<?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/44002?offset=290</link>
	<atom:link href="https://bioinformaticsonline.com/related/44002?offset=290" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12594/faculty-positions-at-central-university-of-punjab</guid>
  <pubDate>Mon, 07 Jul 2014 23:33:33 -0500</pubDate>
  <link></link>
  <title><![CDATA[Faculty Positions at Central University of Punjab]]></title>
  <description><![CDATA[
<p>Faculty Positions: Rolling/Open Advertisement Advt.No: T-10 (2013)</p>

<p>Pay Scale: Pay Band Rs.15600-39100 with AGP of Rs.6,000/-</p>

<p>Essential Qualifications for Professors, Associate Professors, and Assistant Professors: As per “UGC REGULATIONS ON MINIMUM QUALIFICATIONS FOR APPOINTMENT OF TEACHERS AND OTHER ACADEMIC STAFF IN UNIVERSITIES AND COLLEGES AND MEASURES FOR THE MAINTENANCE OF STANDARDS IN HIGHER EDUCATION 2010“ and the 2nd Amendments to the regulation issued in June 2013.</p>

<p>For details: http://www.ugc.ac.in/oldpdf/regulations/revised_finalugcregulationfinal10.pdf http://www.ugc.ac.in/pdfnews/8539300_English.pdf and University rules.</p>

<p>Procedure to apply:</p>

<p>Application forms along with API form complete in all respect along with necessary documents and application fee of Rs. 500/-. (Rs. 250/- for Scheduled Caste/Scheduled Tribe/Person with disabilities) should be sent to:</p>

<p>Registrar, Central University of Punjab, City Campus, Mansa Road, Bathinda-151001</p>

<p>For more info visit: http://www.centralunipunjab.com/Teaching/Final%20Details-t10-2013.pdf, http://www.centralunipunjab.com/Teaching/Advertisement-t10-2013.jpg</p>

