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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/34221?offset=140</link>
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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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36497/installing-python-numpy</guid>
	<pubDate>Mon, 07 May 2018 04:31:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36497/installing-python-numpy</link>
	<title><![CDATA[Installing  python-numpy !]]></title>
	<description><![CDATA[<p>$ sudo apt-get install python-numpy python-scipy python-matplotlib ipython ipython-notebook python-pandas python-sympy python-nose<br />[sudo] password for urbe: <br />Reading package lists... Done<br />Building dependency tree <br />Reading state information... Done<br />The following packages were automatically installed and are no longer required:<br /> bridge-utils containerd linux-headers-4.4.0-116 linux-headers-4.4.0-116-generic linux-headers-4.4.0-21 linux-headers-4.4.0-21-generic<br /> linux-image-4.4.0-116-generic linux-image-4.4.0-21-generic linux-image-extra-4.4.0-116-generic linux-image-extra-4.4.0-21-generic<br /> linux-signed-image-4.4.0-116-generic runc ubuntu-fan<br />Use 'sudo apt autoremove' to remove them.<br />The following additional packages will be installed:<br /> blt fonts-lyx fonts-mathjax ipython-notebook-common isympy libaec0 libamd2.4.1 libdsdp-5.8gf libglpk36 libgsl2 libhdf5-10 libjs-highlight<br /> libjs-highlight.js libjs-jquery-ui libjs-marked libjs-mathjax libjs-underscore libsz2 python-antlr python-bs4 python-chardet python-cvxopt<br /> python-cycler python-dateutil python-decorator python-glade2 python-gmpy python-html5lib python-imaging python-jdcal python-jinja2 python-joblib<br /> python-lxml python-markupsafe python-matplotlib-data python-mpmath python-numexpr python-openpyxl python-pandas-lib python-patsy python-pexpect<br /> python-pil python-ptyprocess python-py python-pycurl python-pyglet python-pymysql python-pyparsing python-pytest python-simplegeneric<br /> python-simplejson python-statsmodels python-statsmodels-lib python-sympy-doc python-tables python-tables-data python-tables-lib python-tk<br /> python-tornado python-tz python-xlrd python-xlwt python-zmq tk8.6-blt2.5 ttf-bitstream-vera<br />Suggested packages:<br /> blt-demo ipython-doc ipython-qtconsole python-pygments nodejs pandoc libiodbc2-dev libmysqlclient-dev gsl-ref-psdoc | gsl-doc-pdf | gsl-doc-info<br /> | gsl-ref-html libjs-jquery-ui-docs fonts-mathjax-extras libjs-mathjax-doc python-gtk2-doc python-genshi python-jinja2-doc python-lxml-dbg<br /> python-lxml-doc ffmpeg inkscape python-cairocffi python-configobj python-excelerator python-matplotlib-doc python-qt4 python-sip python-traits<br /> python-wxgtk3.0 ttf-staypuft python-gmpy2 python-mpmath-doc python-coverage python-nose-doc python-numpy-dbg python-numpy-doc python-pandas-doc<br /> python-patsy-doc python-pexpect-doc python-pil-doc python-pil-dbg subversion python-pytest-xdist libcurl4-gnutls-dev python-pycurl-dbg<br /> python-pycurl-doc python-pymysql-doc python-mock python-scipy-doc python-statsmodels-doc python-tables-doc python-netcdf vitables tix<br /> python-tk-dbg<br />The following NEW packages will be installed:<br /> blt fonts-lyx fonts-mathjax ipython ipython-notebook ipython-notebook-common isympy libaec0 libamd2.4.1 libdsdp-5.8gf libglpk36 libgsl2<br /> libhdf5-10 libjs-highlight libjs-highlight.js libjs-jquery-ui libjs-marked libjs-mathjax libjs-underscore libsz2 python-antlr python-bs4<br /> python-chardet python-cvxopt python-cycler python-dateutil python-decorator python-glade2 python-gmpy python-html5lib python-imaging<br /> python-jdcal python-jinja2 python-joblib python-lxml python-markupsafe python-matplotlib python-matplotlib-data python-mpmath python-nose<br /> python-numexpr python-numpy python-openpyxl python-pandas python-pandas-lib python-patsy python-pexpect python-pil python-ptyprocess python-py<br /> python-pycurl python-pyglet python-pymysql python-pyparsing python-pytest python-scipy python-simplegeneric python-simplejson python-statsmodels<br /> python-statsmodels-lib python-sympy python-sympy-doc python-tables python-tables-data python-tables-lib python-tk python-tornado python-tz<br /> python-xlrd python-xlwt python-zmq tk8.6-blt2.5 ttf-bitstream-vera<br />0 upgraded, 73 newly installed, 0 to remove and 35 not upgraded.<br />Need to get 49,5 MB of archives.<br />After this operation, 271 MB of additional disk space will be used.