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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27076?offset=370</link>
	<atom:link href="https://bioinformaticsonline.com/related/27076?offset=370" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/33794/senior-bioinformatics-software-developer-hyderabad-telangana</guid>
  <pubDate>Mon, 03 Jul 2017 10:10:31 -0500</pubDate>
  <link></link>
  <title><![CDATA[Senior Bioinformatics Software Developer, Hyderabad, Telangana]]></title>
  <description><![CDATA[
<p>DuPont Pioneer is the world leader in plant biotechnology area including discovery, development and delivery of elite crop genetics. DuPont Pioneer is aggressively building Big Data and Predictive Analytics capabilities in order to deliver improved services to our customers. We are currently seeking Senior Bioinformatics Software Developer at the DuPont Knowledge Center in Hyderabad, India for our global Data Science and Informatics group. At DuPont Pioneer, you’ll become part of a work environment that nurtures your interests, ignites your passion, creates opportunities to serve and helps you attain success–both personally and professionally. The hiring level will be commensurate with the level of experience. This is a critical position with the potential to make immediate, significant impact on our business.<br />The successful candidate will have an extensive background in computer science and bioinformatics through courses or academic degrees, and proven experience in bioinformatics software development. We are looking for those creative, smart, model driven, agile individuals who enjoy giving their all to tackle diverse software needs.<br />Duties / Responsibilities</p>

<p>Job Qualifications<br />Education and Experience<br />•	Master Degree in Bioinformatics, Computational biology, Scientific Computing or related field <br />•	3-5 years of Post-Master’s experience in Bioinformatics software development <br />•	Proven experience developing high throughput bioinformatics applications<br />Required Competencies<br />•	Strong proven experience in Python programming language in Linux environment<br />•	Proven High Performance computing experience (LSF/SGE/OGE)<br />•	Exposure in code versioning and repository management (GIT/SVN)<br />•	Proven experience in Bioinformatics algorithm development<br />•	Deep understanding in Bioinformatics tools, data types<br />Desired Competencies<br />•	Familiarity working in a scientific computing environment (NumPy, SciPy, Pandas etc.)<br />•	Familiarity working with Cloud technologies (AWS, Azure)<br />•	Ability to demonstrate solid analytical skills and exceptional attention to detail.<br />•	Experience in relational databases and data structures<br />•	Proven experience working with teams using agile software development methodologies and processes<br />•	Familiarity with Service Oriented Architecture (SOA)<br />•	Familiarity with build tools (Jenkins, make, ANT, Maven)<br />•	Exposure to project management tools (JIRA, Confluence, RED MINE, etc.)</p>

<p>More at http://careers.dupont.com/jobsearch/job-details/senior-bioinformatics-software-developer/012939W-01/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/34375/the-10th-north-east-bioinformatics-network-nebinet-annual-coordinators-meet</guid>
	<pubDate>Sat, 18 Nov 2017 15:02:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/34375/the-10th-north-east-bioinformatics-network-nebinet-annual-coordinators-meet</link>
	<title><![CDATA[The 10th North East Bioinformatics Network (NEBINet) Annual Coordinators' Meet]]></title>
