103.cds.fasta.ks.tsv \<br /> Sspon.v20190103.gff3 Sspon_cds.out/Sspon.v20190103.cds.fasta.blast.tsv.mcl</p></blockquote><p>&nbsp;For more reading - There are 9 sub-modules in WGD</p><ul>
<li><span>kde: KDE fitting to the Ks distribution</span></li>
<li><span>ksd: Ks distribution construction</span></li>
<li><span>mcl: BLASP comparison of All-vs-ALl + MCL classification analysis.</span></li>
<li><span><span>mix: Hybrid modeling of Ks distribution.</span></span></li>
<li><span>pre: preprocess the CDS file</span></li>
<li><span>syn: Call I-ADHoRe 3.0 to use GFF files for collinearity analysis</span></li>
<li><span>viz: draw histogram and density plot</span></li>
<li><span>wf1: Ks standard analysis procedure of the whole genome paranome (paranome), call mcl, ksd and syn</span></li>
<li><span>wf2: Ks standard analysis procedure of one-vs-one homologous gene (ortholog), call wcl and kSD</span></li>
</ul>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/18380/jrfsrf-at-university-of-hyderabad</guid>
  <pubDate>Fri, 17 Oct 2014 01:55:44 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF/SRF at University of Hyderabad]]></title>
  <description><![CDATA[
<p>Applications are invited for the following post of Junior Research Fellow (temporary position coterminous with the project) under DBT funded research project on ““Understanding the functions of α1β1γ1/α2β1γ1 selective AMPK Modulators in dissecting the pharmacological role of these isozymes in metabolic diseases”</p>

<p>Qualified and interested candidates can send their curriculum vitae by e-mail to hr@drils.org on or before 27th October 2014 mention in the subject line of the mail the following code: AMPK-Biology.</p>

<p>Selected candidates will be called for a personal interview to Dr. Reddy’s Institute of Life Sciences, University of Hyderabad Campus, Gachibowli, Hyderabad. The selected candidate is expected to report within two weeks from the date of selection to start work on the project.</p>

<p>Junior Research Fellowship (Molecular Modeling/Biology) for two years and Senior Research fellowship for one year</p>

<p>Junior Research Fellowship: Rs. 15,600/- (consolidated) per month for first two years.<br />Senior Research Fellowship: Rs. 18,200/-(consolidated) per month for the 3rd year.</p>

<p>Duration: The duration of the fellowship is for three years. However, the performance of the candidate will be reviewed after the completion of every year and the fellowship will be renewed only upon satisfactory performance.</p>

<p>Responsibilities:</p>

<p>1) Literature search.<br />2) Design, plan and execute experiments under the supervision of the scientist.<br />3) Provide scientific support to the scientist in his/her research activities.<br />4) Book keeping and maintenance of stocks and consumables.</p>

<p>Essential Qualifications:</p>

<p>Required: M.Sc. in Microbiology/Biotechnology/Bioinformatics or any other related branch of basic Sciences from a recognized university/institute with a consistent academic record of minimum 60% aggregate in all qualifying examinations. The candidate should be NET qualified for lectureship. The candidate should be motivated to work with dedication.</p>

<p>Desirable: expertise/experience in both Molecular Modeling and Molecular Biology.</p>

<p>Experience: 0-2 years in the areas of Molecular Modeling and/or Molecular Biology and cell biology and Biochemistry.</p>

<p>Preferable: Relevant research experience as evident from thesis/dissertation/project work.</p>

<p>Advertisement: http://www.ilsresearch.org/userfiles/Junior%20REsearch%20Fellowship%20-%20AMPK(Biology).pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43112/calling-variants-in-non-diploid-systems</guid>
	<pubDate>Sat, 26 Jun 2021 15:37:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43112/calling-variants-in-non-diploid-systems</link>
	<title><![CDATA[Calling variants in non-diploid systems]]></title>
	<description><![CDATA[<p><span>The main challenge associated with non-diploid variant calling is the difficulty in distinguishing between the sequencing noise (abundant in all NGS platforms) and true low frequency variants. Some of the early attempts to do this well have been accomplished on human mitochondrial&nbsp;</span><span>DNA</span><span>&nbsp;although the same approaches will work equally good on viral and bacterial genomes (</span><a href="https://training.galaxyproject.org/training-material/topics/variant-analysis/tutorials/non-dip/tutorial.html#Rebolledo-Jaramillo2014">Rebolledo-Jaramillo&nbsp;<em>et al.</em>&nbsp;2014</a><span>,&nbsp;</span><a href="https://training.galaxyproject.org/training-material/topics/variant-analysis/tutorials/non-dip/tutorial.html#Li2015">Li&nbsp;<em>et al.</em>&nbsp;2015</a><span>).</span></p><p>Address of the bookmark: <a href="https://training.galaxyproject.org/training-material/topics/variant-analysis/tutorials/non-dip/tutorial.html" rel="nofollow">https://training.galaxyproject.org/training-material/topics/variant-analysis/tutorials/non-dip/tutorial.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/18385/biinformamatics-lead-at-google-life-sciences</guid>
  <pubDate>Fri, 17 Oct 2014 02:24:55 -0500</pubDate>
  <link></link>
  <title><![CDATA[Biinformamatics Lead at Google Life Sciences]]></title>
  <description><![CDATA[
<p>Google Life Sciences is recruiting a technical lead with experience in bioinformatics and clinical bioinformatics, including for biomarker discovery projects such as the Baseline study.</p>

