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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36516?offset=300</link>
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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>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36583/eugi-a-novel-resource-for-studying-genomic-islands-to-facilitate-horizontal-gene-transfer-detection-in-eukaryotes</guid>
	<pubDate>Sat, 12 May 2018 07:26:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36583/eugi-a-novel-resource-for-studying-genomic-islands-to-facilitate-horizontal-gene-transfer-detection-in-eukaryotes</link>
	<title><![CDATA[EuGI: a novel resource for studying genomic islands to facilitate horizontal gene transfer detection in eukaryotes]]></title>
	<description><![CDATA[<p><span>SWGIS v2.0 along with the EuGI database, which houses GIs identified in 66 different eukaryotic species, and the EuGI web-resource, provide the first comprehensive resource for studying HGT in eukaryotes.</span></p>
<p>https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-018-4724-8</p><p>Address of the bookmark: <a href="https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-018-4724-8" rel="nofollow">https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-018-4724-8</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/38238/list-of-motif-discovery-tools</guid>
	<pubDate>Tue, 20 Nov 2018 03:54:26 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/38238/list-of-motif-discovery-tools</link>
	<title><![CDATA[List of motif discovery tools !]]></title>
	<description><![CDATA[<div><div>In genetics, a sequence motif is a nucleotide or amino-acid sequence pattern that is widespread and has, or is conjectured to have, a biological significance. For proteins, a sequence motif is distinguished from a structural motif, a motif formed by the three-dimensional arrangement of amino acids which may not be adjacent.</div><div>&nbsp;</div><div>Following are the list of tools for motif discovery:</div><div>&nbsp;</div><div><a href="http://genius.embnet.dkfz-heidelberg.de/menu/biounit/open-husar/">2Dsweep -- protein annotation by secondary structure elements</a></div><p>Perform secondary structure predictions on protein sequences.</p></div><div><div><a href="http://floresta.eead.csic.es/3dfootprint/">3D-footprint -- database of DNA-binding protein structures</a></div><p>Find binding specificity information about DNA-protein complexes.</p></div><div><div><a href="http://floresta.eead.csic.es/3dfootprint/">3D-footprint: DNA-binding protein database</a></div><p>Find information about the binding specificity of DNA-binding proteins.</p></div><div><div><a href="http://3d-partner.life.nctu.edu.tw/">3D-partner -- a web server to infer interacting partners and binding models</a></div><p>Predict interacting partners and binding models.</p></div><div><div><a href="http://motif.stanford.edu/distributions/3motif/">3MOTIF -- a protein structure visualization system for conserved sequence motifs</a></div><p>Use this web-based sequence motif visualization system to display sequence motif information in its appropriate three-dimensional (3D) context.</p></div><div><div><a href="http://bioinfo.mpiz-koeln.mpg.de/afawe/">AFAWE -- Automatic functional annotation in a distributed Web Services Environment</a></div><p>Protein function prediction and annotation in an integrated environment powered by web service.</p></div><div><div><a href="http://anchor.enzim.hu/">ANCHOR -- Prediction of Protein Binding Regions in Disordered Proteins</a></div><p>Find information about protein binding.</p></div><div><div><a href="http://annie.bii.a-star.edu.sg/annie/home.do">ANNIE -- ANNotation and Interpretation Environment for Protein Sequences</a></div><p>Use to predict function from de novo protein sequences.</p></div><div><div><a href="http://bioinformatica.isa.cnr.it/ASC/">Active Sequences Collection (ASC) database -- A new tool to assign functions to protein sequences</a></div><p>Search for short active protein sequences with demonstrated biological activities.</p></div><div><div><a href="http://blocks.fhcrc.org/">Blocks -- Ungapped segments in conserved protein sequences</a></div><p>Search for ungapped segments corresponding to the most highly conserved regions of proteins.