	<description><![CDATA[<p>The 10th North East Bioinformatics Network (NEBINet) Annual Coordinators' Meet organised by the Bioinformatics Centre, St Edmund's College, Shillong and sponsored by the Department of Biotechnology, Government of India, was held at St Edmund's College Auditorium here on Thursday. Meghalaya Governor Ganga Prasad graced the inaugural programme as chief guest. <br />In his inaugural address, the Governor said the panorama of scientific scenario has greatly changed over the years, the thrust areas have undergone a metamorphosis but the conceptual underpinning of the basic sciences still continues. <br />"Of late, the activity of basic research has been intricately intertwined with technology. And we are determined to carry forward this change, for it is through technology that science can actually reach the masses in our country and afar, and the changing times have also inculcated a culture of cross-departmental and interdisciplinary research. Science and technology has always played a pivotal role in taking a nation towards greater heights by ways of innovations and inventions," he added. <br />Prasad also hoped that discussions, suggestions and sharing of innovative ideas during the two-day 10th NEBINet Annual Coordinators' Meet will open up new avenues to make substantial advancement in Biological Sciences which will provide a platform for proper and effective delivery mechanism for the common man. <br />During the inaugural function, Advisor of Department of Biotechnology Dr T Madhan Mohan gave an overview of the NEBINet and Bioinformatics programme. <br />President of Epygen Biotech FZ LLC, Dubai, UAE, Dr Debayan Ghosh, delivered the keynote address. <br />St Edmund's College governing body secretary Brother Simon Coelho and St Edmund's College Principal Dr Sylvanus Lamare also spoke during the function.</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36897/gmcloser-closing-gaps-in-assemblies-accurately-with-a-likelihood-based-selection-of-contig-or-long-read-alignments</guid>
	<pubDate>Mon, 11 Jun 2018 05:43:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36897/gmcloser-closing-gaps-in-assemblies-accurately-with-a-likelihood-based-selection-of-contig-or-long-read-alignments</link>
	<title><![CDATA[GMcloser: closing gaps in assemblies accurately with a likelihood-based selection of contig or long-read alignments]]></title>
	<description><![CDATA[GMcloser uses likelihood-based classifiers calculated from the alignment statistics between scaffolds, contigs and paired-end reads to correctly assign contigs or long reads to gap regions of scaffolds, thereby achieving accurate and efficient gap closure. We demonstrate with sequencing data from various organisms that the gap-closing accuracy of GMcloser is 3–100-fold higher than those of other available tools, with similar efficiency.

https://academic.oup.com/bioinformatics/article/31/23/3733/209212<p>Address of the bookmark: <a href="https://academic.oup.com/bioinformatics/article/31/23/3733/209212" rel="nofollow">https://academic.oup.com/bioinformatics/article/31/23/3733/209212</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/34916/bioinformatics-tools-developed-for-oxford-nanopore-data-analysis</guid>
	<pubDate>Wed, 27 Dec 2017 20:47:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/34916/bioinformatics-tools-developed-for-oxford-nanopore-data-analysis</link>
	<title><![CDATA[Bioinformatics tools developed for Oxford Nanopore data analysis !]]></title>
	<description><![CDATA[<p><span>MinION is the only portable real-time device for DNA and RNA&nbsp;</span><span>sequencing</span><span>. Each consumable flow cell can now generate 10&ndash;20 Gb of DNA&nbsp;</span><span>sequence</span><span>&nbsp;data. Ultra-</span><span>long read lengths are possible (hundreds of kb) as you can choose your fragment length.&nbsp;</span>One of the technical advantages of ONT data is the read length, which offers great prospects for genome assembly. Generally, assemblers are based on several different types of algorithms, such as greedy, overlap-layout-consensus (OLC), de Bruijn graph (DBG), and string graph.