<br />Do you want to continue? [Y/n] Y<br />Get:1 http://be.archive.ubuntu.com/ubuntu xenial-updates/main amd64 python-pymysql all 0.7.2-1ubuntu1 [56,4 kB]<br />Get:2 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 tk8.6-blt2.5 amd64 2.5.3+dfsg-3 [574 kB]<br />Get:3 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 blt amd64 2.5.3+dfsg-3 [4.852 B]<br />Get:4 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 fonts-lyx all 2.1.4-2 [161 kB]<br />Get:5 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 fonts-mathjax all 2.6.1-1 [960 kB]<br />Get:6 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 python-decorator all 4.0.6-1 [9.326 B]<br />Get:7 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-ptyprocess all 0.5-1 [12,9 kB]<br />Get:8 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-pexpect all 4.0.1-1 [40,5 kB]<br />Get:9 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 python-simplegeneric all 0.8.1-1 [11,5 kB]<br />Get:10 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[2.252 kB]<br />Get:64 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-sympy-doc all 0.7.6.1-1 [4.774 kB]<br />Get:65 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-tables-lib amd64 3.2.2-2 [353 kB]<br />Get:66 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-tables-data all 3.2.2-2 [45,3 kB]<br />Get:67 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-tables all 3.2.2-2 [335 kB]<br />Get:68 http://be.archive.ubuntu.com/ubuntu xenial-updates/main amd64 python-tk amd64 2.7.12-1~16.04 [26,3 kB]<br />Get:69 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-xlrd all 0.9.4-1 [107 kB]<br />Get:70 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-xlwt all 0.7.5+debian1-1 [83,5 kB]<br />Get:71 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-scipy amd64 0.17.0-1 [8.733 kB]<br />Get:72 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-statsmodels-lib amd64 0.6.1-4 [173 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...<br />Setting up libglpk36:amd64 (4.57-1build3) ...<br />Setting up libgsl2:amd64 (2.1+dfsg-2) ...<br />Setting up libsz2:amd64 (0.3.2-1) ...<br />Setting up libhdf5-10:amd64 (1.8.16+docs-4ubuntu1) ...<br />Setting up python-antlr (2.7.7+dfsg-6ubuntu1) ...<br />Setting up python-bs4 (4.4.1-1) ...<br />Setting up python-chardet (2.3.0-2) ...<br />Setting up libdsdp-5.8gf (5.8-9.1ubuntu2) ...<br />Setting up python-cvxopt (1.1.4-1.4) ...<br />Setting up python-cycler (0.9.0-1) ...<br />Setting up python-dateutil (2.4.2-1) ...<br />Setting up python-glade2 (2.24.0-4ubuntu1) ...<br />Setting up python-gmpy (1.17-1) ...<br />Setting up python-html5lib (0.999-4) ...<br />Setting up python-pil:amd64 (3.1.2-0ubuntu1.1) ...<br />Setting up python-imaging (3.1.2-0ubuntu1.1) ...<br />Setting up python-jdcal (1.0-1build1) ...<br />Setting up python-joblib (0.9.4-1) ...<br />Setting up python-lxml (3.5.0-1build1) ...<br />Setting up ttf-bitstream-vera (1.10-8) ...<br />Setting up python-matplotlib-data (1.5.1-1ubuntu1) ...<br />Setting up python-pyparsing (2.0.3+dfsg1-1ubuntu0.1) ...<br />Setting up python-tz (2014.10~dfsg1-0ubuntu2) ...<br />Setting up python-numpy (1:1.11.0-1ubuntu1) ...<br />Setting up python-matplotlib (1.5.1-1ubuntu1) ...<br />Setting up python-mpmath (0.19-3) ...<br />Setting up python-nose (1.3.7-1) ...<br />Setting up python-numexpr (2.4.3-1ubuntu1) ...<br />Setting up python-openpyxl (2.3.0-1) ...<br />Setting up python-pandas-lib (0.17.1-3ubuntu2) ...<br />Setting up python-pandas (0.17.1-3ubuntu2) ...<br />Setting up python-patsy (0.4.1-2) ...<br />Setting up python-py (1.4.31-1) ...<br />Setting up python-pyglet (1.1.4.dfsg-3) ...<br />Setting up python-pytest (2.8.7-4) ...<br />Setting up python-simplejson (3.8.1-1ubuntu2) ...<br />Setting up python-sympy (0.7.6.1-1) ...<br />Setting up python-sympy-doc (0.7.6.1-1) ...<br />Setting up python-tables-lib (3.2.2-2) ...<br />Setting up python-tables-data (3.2.2-2) ...<br />Setting up python-tables (3.2.2-2) ...<br />Setting up python-tk (2.7.12-1~16.04) ...<br />Setting up python-xlrd (0.9.4-1) ...<br />Setting up python-xlwt (0.7.5+debian1-1) ...<br />Setting up python-scipy (0.17.0-1) ...<br />Setting up python-statsmodels-lib (0.6.1-4) ...<br />Setting up python-statsmodels (0.6.1-4) ...<br />Processing triggers for libc-bin (2.23-0ubuntu10) ...