<p>Responsibilities</p>

<p>Lead teams of scientists in structuring, prototyping, and executing large-scale bioinformatic and other analysis.<br />Develop novel bioinformatics, statistical, data processing, pathway, data mining and other algorithms to identify biological signals and their clinical correlates in broad kinds of individual and population data.<br />Develop novel platform-level analytical tools for sequence-based assays (assembly, annotation, variant calling and interpretation, phasing, genome structure, etc.), expression assays (RNAseq and microarray), proteomics, and metabolomics.<br />Develop statistical models that robustly correlate complex laboratory-derived information with phenotypic and clinical information.<br />Create scientifically rigorous visualizations, communications, and presentations of results.</p>

<p>Reference @ https://www.google.com/about/careers/search#!t=jo&amp;jid=62095001</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43766/genometools-the-versatile-open-source-genome-analysis-software</guid>
	<pubDate>Wed, 02 Feb 2022 04:00:21 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43766/genometools-the-versatile-open-source-genome-analysis-software</link>
	<title><![CDATA[GenomeTools: The versatile open source genome analysis software]]></title>
	<description><![CDATA[<p>The&nbsp;<em>GenomeTools</em>&nbsp;genome analysis system is a&nbsp;<a href="http://genometools.org/license.html">free</a>&nbsp;collection of bioinformatics&nbsp;<a href="http://genometools.org/tools.html">tools</a>&nbsp;(in the realm of genome informatics) combined into a single binary named&nbsp;<em>gt</em>. It is based on a C library named &ldquo;libgenometools&rdquo; which consists of several modules.</p>
<p><img src="http://genometools.org/images/annotation.png" alt="image" style="border: 0px;"></p>
<p>If you are interested in gene prediction, have a look at&nbsp;<a href="http://genomethreader.org/" title="GenomeThreader gene prediction        software"><em>GenomeThreader</em></a>.</p>
<p>http://genometools.org/pub/</p><p>Address of the bookmark: <a href="http://genometools.org/" rel="nofollow">http://genometools.org/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/18580/faculty-positions-at-central-university-of-punjab-bathinda</guid>
  <pubDate>Wed, 22 Oct 2014 10:45:37 -0500</pubDate>
  <link></link>
  <title><![CDATA[Faculty Positions at CENTRAL UNIVERSITY OF PUNJAB, BATHINDA]]></title>
  <description><![CDATA[
<p>Advertisement No. T/NT-01 (2014)</p>

<p>Faculty Positions<br />The Central University of Punjab (CUP), Bathinda will be having the Schools and Departments as given in Table-I. The University invites applications from eligible candidates for the posts of Professors (Pay Band Rs. 37400-67000 with AGP of Rs. 10, 000/-), Associate Professors (Pay Band Rs.37400-67000 with AGP of Rs. 9,000/-) and Assistant Professors (Pay Band Rs.15600-39100 with AGP of Rs. 6,000/-)</p>

<p>POSITION AVAILABLE IN THE AREA OF SPECIALIZTION</p>

<p>3. Bioinformatics,</p>

<p>Procedure to apply: Application forms along with API form complete in all respect along with necessary documents and application fee of Rs. 750/-. (Rs. 250/- for Scheduled Caste/Scheduled Tribe/Person with disabilities) should be sent to:</p>

<p>Registrar (Officiating)<br />Central University of Punjab<br />City Campus, Mansa Road<br />Bathinda-151 001</p>

<p>Application forms from the prospective candidates are accepted upto November 10, 2014.</p>

<p>Based on the qualification of the candidates and the need of the university, the applications received will be processed through appropriately constituted selection committees shortly. Minimum qualification can be relaxed in case of exceptionally outstanding candidate. For further details visit www.cup.ac.in; www.centralunipunjab.com; www.cup.edu.in</p>

<p>The candidate should download the application form available at website www.cup.ac.in;<br />www.centralunipunjab.com; and submit it complete in all respects on or before 10th November 2014.</p>

<p>Those who have applied earlier need to submit Academic Performance Index (API) form, 5 copies of Summary of the Application Form (available at: www.cup.ac.in; www.centralunipunjab.com and Updated CV if not updated recently (without application fee).</p>

<p>http://cup.edu.in/Faculty_details_and_general_instructions.pdf</p>

<p>http://cup.edu.in/Final%20Application%20and%20summary%20Sheet%20and%20Api%20form.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43641/refseq-viraal-genome-sequences</guid>
	<pubDate>Sat, 11 Dec 2021 08:35:18 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43641/refseq-viraal-genome-sequences</link>
	<title><![CDATA[Refseq viraal genome sequences !]]></title>
	<description><![CDATA[<p>List of all viruses on NCBI&nbsp;</p>
<p>https://ftp.ncbi.nlm.nih.gov/refseq/release/viral/</p><p>Address of the bookmark: <a href="https://ftp.ncbi.nlm.nih.gov/refseq/release/viral/" rel="nofollow">https://ftp.ncbi.nlm.nih.gov/refseq/release/viral/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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