</p><p><span>List of analysis tools developed for Oxford Nanopore data</span></p><p>BWA <br />Fast nanopore data tuned alignment tool <br />https://github.com/lh3/bwa</p><p>GraphMap<br />Mapper for long and error-prone reads<br />https://github.com/isovic/graphmap</p><p>LAST<br />Nanopore tuned alignment tool<br />http://last.cbrc.jp/</p><p>LINKS<br />Software tool for long read scaffolding <br />https://github.com/warrenlr/LINKS/</p><p>marginAlign<br />Tools to align nanopore reads to a reference<br />https://github.com/benedictpaten/marginAlign</p><p>minoTour<br />Real time analysis tools<br />http://minotour.nottingham.ac.uk/</p><p>nanoCORR<br />Error-correction tool for nanopore sequence data<br />https://github.com/jgurtowski/nanocorr</p><p>NanoOK<br />Software for nanopore data, quality and error profiles<br />https://documentation.tgac.ac.uk/display/NANOOK/NanoOK</p><p>Nanopolish<br />Nanopore analysis and genome assembly software<br />https://github.com/jts/nanopolish</p><p>nanopore<br />Variant-detection tool for nanopore sequence data<br />https://github.com/mitenjain/nanopore</p><p>Nanocorrect<br />Error-correction tool for nanopore sequence data<br />https://github.com/jts/nanocorrect/</p><p>npReader<br />Real-time conversion and analysis of nanopore reads<br />https://github.com/mdcao/npReader</p><p>poRe<br />Tool for analyzing and visualizing nanopore data<br />https://sourceforge.net/p/rpore/wiki/Home/</p><p>PoreSeq<br />Error-correction and variant-calling software<br />https://github.com/tszalay/poreseq</p><p>Poretools<br />Nanopore sequence analysis and visualization software <br />https://github.com/arq5x/poretools</p><p>SSPACE-LongRead<br />Genome scaffolding tool <br />http://www.baseclear.com/genomics/bioinformatics/basetools/SSPACE-longread</p><p>SMIS<br />Genome scaffolding tool <br />https://sourceforge.net/projects/phusion2/files/smis/</p><p>&nbsp;</p><p>List of assemblers for Oxford Nanopore MinION long reads</p><p>LQS<br />DALIGNER, Celera OLC Nanocorrect, <br />Nanopolish corrector<br />https://github.com/jts/nanopolish</p><p>PBcR<br />HGAP or BLASR, Celera OLC <br />PBcR corrector<br />http://wgs-assembler.sourceforge.net/wiki/index.php/PBcR<br /> &ndash;<br />Canu<br />MHAP, Celera OLC <br />Canu corrector<br />https://github.com/marbl/canu</p><p>Falcon<br />String graph, Celera OLC <br />Falcon corrector<br />https://github.com/PacificBiosciences/falcon</p><p>Miniasm <br />OLC<br />https://github.com/lh3/miniasm</p><p>ra-integrate<br />OLC<br />https://github.com/mariokostelac/ra-integrate/</p><p>ALLPATHS-LG<br />de Bruijn graph <br />ALLPATHS-L corrector<br />https://www.broadinstitute.org/software/allpaths-lg/blog/?page_id=12</p><p>SPAdes <br />de Bruijn graph <br />SPAdes corrector<br />http://bioinf.spbau.ru/spades</p>]]></description>
	<dc:creator>biogeek</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38316/simba-a-genome-assembly-project-management-system</guid>
	<pubDate>Thu, 29 Nov 2018 08:52:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38316/simba-a-genome-assembly-project-management-system</link>
	<title><![CDATA[SIMBA: a Genome Assembly Project Management System]]></title>
	<description><![CDATA[<p><span>SIMBA</span><span>, SImple Manager for Bacterial Assemblies, is a Web interface for managing assembly projects of bacterial genomes. SIMBA was created to assist bioinformaticians to assemble bacterial genomes sequenced with NextGeneration Sequencing (NGS) platforms quickly, easily and effectively. SIMBA also is open source tool, i.e., can be freely downloaded, shared and modified.</span></p><p>Address of the bookmark: <a href="http://ufmg-simba.sourceforge.net/" rel="nofollow">http://ufmg-simba.sourceforge.net/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/35552/the-brent-lab</guid>
  <pubDate>Fri, 09 Feb 2018 10:55:27 -0600</pubDate>
  <link></link>
  <title><![CDATA[The Brent Lab]]></title>