<br />➜ redundans git:(master) ✗ python2 redundans.py -v -i test/*_?.fq.gz -f test/contigs.fa -o test/run1<br />Options: Namespace(fasta='test/contigs.fa', fastq=['test/5000_1.fq.gz', 'test/5000_2.fq.gz', 'test/600_1.fq.gz', 'test/600_2.fq.gz'], identity=0.51, iters=2, joins=5, limit=0.2, linkratio=0.7, log=', mode 'w' at 0x7f85d1de31e0&gt;, longreads=[], mapq=10, mem=16, minLength=200, nocleaning=True, nogapclosing=True, norearrangements=False, noreduction=True, noscaffolding=True, outdir='test/run1', overlap=0.8, reference='', resume=False, threads=4, tmp='/tmp', usebwa=False, verbose=True)</p><p>##################################################<br />[Mon May 7 11:29:18 2018] Reduction...<br />#file name genome size contigs heterozygous size [%] heterozygous contigs [%] identity [%] possible joins homozygous size [%] homozygous contigs [%]<br />/usr/lib/python2.7/dist-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.<br /> warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')<br />test/run1/contigs.fa 163897 245 66377 40.50 221 90.20 94.854 0 97520 59.50 24 9.80</p><p>##################################################<br />[Mon May 7 11:29:29 2018] Estimating parameters of libraries...<br /> Aligning 19504 mates per library...<br />Insert size statistics Mates orientation stats<br />FastQ files read length median mean stdev FF FR RF RR<br />test/5000_1.fq.gz test/5000_2.fq.gz 50 4998 4990.20 721.47 0 4674 0 0<br />test/600_1.fq.gz test/600_2.fq.gz 100 599 598.63 47.68 0 10000 0 0</p><p>##################################################<br />[Mon May 7 11:29:29 2018] Scaffolding...<br /> iteration 1.1: test/run1/contigs.reduced.fa 24 97520 39.355 17 94157 7321 2195 0 29603<br /> 19505 pairs. 17302 passed filtering [88.71%]. 1627 in different contigs [8.34%].<br /> 1526 pairs. 558 in different contigs [36.57%].<br /> iteration 1.2: test/run1/_sspace.1.1.fa 3 97626 39.344 3 97626 87536 6063 821 87536<br /> 19505 pairs. 17607 passed filtering [90.27%]. 182 in different contigs [0.93%].<br /> 1077 pairs. 124 in different contigs [11.51%].<br /> iteration 2.1: test/run1/_sspace.1.2.fa 3 97626 39.344 3 97626 87536 6063 821 87536<br /> 19505 pairs. 15112 passed filtering [77.48%]. 1295 in different contigs [6.64%].<br /> 3417 pairs. 396 in different contigs [11.59%].<br /> iteration 2.2: test/run1/_sspace.2.1.fa 1 99133 39.344 1 99133 99133 99133 2328 99133<br /> 19505 pairs. 15152 passed filtering [77.68%]. 0 in different contigs [0.00%].<br /> 3398 pairs. 0 in different contigs [0.00%].</p><p>##################################################<br />[Mon May 7 11:29:34 2018] Gap closing...<br /> iteration 1.1: test/run1/scaffolds.fa 1 99133 39.344 1 99133 99133 99133 2328 99133</p><p>##################################################<br />[Mon May 7 11:29:35 2018] Final reduction...<br />#file name genome size contigs heterozygous size [%] heterozygous contigs [%] identity [%] possible joins homozygous size [%] homozygous contigs [%]<br />[WARNING] Nothing reduced!<br />test/run1/scaffolds.filled.fa 99390 1 0 0.00 0 0.00 0.000 0 99390 100.00 1 100.00</p><p>##################################################<br />[Mon May 7 11:29:35 2018] Reporting statistics...<br />#fname contigs bases GC [%] contigs &gt;1kb bases in contigs &gt;1kb N50 N90 Ns longest<br />test/contigs.fa 245 163897 40.298 24 117391 3975 233 0 29603<br />test/run1/contigs.fa 245 163897 40.298 24 117391 3975 233 0 29603<br />test/run1/contigs.reduced.fa 24 97520 39.355 17 94157 7321 2195 0 29603<br />test/run1/_sspace.1.1.fa 3 97626 39.344 3 97626 87536 6063 821 87536<br />test/run1/_sspace.1.2.fa 3 97626 39.344 3 97626 87536 6063 821 87536<br />test/run1/_sspace.2.1.fa 1 99133 39.344 1 99133 99133 99133 2328 99133<br />test/run1/_sspace.2.2.fa 1 99133 39.344 1 99133 99133 99133 2328 99133<br />test/run1/scaffolds.fa 1 99133 39.344 1 99133 99133 99133 2328 99133<br />test/run1/_gapcloser.1.1.fa 1 99390 39.689 1 99390 99390 99390 2 99390<br />test/run1/scaffolds.filled.fa 1 99390 39.689 1 99390 99390 99390 2 99390<br />test/run1/scaffolds.reduced.fa 1 99390 39.689 1 99390 99390 99390 2 99390</p><p>##################################################<br />[Mon May 7 11:29:35 2018] Cleaning-up...<br />#Time elapsed: 0:00:17.376924</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36518/mix-combining-multiple-assemblies-from-ngs-data</guid>
	<pubDate>Tue, 08 May 2018 04:58:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36518/mix-combining-multiple-assemblies-from-ngs-data</link>
	<title><![CDATA[MIX: Combining multiple assemblies from NGS data]]></title>