<p>Last Apply Date: 31 Dec 2014</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/35429/list-of-visualization-tools-for-genome-alignments</guid>
	<pubDate>Fri, 02 Feb 2018 13:25:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/35429/list-of-visualization-tools-for-genome-alignments</link>
	<title><![CDATA[List of visualization tools for genome alignments]]></title>
	<description><![CDATA[<p><span>Genome</span><span>&nbsp;browsers are useful not only for showing final results but also for improving analysis protocols, testing data quality, and generating result drafts. Its integration in analysis pipelines allows the optimization of parameters, which leads to better results. But sometime, we need publication ready figure of genomes. Following are the list of genome alignment visualization tools, which could be useful for analysis and&nbsp;interpretation of results:</span></p><p>ABySS Explorer</p><p>Interactive Java application that uses a novel graph-based representation to display a sequence assembly and associated metadata</p><p>http://www.bcgsc.ca/platform/bioinfo/software/abyss-explorer</p><p>BamView</p><p>Genome browser and annotation tool that allows visualization of sequence features, next-generation sequencing (NGS) data and the results of analyses within the context of the sequence, and also its six-frame translation</p><p>http://www.sanger.ac.uk/resources/software/artemis/</p><p>DNannotator&nbsp;</p><p>Annotation web toolkit for regional genomic sequences</p><p>http://bioapp.psych.uic.edu/DNannotator.htm</p><p>JVM&nbsp;</p><p>Java Visual Mapping tool for NGS reads</p><p>http://www.springer.com/cda/content/document/cda_downloaddocument/9789401792448-c2.pdf?SGWID=0-0-45-1487072-p176815501</p><p>LookSeq&nbsp;</p><p>Web-based visualization of sequences derived from multiple sequencing technologies. Low- or high-depth read pileups and easy visualization of putative single nucleotide and structural variation</p><p>http://lookseq.sourceforge.net</p><p>MagicViewer&nbsp;</p><p>Visualization of short read alignment, identification of genetic variation and association with annotation information of a reference genome</p><p>http://bioinformatics.zj.cn/magicviewer/</p><p>MapView&nbsp;</p><p>Alignments of huge-scale single-end and pair-end short reads</p><p>http://omictools.com/mapview-s1367.html</p><p>MultiPipMaker</p><p>Computes alignments of similar regions in two DNA sequences. The resulting alignments are summarized with a &lsquo;percent identity plot&rsquo; (pip)</p><p>http://pipmaker.bx.psu.edu/pipmaker/</p><p>PileLineGUI&nbsp;</p><p>Handling genome position files in NGS studies</p><p>http://sing.ei.uvigo.es/pileline/pilelinegui.html</p><p>SAMtools tview&nbsp;</p><p>Simple and fast text alignment viewer; NGS compatible</p><p>http://www.htslib.org/</p><p>SEWAL</p><p>Uses a locality-sensitive hashing algorithm to enumerate all unique sequences in an entire Illumina sequencing run</p><p>http://www.sourceforge.net/projects/sewal</p><p>STAR&nbsp;</p><p>A web-based integrated solution to management and visualization of sequencing data</p><p>http://wanglab.ucsd.edu/star/browser</p><p>SVA&nbsp;</p><p>Software for annotating and visualizing sequenced human genomes</p><p>http://www.svaproject.org</p><p>Viewer (IGV)&nbsp;</p><p>Visualization of large heterogeneous datasets, providing a smooth and intuitive user experience at all levels of genome resolution</p><p>https://www.broadinstitute.org/igv/</p><p>ZOOM Lite&nbsp;</p><p>NGS data mapping and visualization software</p><p>http://bioinfor.com/zoom/lite/</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/12787/integrative-genomics-viewer-igv-tutorial</guid>
	<pubDate>Sat, 12 Jul 2014 15:16:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/12787/integrative-genomics-viewer-igv-tutorial</link>
	<title><![CDATA[Integrative Genomics Viewer (IGV) tutorial]]></title>
	<description><![CDATA[<p>The <a href="http://www.broadinstitute.org/igv/">Integrative Genomics Viewer (IGV)</a> from the Broad Center allows you to view several types of data files involved in any NGS analysis that employs a reference genome, including how reads from a dataset are mapped, gene annotations, and predicted genetic variants.</p>
<p>http://www.broadinstitute.org/igv/</p><p>Address of the bookmark: <a href="https://wikis.utexas.edu/display/bioiteam/Integrative+Genomics+Viewer+%28IGV%29+tutorial" rel="nofollow">https://wikis.utexas.edu/display/bioiteam/Integrative+Genomics+Viewer+%28IGV%29+tutorial</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36842/gap-filling-or-contigs-extensions-tools</guid>
	<pubDate>Fri, 01 Jun 2018 08:07:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36842/gap-filling-or-contigs-extensions-tools</link>
	<title><![CDATA[Gap filling or Contigs extensions tools !]]></title>
	<description><![CDATA[
<p>There are many tools to perform gap filling using Illumina short reads, for example "GapFiller: a de novo assembly approach to fill the gap within paired reads" or "Toward almost closed genomes with GapFiller". There are also some tools like GAPresolution that can help to perform local re-assemblies using 454 reads. We used GAPresolution but it is not a very good software, it is useful only in some specific situations.</p>

<p>Take a look at the PRICE software from the DeRisi lab. Its meant to do something very similar. http://derisilab.ucsf.edu/index.php?page=software</p>

<p>You could also look at SSPACE (http://www.baseclear.com/landingpages/basetools-a-wide-range-of-bioinformatics-solutions/sspacev12/), ATLAS tools (http://www.hgsc.bcm.tmc.edu/content/bcm-hgsc-software), and SCARPA (http://compbio.cs.toronto.edu/hapsembler/scarpa.html).</p>

<p>See the PAGIT protocol: http://www.sanger.ac.uk/resources/software/pagit/ </p>

<p>In particular, take a look at the IMAGE tool: http://genomebiology.com/2010/11/4/R41 </p>

<p>Also SOAPdenovo has ha function for scaffolding. Not sure about ABYSS</p>

<p>Here there is a useful explanation of several tools.</p>

<p>https://bioinformaticsonline.com/search?q=scaffolding&amp;entity_type=object&amp;entity_subtype=bookmarks&amp;offset=0&amp;search_type=entities</p>

<p>I could be wrong, but the above answers to your hypothetical scenario appear to miss the point that you aren't interested in assembling the full genome, just the 100 kb part you're interested in. I suggest the following algorithm:</p>