  <description><![CDATA[
<p>The Brent Lab is developing and applying computational methods for mapping gene regulation networks, modeling them quantitatively, and engineering new behaviors into them.</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40573/de-novo-genome-assembly-for-illumina-data</guid>
	<pubDate>Mon, 20 Jan 2020 05:13:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40573/de-novo-genome-assembly-for-illumina-data</link>
	<title><![CDATA[De novo Genome Assembly for Illumina Data]]></title>
	<description><![CDATA[<p>Written and maintained by <a href="mailto:simon.gladman@unimelb.edu.au">Simon Gladman</a> - Melbourne Bioinformatics (formerly VLSCI)</p>
<p>Protocol Overview / Introduction</p>
<p>In this protocol we discuss and outline the process of de novo assembly for small to medium sized genomes.</p>
<p>https://www.melbournebioinformatics.org.au/tutorials/tutorials/assembly/assembly-protocol/</p><p>Address of the bookmark: <a href="https://www.melbournebioinformatics.org.au/tutorials/tutorials/assembly/assembly-protocol/" rel="nofollow">https://www.melbournebioinformatics.org.au/tutorials/tutorials/assembly/assembly-protocol/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36197/bioinformatics-oneliner</guid>
	<pubDate>Tue, 10 Apr 2018 04:13:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36197/bioinformatics-oneliner</link>
	<title><![CDATA[Bioinformatics OneLiner]]></title>
	<description><![CDATA[<p>To remove all line ends (\n) from a Unix text file:</p><pre>sed ':a;N;$!ba;s/\n//g' filename.txt &gt; newfilename_oneline.txt</pre><p>To get average for a column of numbers (here the second column $2):</p><pre>awk '{ sum += $2; n++ } END { if (n &gt; 0) print sum / n; }'</pre><p>To get sequence length for all sequences in a fasta file:</p><pre>awk '/^&gt;/ {if (seqlen){print seqlen}; print ;seqlen=0;next; } { seqlen = seqlen +length($0)}END{print seqlen}' \<br />filename.fasta</pre><p>To copy (move, rename, etc) files based on their list in a text file:</p><pre>cat file_list.txt | while read line; do cp "$line" complete_dataset/"$line"; done</pre><p>To split bam files into sets with mapped and unmapped reads:</p><pre>samtools view -F4 sample.bam &gt; sample.mapped.sam<br />samtools view -f4 sample.bam &gt; sample.unmapped.sam</pre><p>To gzip all your fastq files using gnu parallel and gzip:</p><pre>parallel gzip ::: *.fastq</pre><p>To gzip all your fastq files using pigz:</p><pre>pigz *.fastq</pre><p>To count all sequences in a fasta file:</p><pre>grep "^&gt;" yourfile.fasta -c</pre><p>To count all sequences in all fasta files in your current directory:</p><pre>for a in *.fasta; do ls $a; grep "^&gt;" -c $a; done</pre><p>To keep only one copy of duplicated lines:</p><pre>awk '!seen[$0]++'</pre><p>To sum assembly size from SPAdes contigs.fasta or scaffolds.fasta file:</p><pre>grep "^&gt;" scaffolds.fasta | cut -f 4 -d '_' | paste -sd+ | bc</pre><p>To remove everything after the first space at each line, e.g. to to simplify fasta headers:</p><pre>cut -d' ' -f1 &lt; your_file</pre><p>To count reads in a all .fastq.gz files in your current folder (fast, using gnu parallel):</p><pre>parallel "echo {} &amp;&amp; gunzip -c {} | wc -l | awk '{d=\$1; print d/4;}'" ::: *.gz</pre><p>To count reads in a all .fastq.gz files in your current folder:</p><pre>zcat *.gz | echo $((`wc -l`/4))</pre><p>To count reads in a all .fastq files in your current folder:</p><pre>cat *.fastq | echo $((`wc -l`/4))</pre><p>To count base pairs in a all .fastq.gz files in your current folder:</p><pre>zcat *.fastq.gz | paste - - - - | cut -f 2 | tr -d '\n' | wc -c </pre><p>To split multifasta file into many fasta files:</p><pre>awk '/^&gt;/ {OUT=substr($0,2) ".fa"}; {print &gt;&gt; OUT; close(OUT)}' Input_File</pre><p>To convert Illumina FASTQ 1.3 to 1.8:</p><pre>sed -e '4~4y/@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\]^_`abcdefghi/!"