	<description><![CDATA[<p>Mix is a tool that combines two or more draft assemblies, without relying on a reference genome and has the goal to reduce contig fragmentation and thus speed-up genome finishing. The proposed algorithm builds an extension graph where vertices represent extremities of contigs and edges represent existing alignments between these extremities. These alignment edges are used for contig extension. The resulting output assembly corresponds to a path in the extension graph that maximizes the cumulative contig length.</p>
<p>The Mix algorithm, approach and results were published in BMC bioinformatics :&nbsp;<a href="http://www.biomedcentral.com/1471-2105/14/S15/S16">http://www.biomedcentral.com/1471-2105/14/S15/S16</a>.</p><p>Address of the bookmark: <a href="https://github.com/cbib/MIX" rel="nofollow">https://github.com/cbib/MIX</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40604/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output</guid>
	<pubDate>Fri, 24 Jan 2020 06:04:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40604/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output</link>
	<title><![CDATA[gapFinisher: A reliable gap filling pipeline for SSPACE-LongRead scaffolder output]]></title>
	<description><![CDATA[<p><span>gapFinisher is based on the controlled use of a previously published gap filling tool FGAP and works on all standard Linux/UNIX command lines. They compare the performance of gapFinisher against two other published gap filling tools PBJelly and GMcloser. </span></p>
<p><span>gapFinisher can fill gaps in draft genomes quickly and reliably.</span></p><p>Address of the bookmark: <a href="https://github.com/kammoji/gapFinisher" rel="nofollow">https://github.com/kammoji/gapFinisher</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43997/tools-for-rna-classification</guid>
	<pubDate>Tue, 08 Nov 2022 03:39:11 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43997/tools-for-rna-classification</link>
	<title><![CDATA[Tools for RNA classification]]></title>
	<description><![CDATA[<p><span>barrnap</span>&nbsp;-&nbsp;<a href="https://github.com/tseemann/barrnap" target="_blank">https://github.com/tseemann/barrnap</a></p><p><span>CPAT</span>&nbsp;-&nbsp;<a href="https://github.com/liguowang/cpat" target="_blank">https://github.com/liguowang/cpat</a>,&nbsp;<a href="http://lilab.research.bcm.edu/" target="_blank">http://lilab.research.bcm.edu/</a>&nbsp;(web server)</p><p><span>CPC2</span>&nbsp;-&nbsp;<a href="https://github.com/gao-lab/CPC2_standalone" target="_blank">https://github.com/gao-lab/CPC2_standalone</a>,&nbsp;<a href="http://cpc2.gao-lab.org/" target="_blank">http://cpc2.gao-lab.org/</a>&nbsp;(web server)</p><p><span>Infernal</span>&nbsp;-&nbsp;<a href="http://eddylab.org/infernal/" target="_blank">http://eddylab.org/infernal/</a>,&nbsp;<a href="https://github.com/EddyRivasLab/infernal" target="_blank">https://github.com/EddyRivasLab/infernal</a></p><p><span>NCBI RefSeq</span>&nbsp;-&nbsp;<a href="https://www.ncbi.nlm.nih.gov/refseq/" target="_blank">https://www.ncbi.nlm.nih.gov/refseq/</a></p><p><span>Rfam</span>&nbsp;-&nbsp;<a href="http://rfam.xfam.org/" target="_blank">http://rfam.xfam.org/</a>,&nbsp;<a href="https://docs.rfam.org/en/latest/index.html" target="_blank">https://docs.rfam.org/en/latest/index.html</a></p><p><span>SILVA</span>&nbsp;-&nbsp;<a href="https://www.arb-silva.de/" target="_blank">https://www.arb-silva.de/</a></p><p><span>RNAmmer</span>&nbsp;-&nbsp;<a href="http://www.cbs.dtu.dk/services/RNAmmer/" target="_blank">http://www.cbs.dtu.dk/services/RNAmmer/</a>&nbsp;(web server, standalone download link)</p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44518/virus-bioinformatics-tools</guid>
	<pubDate>Wed, 24 Apr 2024 06:19:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44518/virus-bioinformatics-tools</link>
	<title><![CDATA[Virus Bioinformatics Tools]]></title>
	<description><![CDATA[<p><span>Bioinformatics tools play a crucial role in studying viruses, enabling researchers to analyze their genetic makeup, structure, function, and evolution. Here are some commonly used bioinformatics tools for virus research</span></p>
<p>https://evirusbioinfc.notion.site/18e21bc49827484b8a2f84463cb40b8d?v=92e7eb6703be4720abf17a901bc9a947</p><p>Address of the bookmark: <a href="https://evirusbioinfc.notion.site/18e21bc49827484b8a2f84463cb40b8d?v=92e7eb6703be4720abf17a901bc9a947" rel="nofollow">https://evirusbioinfc.notion.site/18e21bc49827484b8a2f84463cb40b8d?v=92e7eb6703be4720abf17a901bc9a947</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44718/mycology-research-resources-for-bioinformaticians-unlocking-the-fungal-kingdom</guid>