</p></div><div><div><a href="http://cast.engr.uic.edu/">CASTp -- computed atlas of surface topography of proteins with structural and topographical mapping of functionally annotated residues</a></div><p>Identify and measure surface accessible pockets as well as interior inaccessible cavities, for proteins and other molecules.</p></div><div><div><a href="http://www.ebi.ac.uk/thornton-srv/databases/CSA">CSA -- The Catalytic Site Atlas</a></div><p>To search for catalytic residue annotation for enzymes in the Protein Data Bank.</p></div><div><div><a href="http://www.sbg.bio.ic.ac.uk/~confunc/">ConFunc -- Conserved residue Protein Function Prediction Server</a></div><p>Predict protein function using Gene Ontology.</p></div><div><div><a href="http://consurf.tau.ac.il/">ConSurf-DB -- evolutionary conservation profiles of protein structures database</a></div><p>Automatically calculate evolutionary conservation scores of key amino acid residues and map them on protein structures.</p></div><div><div><a href="http://salilab.org/DBAli/">DBAli -- A Database of Structure Alignments</a></div><p>Mine the protein structure space.</p></div><div><div><a href="http://dilimot.embl.de/">DILIMOT -- discovery of linear motifs in proteins</a></div><p>Predict short linear motifs (3-8 residues) in a set of protein sequences.</p></div><div><div><a href="http://www.ebi.ac.uk/dasty/">Dasty2 -- an Ajax protein DAS client</a></div><p>A web client for visualizing protein sequence feature information using DAS.</p></div><div><div><a href="http://genius.embnet.dkfz-heidelberg.de/menu/biounit/open-husar/">DomainSweep -- protein annotation by domain analysis</a></div><p>Identify the domain architecture within a protein sequence.</p></div><div><div><a href="http://e1ds.csbb.ntu.edu.tw/">E1DS -- catalytic site prediction based on 1D signatures of concurrent conservation</a></div><p>Predict enzyme catalytic site.</p></div><div><div><a href="http://elm.eu.org/">ELM -- Eukarotic Linear Motif Resource</a></div><p>Predict functional sites in eukaryotic proteins.</p></div><div><div><a href="http://us.expasy.org/tools/#proteome">EXPASY Proteome Tools Collection</a></div><p>Use a collection of tools for protein analyses.</p></div><div><div><a href="http://us.expasy.org/tools/findmod/">EXPASY-Findmod</a></div><p>Predict potential protein post-translational modifications and find potential single amino acid substitutions in peptides.</p></div><div><div><a href="http://mbs.cbrc.jp/EzCatDB/">EzCatDB -- the Enzyme Catalytic-mechanism Database</a></div><p>Search for information related to the catalytic mechanisms of enzymes.</p></div><div><div><a href="http://bioinf.cs.ucl.ac.uk/ffpred/">FFPred -- feature-based function prediction</a></div><p>An integrated feature-based function prediction server for vertebrate proteomes.</p></div><div><div><a href="http://www.ebi.ac.uk/printsscan/">FingerPRINT Scan</a></div><p>Identify the closest matching PRINTS sequence motif fingerprints in a protein sequence.</p></div><div><div><a href="http://firedb.bioinfo.cnio.es/">FireDB -- a database of functionally important residues from proteins of known structure</a></div><p>Search for functional annotation of important sites in proteins with known structures.</p></div><div><div><a href="http://bioserv.rpbs.univ-paris-diderot.fr/cgi-bin/Frog2">Frog2 -- a FRee Online druG 3D conformation generator</a></div><p>Produce 3D conformations of small drug compounds.</p></div><div><div><a href="http://www.hgpd.jp/">HGPD -- Human Gene and Protein Database</a></div><p>A database presenting experiment-based results in human proteomics.</p></div><div><div><a href="http://hhsenser.tuebingen.mpg.de/">HHsenser -- exhaustive transitive profile search using HMMx96HMM comparison</a></div><p>Conduct exhaustive intermediate profile searches of a set of homologous protein sequences.</p></div><div><div><a href="http://loschmidt.chemi.muni.cz/hotspotwizard/">HotSpot Wizard -- Substrate Specificity Hot Spot Identification web server</a></div><p>Design protein mutations in site-directed mutagenesis.</p></div><div><div><a href="http://phylogenomics.berkeley.edu/intrepid/">INTREPID -- INformation-theoretic TREe traversal for Protein functional site IDentification</a></div><p>Use for protein functional site identification.