<p>1. Start with the initial assembly C0 of the contigs you have identified as overlapping your region of interest, and the set S of reads those contigs contain. Let C = C0.</p>

<p>2. Repeat:<br />a. Identify paired-end reads (not in C) for which one or both ends align within, or extending, contigs in C.<br />b. Identify unpaired reads that align extending these new paired-end reads.<br />c. Construct a new assembly C' from C and the new reads identified in (a) and (b).<br />d. Trim C' so it does not extend more than 100 kb to either end of C0. Set C = C'.<br />e. Let S' denote the reads that contribute to C'. If S' does not contain any reads not present in S, stop. Otherwise, Set S = S'.</p>

<p>3. If you don't have a complete assembly of the region of interest, generate an STS for each end of each contig, probe a library for clones including these STSes, subclone these clones into a paired-end sequencing vector, and generate paired-end reads for this library; then try steps (1) and (2) again, adding these new sequencing reads to what you had before.</p>

<p>4. If your average sequencing depth for the region of interest exceeds 25 or so without filling all gaps, it is likely that the remaining gaps represent sequences that are not getting cloned in your sequencing vectors. Try different sequencing vectors.</p>
]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/12963/cosmos-our-workflow-management-system-for-ngs-data</guid>
	<pubDate>Wed, 23 Jul 2014 07:29:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/12963/cosmos-our-workflow-management-system-for-ngs-data</link>
	<title><![CDATA[COSMOS, our workflow management system for NGS data]]></title>
	<description><![CDATA[<p><strong>COSMOS</strong>, our Python-based management system for implementing large-scale parallel workflows focusing on, but not restricted to, large-scale short-read "NGS" sequencing data is open-access published via <a href="http://bioinformatics.oxfordjournals.org/content/early/2014/06/29/bioinformatics.btu385.abstract">Advance Access</a> in <em>Bioinformatics</em> (<a href="http://scholar.harvard.edu/lancaster/publications/cosmos-python-library-massively-parallel-workflows">Gafni et al. 2014</a>).&nbsp; It is also available for download for non-commercial academic and research purposes at:</p>
<p><strong>&nbsp;<a href="http://cosmos.hms.harvard.edu/">http://cosmos.hms.harvard.edu/</a></strong>.</p><p>Address of the bookmark: <a href="https://cosmos.hms.harvard.edu/" rel="nofollow">https://cosmos.hms.harvard.edu/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38743/molinspiration-broad-range-of-cheminformatics-software-tools-supporting-molecule-manipulation</guid>
	<pubDate>Sun, 20 Jan 2019 05:32:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38743/molinspiration-broad-range-of-cheminformatics-software-tools-supporting-molecule-manipulation</link>
	<title><![CDATA[molinspiration: broad range of cheminformatics software tools supporting molecule manipulation]]></title>
	<description><![CDATA[<p><span>Molinspiration offers&nbsp;</span><a href="https://www.molinspiration.com/products.html">broad range of cheminformatics software tools</a><span>&nbsp;supporting molecule manipulation and processing, including SMILES and SDfile conversion, normalization of molecules, generation of tautomers, molecule fragmentation, calculation of various molecular properties needed in QSAR, molecular modelling and drug design, high quality molecule depiction, molecular database tools supporting substructure and similarity searches. Our products support also fragment-based virtual screening, bioactivity prediction and data visualization. Molinspiration tools are written in Java, therefore can be used practically on any computer platform.</span></p><p>Address of the bookmark: <a href="https://www.molinspiration.com/" rel="nofollow">https://www.molinspiration.com/</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/12995/national-center-for-bioinformatics-ncb</guid>
  <pubDate>Wed, 23 Jul 2014 14:10:49 -0500</pubDate>
  <link></link>
  <title><![CDATA[National Center for Bioinformatics (NCB)]]></title>
  <description><![CDATA[
<p>NCB is offering M.Phil and Ph.D programs in the area of Bioinformatics. The major goal of NCB is to promote quality training and research in the area of Bioinformatics. Bioinformatics originated as a cross-disciplinary field as the need for computational sections to research problem raised in biomedicine. </p>