	<pubDate>Fri, 13 Dec 2024 11:21:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44718/mycology-research-resources-for-bioinformaticians-unlocking-the-fungal-kingdom</link>
	<title><![CDATA[Mycology Research Resources for Bioinformaticians: Unlocking the Fungal Kingdom]]></title>
	<description><![CDATA[<p>Mycology, the study of fungi, is a field that bridges ecology, medicine, and biotechnology. With advancements in bioinformatics, researchers now have unprecedented opportunities to explore the fungal kingdom at molecular, genetic, and ecological levels. From understanding pathogenic fungi to harnessing fungal enzymes for industrial applications, the potential is vast.</p><p>To fully leverage these opportunities, bioinformaticians require specialized tools and databases. This blog highlights essential resources for mycology research, focusing on databases, tools, and platforms tailored for fungal biology.</p><h4><strong>1. Fungal Databases</strong></h4><h5><strong>1.1. MycoCosm</strong></h5><p><strong>Website</strong>: <a target="_new">MycoCosm</a><br />Developed by the DOE Joint Genome Institute, MycoCosm is a comprehensive portal for fungal genomics. It offers genomic and transcriptomic data for a wide range of fungi, including saprobes, pathogens, and symbionts.</p><ul>
<li><strong>Key Features</strong>: Genome browsers, comparative genomics tools, and functional annotations.</li>
<li><strong>Best For</strong>: Large-scale studies on fungal evolution and ecology.</li>
</ul><h5><strong>1.2. FungiDB</strong></h5><p><strong>Website</strong>: <a href="https://fungidb.org/" target="_new">FungiDB</a><br />FungiDB is an integrated genomic resource for fungal pathogens and non-pathogens. It provides access to genome sequences, transcriptomic data, and functional annotations.</p><ul>
<li><strong>Key Features</strong>: Advanced search options, BLAST, and pathway analysis tools.</li>
<li><strong>Best For</strong>: Studying fungal pathogenesis and host-pathogen interactions.</li>
</ul><h5><strong>1.3. Index Fungorum</strong></h5><p><strong>Website</strong>: <a href="http://www.indexfungorum.org/" target="_new">Index Fungorum</a><br />This nomenclatural database provides information on the scientific names of fungi. It&rsquo;s an essential resource for taxonomists and researchers focused on fungal biodiversity.</p><ul>
<li><strong>Key Features</strong>: Taxonomic hierarchy and synonymy tracking.</li>
<li><strong>Best For</strong>: Identifying and classifying fungal species.</li>
</ul><h5><strong>1.4. UNITE</strong></h5><p><strong>Website</strong>: <a target="_new">UNITE</a><br />UNITE is a specialized database for fungal ITS (Internal Transcribed Spacer) sequences, often used in fungal identification and phylogenetics.</p><ul>
<li><strong>Key Features</strong>: Curated reference datasets and community annotations.</li>
<li><strong>Best For</strong>: Environmental mycology and microbial ecology studies.</li>
</ul><h4><strong>2. Analytical Tools</strong></h4><h5><strong>2.1. Funannotate</strong></h5><p><strong>Repository</strong>: <a href="https://github.com/nextgenusfs/funannotate" target="_new">GitHub - Funannotate</a><br />Funannotate is a genome annotation tool designed for fungi. It supports tasks like gene prediction, functional annotation, and orthology analysis.</p><ul>
<li><strong>Best For</strong>: Annotating newly sequenced fungal genomes.</li>
</ul><h5><strong>2.2. BUSCO (Benchmarking Universal Single-Copy Orthologs)</strong></h5><p><strong>Website</strong>: <a target="_new">BUSCO</a><br />BUSCO evaluates genome assembly and annotation completeness using orthologs. It includes a fungal-specific dataset.</p><ul>
<li><strong>Best For</strong>: Assessing the quality of fungal genome assemblies.</li>
</ul><h5><strong>2.3. Pathogen-Host Interactions Database (PHI-base)</strong></h5><p><strong>Website</strong>: <a href="http://www.phi-base.org/" target="_new">PHI-base</a><br />PHI-base is a manually curated resource containing information on pathogen-host interactions, including fungal pathogens.</p><ul>
<li><strong>Best For</strong>: Exploring virulence factors and host-pathogen relationships.</li>