#$%&amp;'\''()*+,-.\/0123456789:;&lt;=&gt;?@ABCDEFGHIJ/' f.fastq</pre><p>To convert FASTQ to FASTA:</p><pre>sed -n '1~4s/^@/&gt;/p;2~4p' </pre><p>To get fastq read length distribution:</p><pre>cat reads.fastq | awk '{if(NR%4==2) print length($1)}' | sort | uniq -c</pre><p>To deinterleave interleaved fastq file:</p><pre>cat myf.fq | paste - - - - - - - - | tee &gt;(cut -f 1-4 | tr "\t" "\n" &gt; myfile_1.fq) | cut -f 5-8 | \<br />tr "\t" "\n" &gt; myf2.fq </pre><p>To filter and sort contig identifiers from SPAdes assembly (e.g. here lenght &gt;= 4000 + coverage &gt;=100):</p><pre>grep "^&gt;" scaffolds.fasta | sed s"/_/ /"g | awk '{ if ($4 &gt;= 4000 &amp;&amp; $6 &gt;= 100) print $0 }' | sort -k 4 -n | \<br />sed s"/ /_/"g</pre><p>To append something to all headers of your fasta files:</p><pre>sed 's/&gt;.*/&amp;YOURSTRING/' filename.fasta &gt; new_filename.fasta</pre><p>To replace/squeeze multiple adjacent spaces by only one space:&nbsp;</p><pre>tr -s " " &lt; file</pre><p>To filter fastq based on length (here larger than or equal to 21, but smaller than or equal to 25.</p><pre>cat your.fastq | paste - - - - | awk 'length($2)&nbsp; &gt;= 21 &amp;&amp; length($2) &lt;= 25' | sed 's/\t/\n/g' &gt; filtered.fastq</pre><p>To print difference between the last and first row in 5th column:</p><pre>awk '{if (!first){first=$5;}; last=$5;} END {print last-first}' myfile.txt</pre><p>To sample only 200 first bases from all sequences in a multifasta file (e.g. from assembly scaffolds.fasta file here):</p><pre>awk '/^&gt;/{ seqlen=0; print; next; } seqlen &lt; 200 { if (seqlen + length($0) &gt; 200) $0 = substr($0, 1, 200-seqlen);\<br /> seqlen += length($0); print }' scaffolds.fasta &gt; 200bp_scaffolds.fasta</pre><p>&nbsp;To pipe a compressed fasta file directly into makeblastdb.</p><pre>gunzip -c fasta.gz | makeblastdb -in -</pre><p>To remove sequences with duplicate fasta headers from a fasta file.</p><pre>awk '/^&gt;/{f=!d[$1];d[$1]=1}f' in.fasta &gt; out.fasta</pre>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/42626/spades-team-announce-new-version-spades-v315</guid>
	<pubDate>Fri, 15 Jan 2021 10:24:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/42626/spades-team-announce-new-version-spades-v315</link>
	<title><![CDATA[SPADes team announce new version SPADes v3.15]]></title>
	<description><![CDATA[<p>New SPAdes 3.15.0.0. announced by the SPADes team This release includes such new features as:&nbsp;<br />- CoronaSPAdes pipeline for the assembly of transcriptomic and metatranscriptomic data of full-length coronaviridae genomes;&nbsp;<br />- Meta-Viral and RNA-Viral pipelines for metagenomic and metatranscriptomic data defining viral genomes;&nbsp;<br />-New trusted contiguous use algorithm;&nbsp;<br />-Switched to the memory allocator mimalloc;&nbsp;<br />- PlasmidSPAdes and bgcSPAdes are now provided as an input assembly graph;&nbsp;<br />- Important improvements and corrections to the metaplasmid pipeline;&nbsp;<br />- Multiple performance improvements in procedures for simplification and repeat resolving.&nbsp;<br />Please, consider updating.</p><p>Check out more at&nbsp;https://cab.spbu.ru/software/spades/</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36384/binding-site-prediction-in-protein</guid>
	<pubDate>Wed, 25 Apr 2018 04:35:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36384/binding-site-prediction-in-protein</link>
	<title><![CDATA[Binding Site Prediction in Protein !]]></title>