<p>More at http://ncb.qau.edu.pk/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41559/dahak-benchmarking-and-containerization-of-tools-for-analysis-of-complex-non-clinical-metagenomes</guid>
	<pubDate>Thu, 09 Apr 2020 04:56:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41559/dahak-benchmarking-and-containerization-of-tools-for-analysis-of-complex-non-clinical-metagenomes</link>
	<title><![CDATA[Dahak: benchmarking and containerization of tools for analysis of complex non-clinical metagenomes.]]></title>
	<description><![CDATA[<p><span>Dahak is a software suite that integrates state-of-the-art open source tools for metagenomic analyses. Tools in the dahak software suite will perform various steps in metagenomic analysis workflows including data pre-processing, metagenome assembly, taxonomic and functional classification, genome binning, and gene assignment. We aim to deliver the analytical framework as a robust and reliable containerized workflow system, which will be free from dependency, installation, and execution problems typically associated with other open-source bioinformatics solutions. This will maximize the transparency, data provenance (i.e., the process of tracing the origins of data and its movement through the workflow), and reproducibility.</span></p>
<p><span>More at&nbsp;<a href="https://dahak-metagenomics.github.io/dahak/">https://dahak-metagenomics.github.io/dahak/</a></span></p><p>Address of the bookmark: <a href="https://github.com/dahak-metagenomics/dahak" rel="nofollow">https://github.com/dahak-metagenomics/dahak</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/13276/senior-research-fellow-at-nit-rourkela</guid>
  <pubDate>Wed, 30 Jul 2014 00:53:13 -0500</pubDate>
  <link></link>
  <title><![CDATA[Senior Research Fellow at NIT, Rourkela]]></title>
  <description><![CDATA[
<p>NATIONAL INSTITUTE OF TECHNOLOGY, ROURKELA – 769 008(ORISSA)<br />SPONSORED RESEARCH, INDUSTRIAL CONSULTANCY &amp; CONTINUING EDUCATION</p>

<p>ADVERTISEMENT NO: NITR/SR/CH-BIF/2014/30</p>

<p>Applications are invited on prescribed format for the following assignment in a purely time bound research project undertaken in the Department of Biotechnology &amp; Medical Engineering of the Institute.</p>

<p>1. Name of the Temporary Post : Senior Research Fellow-01<br />2. Name of the Research Project: “ Bioinformatics Infrastructure Facility (BIF)”<br />3. Name of the Sponsoring Agency: DBT, Government of India, 4 Tenure of the Project : 12th Five year Plan<br />5 Tenure of the Assignment : 01 year [Likely to be extended for 04 more years]<br />6 Job Description : BIF Maintenance and Active Research in Bioinformatics<br />7. Consolidated monthly compensation / Fellowship: Rs.18,000/- P.M.</p>

<p>8. Essential Qualifications and experience: B.Tech with valid GATE Score or M.Tech degree in Biotechnology/Bioinformatics/Computer Science/Computational Biology<br />9. Desirable Qualifications/ Experiences: Experience of Programming in PERL,R, Python, Unix and Visual Studio + Knowledge in NGS data analysis work flows ,WGS and statistical packages such as CRAN-R,MATLAB etc.</p>

<p>10. Accommodation : Bachelor accommodation in the Institute may be provided subject to availability.<br />11. For technical information on the project, the candidate may contact the Principal Investigator at the following address:</p>

<p>Name : Prof. Mukesh K Gupta<br />Address : Dept. of Biotechnology &amp; Medical Engineering,<br />N.I.T.Rourkela-769 008<br />Telephone No : 0661-2462294<br />E-mail : guptam@nitrkl.ac.in</p>

<p>Eligible persons may apply in the prescribed format (available in the Institute Website)affixed with coloured photographs to be submitted in duplicate along with photo copies of relevant certificates, grade/ mark sheets, publications etc., to Asst. Registrar, SRICCE,<br />National Institute of Technology, Rourkela–769 008 before 22.08.2014. The cover should be super- scribed clearly the post applied for &amp; Name of the Project.</p>

<p>Mere possession of minimum qualification does not guarantee invitation to the interview.<br />Candidates will be short listed based on merit and need of the project.</p>

<p>Advertisement:</p>

<p>http://www.nitrkl.ac.in/IntraWeb/Jobs_Tenders/Jobs/ProjectFellowship/2014/141707192838_1.pdf</p>
]]></description>
</item>
<item>
	<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>
</item>

</channel>
</rss>