</ul><h4><strong>3. Visualization Platforms</strong></h4><h5><strong>3.1. Cytoscape</strong></h5><p><strong>Website</strong>: <a href="https://cytoscape.org/" target="_new">Cytoscape</a><br />A powerful tool for visualizing molecular interaction networks, Cytoscape can be used to study protein-protein interactions, gene networks, and metabolic pathways in fungi.</p><ul>
<li><strong>Best For</strong>: Network biology and functional genomics.</li>
</ul><h5><strong>3.2. iTOL (Interactive Tree of Life)</strong></h5><p><strong>Website</strong>: <a target="_new">iTOL</a><br />iTOL is an interactive tool for visualizing phylogenetic trees.</p><ul>
<li><strong>Best For</strong>: Displaying fungal phylogenies and comparing evolutionary relationships.</li>
</ul><h4><strong>4. Community Resources</strong></h4><h5><strong>4.1. Mycological Society of America (MSA)</strong></h5><p><strong>Website</strong>: <a href="https://msafungi.org/" target="_new">MSA</a><br />The MSA promotes fungal research and provides access to resources, conferences, and publications.</p><ul>
<li><strong>Best For</strong>: Networking with fungal researchers and accessing recent studies.</li>
</ul><h5><strong>4.2. OpenFungi</strong></h5><p><strong>Website</strong>: <a href="https://openfungi.org/" target="_new">OpenFungi</a><br />OpenFungi is an open-source initiative providing fungal genomic and transcriptomic datasets for research and education.</p><ul>
<li><strong>Best For</strong>: Sharing and accessing public fungal datasets.</li>
</ul><h4><strong>5. Genomics Workflows</strong></h4><h5><strong>5.1. Galaxy</strong></h5><p><strong>Website</strong>: <a href="https://usegalaxy.org/" target="_new">Galaxy Project</a><br />Galaxy offers a web-based platform for reproducible bioinformatics workflows, including tools for fungal genome and transcriptome analysis.</p><ul>
<li><strong>Best For</strong>: User-friendly analysis pipelines without requiring coding skills.</li>
</ul><h5><strong>5.2. Snakemake</strong></h5><p><strong>Repository</strong>: <a target="_new">Snakemake</a><br />A flexible pipeline management tool that supports fungal data processing and analysis.</p><ul>
<li><strong>Best For</strong>: Custom workflows for large-scale fungal datasets.</li>
</ul><h4><strong>Conclusion</strong></h4><p>Fungal research is a rapidly growing field with vast implications for medicine, agriculture, and industry. For bioinformaticians, the availability of specialized resources&mdash;databases, tools, and community platforms&mdash;opens doors to innovative discoveries. Whether you are investigating fungal genomics, studying host-pathogen interactions, or exploring fungal biodiversity, the resources outlined above will empower your research journey.</p><p>Dive into these resources and help unravel the mysteries of the fungal kingdom!</p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42974/list-of-bioinformatics-packages-for-ngs-analysis</guid>
	<pubDate>Sat, 20 Mar 2021 00:28:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42974/list-of-bioinformatics-packages-for-ngs-analysis</link>
	<title><![CDATA[List of bioinformatics packages for NGS analysis !]]></title>
	<description><![CDATA[<p>Package suites gather software packages and installation tools for specific languages or platforms. We have some for bioinformatics software.</p><ul>
<li><a href="https://github.com/Bioconductor">Bioconductor</a>&nbsp;&ndash; A plethora of tools for analysis and comprehension of high-throughput genomic data, including 1500+ software packages. [&nbsp;<a href="https://link.springer.com/article/10.1186/gb-2004-5-10-r80">paper-2004</a>&nbsp;|&nbsp;<a href="https://www.bioconductor.org/">web</a>&nbsp;]</li>
<li><a href="https://github.com/biopython/biopython">Biopython</a>&nbsp;&ndash; Freely available tools for biological computing in Python, with included cookbook, packaging and thorough documentation. Part of the&nbsp;<a href="http://open-bio.org/">Open Bioinformatics Foundation</a>. Contains the very useful&nbsp;<a href="https://biopython.org/DIST/docs/api/Bio.Entrez-module.html">Entrez</a>&nbsp;package for API access to the NCBI databases. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/19304878">paper-2009</a>&nbsp;|&nbsp;<a href="https://biopython.org/">web</a>&nbsp;]</li>
<li><a href="https://github.com/bioconda">Bioconda</a>&nbsp;&ndash; A channel for the&nbsp;<a href="http://conda.pydata.org/docs/intro.html">conda package manager</a>&nbsp;specializing in bioinformatics software. Includes a repository with 3000+ ready-to-install (with&nbsp;<code>conda install</code>) bioinformatics packages. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/29967506">paper-2018</a>&nbsp;|&nbsp;<a href="https://bioconda.github.io/">web</a>&nbsp;]</li>