	<description><![CDATA[<p><span>The interaction between proteins and other molecules is fundamental to all biological functions. In this section we include tools that can assist in prediction of interaction sites on protein surface and tools for predicting the structure of the intermolecular complex formed between two or more molecules (docking).</span></p><h4>Pockets Identification</h4><p><a href="http://sts.bioengr.uic.edu/castp/" target="_blank">CASTp</a></p><div style="text-align: justify;">Automatic Identification of pockets and cavities in proteins structure, and quantitation of their volumes using Delaunay triangulation. Available also as PyMOL plugin</div><p><a href="http://www.bioinformatics.leeds.ac.uk/pocketfinder/" target="_blank">Pocket-Finder</a></p><div style="text-align: justify;">Automatic identification of pockets and cavities in proteins structure, and quantitation of their volumes.</div><p><a href="http://gecco.org.chemie.uni-frankfurt.de/pocketpicker/index.html" target="_blank">PocketPicker</a></p><div style="text-align: justify;">Grid-based technique for the analysis of protein pockets. PocketPicker available as a plugin for&nbsp;<a href="https://bip.weizmann.ac.il/toolbox/structure/pymol.htm">PyMOL</a></div><div style="text-align: justify;">&nbsp;</div><div style="text-align: justify;"><h4>Binding Site Prediction</h4>
<p><a href="http://consurf.tau.ac.il/" target="_blank">ConSurf</a></p>
</div><div style="text-align: justify;">&nbsp;</div><div style="text-align: justify;">Identification of functional regions in proteins by surface-mapping of phylogenetic information</div><div style="text-align: justify;">&nbsp;</div><div style="text-align: justify;"><a href="http://www-cryst.bioc.cam.ac.uk/~crescendo/crescendo.php" target="_blank">CRESCENDO</a></div><div style="text-align: justify;">&nbsp;</div><div style="text-align: justify;">Identification protein interaction sites. It uses sequence conservation patterns in homologous proteins to distinguish between residues that are conserved due to structural restraints from those due to functional restraints.&nbsp;&nbsp;</div><div style="text-align: justify;">&nbsp;</div><div style="text-align: justify;"><strong>Ligand Binding Sites</strong></div><div style="text-align: justify;">&nbsp;</div><div style="text-align: justify;"><a href="http://www.sbg.bio.ic.ac.uk/~3dligandsite/" target="_blank">3DLigandSite</a></div><div style="text-align: justify;">&nbsp;</div><div style="text-align: justify;">The server utilizes protein-structure prediction to provide structural models of the binding site. Ligands bound to structures are superimposed onto the model and use to predict the binding site.</div><div style="text-align: justify;">&nbsp;</div><div style="text-align: justify;">F<a href="http://cssb.biology.gatech.edu/skolnick/files/FINDSITE/" target="_blank">INDSITE</a></div><div style="text-align: justify;">&nbsp;</div><div style="text-align: justify;">A threading-based method for ligand-binding site prediction and functional annotation based on binding-site similarity across superimposed groups of threading templates.</div><div style="text-align: justify;">&nbsp;</div><div style="text-align: justify;">
<p><a href="http://scoppi.biotec.tu-dresden.de/pocket/" target="_blank">LIGSITE<sup>csc</sup></a></p>
<div style="text-align: justify;">&nbsp;</div><div style="text-align: justify;">Prediction of binding site by pocket identification using the Connolly surface and degree of conservation</div>
<p><a href="http://metapocket.eml.org/" target="_blank"></a></p>
</div><div style="text-align: justify;">&nbsp;</div><div style="text-align: justify;"><a href="http://metapocket.eml.org/" target="_blank">metaPocket</a>A meta server for ligand-binding site prediction. metaPocket use&nbsp;<a href="https://bip.weizmann.ac.il/toolbox/structure/binding.htm#ligsite">LIGSITE<sup>csc</sup></a>,&nbsp;<a href="https://bip.weizmann.ac.il/toolbox/structure/binding.htm#pass">PASS</a>,&nbsp;<a href="https://bip.weizmann.ac.il/toolbox/structure/binding.htm#qsite">Q-SiteFinder</a>&nbsp;and&nbsp;<a href="http://www.biochem.ucl.ac.uk/~roman/surfnet/surfnet.html" target="_blank">SURFNET</a></div>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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