<li><a href="https://github.com/BioJulia">BioJulia</a>&nbsp;&ndash; Bioinformatics and computational biology infastructure for the Julia programming language. [&nbsp;<a href="https://biojulia.net/">web</a>&nbsp;]</li>
<li><a href="https://github.com/rust-bio/rust-bio">Rust-Bio</a>&nbsp;&ndash; Rust implementations of algorithms and data structures useful for bioinformatics. [&nbsp;<a href="http://bioinformatics.oxfordjournals.org/content/early/2015/10/06/bioinformatics.btv573.short?rss=1">paper-2016</a>&nbsp;]</li>
<li><a href="https://github.com/seqan/seqan3">SeqAn</a>&nbsp;&ndash; The modern C++ library for sequence analysis.</li>
</ul>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/35386/list-of-visualization-tools-for-network-biology</guid>
	<pubDate>Mon, 29 Jan 2018 05:12:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/35386/list-of-visualization-tools-for-network-biology</link>
	<title><![CDATA[List of visualization tools for network biology]]></title>
	<description><![CDATA[<p>Network analysis&nbsp;is any structured technique used to mathematically analyze a circuit (a &ldquo;network&rdquo; of interconnected components). The&nbsp;<span>Network analysis provides the ability to quantify associations between individuals, which makes it possible to infer details about the network as a whole at the species and/or population level.&nbsp;</span>Few tools published in BMC are listed here https://bmcbioinformatics.biomedcentral.com/articles/sections/networks-analysis.</p><p><img src="https://www.dropbox.com/pri/get/Public/Link%20to%20network.gif?_subject_uid=85115969&amp;raw=1&amp;revision_id=BBqs9eYx7G_faj5J33ExdjmtF8nXK2xrN5dUBsKyTLZQ9RB_hGM-YFmWZMBzbQZfRvjYzfs65HbQYrHRyoikxsQscSFTn1Nud2QeJ8KGfVI5wv4Kzp6froKOmPZu8ZygfKo&amp;size=1280x960&amp;size_mode=3&amp;w=AABQaErsFIz5ZjVZSxXvKaSVUkY5ob1Yjk0x7dghy0X7zw" alt="image" style="border: 0px; border: 0px;"></p><p>Following are the list of standalone applications for network analysis:</p><p>Arena 3D</p><p>3D visualization of multi-layer networks</p><p>http://www.arena3d.org</p><p>Biana</p><p>Data integration and network management</p><p>http://sbi.imim.es/web/BIANA.php</p><p>BioLayout Express 3D&nbsp;</p><p>2D/3D network visualization</p><p>http://www.biolayout.org/</p><p>BiologicalNetworks&nbsp;</p><p>Efficient integrated multi-level analysis of microarray, sequence, regulatory and other data</p><p>http://www.biologicalnetworks.org</p><p>BioMiner</p><p>Modeling, analyzing and visualizing biochemical pathways and networks</p><p>http://www.zbi.uni-saarland.de/chair/projects/BioMiner</p><p>Cell Illustrator&nbsp;</p><p>Petri nets for modeling and simulating biological networks</p><p>http://www.cellillustrator.com</p><p>COPASI</p><p>Analysis of biochemical networks and their dynamics</p><p>http://www.copasi.org/</p><p>Cytoscape&nbsp;</p><p>Network visualization and analysis. Over 200 plugins [60]</p><p>http://www.cytoscape.org/</p><p>Dizzy</p><p>Chemical kinetics stochastic simulation software</p><p>http://magnet.systemsbiology.net/software/Dizzy/</p><p>DyCoNet</p><p>Gephi plugin that can be used to identify dynamic communities in networks</p><p>https://github.com/juliemkauffman/DyCoNet</p><p>GENeVis&nbsp;</p><p>Network and pathway visualization</p><p>http://tinyurl.com/genevis/</p><p>GEPHI&nbsp;</p><p>Interactive visualization and exploration for any network and complex system, dynamic and hierarchical graph.</p><p>https://gephi.org</p><p>Igraph</p><p>Collection of network analysis tools with the emphasis on efficiency, portability and ease of use</p><p>http://igraph.sourceforge.net</p><p>Medusa</p><p>Semantic and multi-edged simple networks</p><p>https://sites.google.com/site/medusa3visualization/</p><p>NAViGaTOR</p><p>Visualizing and analyzing protein-protein interaction networks</p><p>http://tinyurl.com/navigator1/</p><p>N-Browse</p><p>Interactive graphical browser for biological networks</p><p>http://www.gnetbrowse.org/</p><p>NeAT</p><p>Topological and clustering analysis of networks</p><p>http://rsat.ulb.ac.be/neat/</p><p>Ondex&nbsp;</p><p>Data integration and visualization of large networks</p><p>http://www.ondex.org/</p><p>Osprey</p><p>Visualization and annotation of biological networks</p><p>http://biodata.mshri.on.ca/osprey/servlet/Index</p><p>Pajek&nbsp;</p><p>Analysis and visualization of large networks and social network analysis</p><p>http://vlado.fmf.uni-lj.si/pub/networks/pajek/</p><p>PathwayAssist&nbsp;</p><p>Navigation and analysis of biological pathways, gene regulation networks and protein interaction maps.</p><p>http://www.ariadnegenomics.com/downloads/</p><p>PIVOT&nbsp;</p><p>Layout algorithms for visualizing protein interactions and families</p><p>http://acgt.cs.tau.ac.il/pivot/</p><p>ProCope&nbsp;</p><p>Prediction and evaluation of protein complexes from purification data experiments</p><p>http://www.bio.ifi.lmu.de/Complexes/ProCope/</p><p>ProViz&nbsp;</p><p>Visualization and exploration of interaction networks. Gene Ontology and PSI-MI formats supported</p><p>http://cbi.labri.fr/eng/proviz.htm</p><p>SpectralNET&nbsp;</p><p>Network analysis and visualizations. Scatter plots and dimensionality reduction algorithms</p><p>https://www.broadinstitute.org/software/spectralnet</p><p>Tulip&nbsp;</p><p>Enables the development of algorithms, visual encodings, interaction techniques, data models and domain-specific visualizations</p><p>http://tulip.labri.fr/TulipDrupal/</p><p>VANESA&nbsp;</p><p>Automatic reconstruction and analysis of biological networks and Petri nets based on life-science database information</p><p>http://agbi.techfak.uni-bielefeld.de/vanesa/</p><p>VANTED&nbsp;</p><p>Network reconstruction, data visualization, integration of various data types, network simulation</p><p>http://tinyurl.com/vanted/</p><p>yEd</p><p>Creation of diagrams manually and import external data</p><p>http://tinyurl.com/yEdGraph/</p><p>Web tools for network analysis</p><p>APID&nbsp;</p><p>Unified protein-protein interactions from BIND, BioGRID, DIP, HPRD, IntAct and MINT</p><p>http://bioinfow.dep.usal.es/apid/</p><p>Arcadia&nbsp;</p><p>Translates text-based descriptions of biological networks (SBML files) into standardized diagrams (Systems Biology Graphical Notation Process Description maps)</p><p>http://arcadiapathways.sourceforge.net/</p><p>AVIS&nbsp;</p><p>Viewer for signaling networks</p><p>http://actin.pharm.mssm.edu/AVIS2</p><p>bioPIXIE&nbsp;</p><p>Discovery of biological networks from diverse functional genomic data</p><p>http://pixie.princeton.edu/pixie</p><p>CellPublisher</p><p>Interactive representations of biochemical processes</p><p>http://cellpublisher.gobics.de/</p><p>Graphle</p><p>Distributed network exploration and visualization of interactive large, dense graphs</p><p>http://tinyurl.com/graphle/</p><p>GraphWeb&nbsp;</p><p>Web server for graph-based analysis of biological networks</p><p>http://biit.cs.ut.ee/graphweb/</p><p>Hubba</p><p>Web-based service to explore the essential nodes in a network</p><p>http://hub.iis.sinica.edu.tw/Hubba</p><p>NetworkBLAST&nbsp;</p><p>Analysis of protein interaction networks across species to infer protein complexes that are conserved in evolution</p><p>http://www.cs.tau.ac.il/~bnet/networkblast.htm</p><p>Pathview&nbsp;</p><p>Tool set for pathway-based data integration and visualization</p><p>http://Pathview.r-forge.r-project.org/</p><p>PINA&nbsp;</p><p>Integrated platform for protein interaction network construction, filtering, analysis, visualization and management</p><p>http://cbg.garvan.unsw.edu.au/pina/home.do</p><p>ReMatch&nbsp;</p><p>Web-based tool for integration of user-given stoichiometric metabolic models into a database collected from public data sources</p><p>http://www.cs.helsinki.fi/group/sysfys/software/rematch/</p><p>SNOW&nbsp;</p><p>Gene mapping on a reference or human protein-protein interaction network that SNOW hosts</p><p>http://snow.bioinfo.cipf.es</p><p>STITCH&nbsp;</p><p>Resource to explore known and predicted interactions of chemicals and proteins</p><p>http://stitch.embl.de/</p><p>STRING</p><p>Protein interaction networks and integration of data such as genomic context, high-throughput experiments, conserved coexpression and previous knowledge derived from the literature</p><p>http://string-db.org</p><p>TVNViewer&nbsp;</p><p>An interactive visualization tool for exploring networks that change over time or space</p><p>http://www.sailing.cs.cmu.edu/main/?page_id=545</p><p>tYNA&nbsp;</p><p>System for managing, comparing and mining multiple networks</p><p>http://tyna.gersteinlab.org/tyna/</p><p>VisANT&nbsp;</p><p>Visualization, mining, analysis and modeling of biological networks, metabolic networks and ecosystems</p><p>http://visant.bu.edu/</p><p>&nbsp;</p>]]></description>
	<dc:creator>Jit</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>

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