</p></div><div><div><a href="http://www.cbs.dtu.dk/">Integrating protein annotation resources through the Distributed Annotation System</a></div><p>Annotate protein using this integrated annotation resource.</p></div><div><div><a href="http://www.ebi.ac.uk/InterProScan/">InterProScan -- protein domains identifier</a></div><p>Identify protein family (and DNA) domains, patterns, motifs, protein families, and functional sites.</p></div><div><div><a href="http://kfc.mitchell-lab.org/">KFC -- Knowledge-based FADE and Contacts</a></div><p>Interactive forecasting of protein interaction hot spots.</p></div><div><div><a href="http://biominer.bime.ntu.edu.tw/magiicpro/">MAGIIC-PRO -- detecting functional signatures by efficient discovery of long patterns in protein sequences</a></div><p>Discover long patterns in protein sequences.</p></div><div><div><a href="http://prodata.swmed.edu/malisam">MALISAM -- Manual ALIgnments for Structurally Analogous Motifs</a></div><p>Database containing pairs of structural analogs and their alignments.</p></div><div><div><a href="http://meme.nbcr.net/">MEME -- discovering and analyzing DNA and protein sequence motifs</a></div><p>Find sequence patterns in DNA and protein sequences.</p></div><div><div><a href="http://www.nii.res.in/modpropep.html">MODPROPEP -- a program for knowledge-based modeling of protein-peptide complexes</a></div><p>A web server for knowledge-based modeling of protein-peptide complexes, specifically peptides in complex with major histocompatibility complex (MHC) proteins and kinases.</p></div><div><div><a href="http://www.bioinfo.tsinghua.edu.cn/~tigerchen/memo.html">MeMo -- a web tool for prediction of protein methylation modifications</a></div><p>Predict protein methylation sites.</p></div><div><div><a href="http://caps.ncbs.res.in/MegaMotifbase/index.html">MegaMotifBase -- a database of structural motifs in protein families and superfamilies</a></div><p>Find structural segments or motifs for protein structures.</p></div><div><div><a href="http://mnm.engr.uconn.edu/MNM/SMSSearchServlet">Minimotif Miner -- a tool for investigating protein function</a></div><p>Find motifs in a protein sequence.</p></div><div><div><a href="http://umber.sbs.man.ac.uk/dbbrowser/motif3d/motif3d.html">Motif3D -- Relating protein sequence motifs to 3D structure</a></div><p>Visualize protein sequence motifs on the 3D protein structures.</p></div><div><div><a href="http://myhits.isb-sib.ch/cgi-bin/motif_scan">MotifScan</a></div><p>Find presence of any known protein motif (Prosite and Pfam) in a protein sequence.</p></div><div><div><a href="http://bioinfo3d.cs.tau.ac.il/MultiBind">MultiBind -- Multiple Alignment of Protein Binding Sites</a></div><p>Recognize spatial chemical binding patterns common to a set of protein structures.</p></div><div><div><a href="http://mendel.imp.univie.ac.at/myristate/SUPLpredictor.htm">NMT -- The MYR Predictor</a></div><p>Analyze proteins for the presence of N-terminal N-myristoylation site.</p></div><div><div><a href="http://www.cbs.dtu.dk/services/NetNGlyc/">NetNGlyc -- N-Glycosylation sites prediction tool</a></div><p>Find the presence of N-Glycosylation sites in human proteins.</p></div><div><div><a href="http://www.cbs.dtu.dk/services/NetOGlyc/">NetOGly 3.1 -- O-glycosylation sites prediction tool</a></div><p>Find the presence of O-GalNAc (mucin type) glycosylation sites in mammalian proteins.</p></div><div><div><a href="http://www.cbs.dtu.dk/services/NetPhos/">NetPhos 2.0 -- Phosphorylation sites predictions</a></div><p>Analyze eukaryotic proteins for the presence of serine, threonine and tyrosine phosphorylation sites.</p></div><div><div><a href="http://www.cbs.dtu.dk/services/NetPhosK/">NetPhosK 1.0 Server -- kinase specific eukaryotic protein phosphorylation sites prediction tool</a></div><p>Find possible kinase specific phosphorylation sites in eukaryotic proteins.</p></div><div><div><a href="http://networkin.info/search.php">NetworKIN -- a resource for exploring cellular phosphorylation networks</a></div><div>&nbsp;</div></div><div><div><a href="http://neuroproteomics.scs.uiuc.edu/neuropred.html">NeuroPred -- a tool to predict cleavage sites in neuropeptide precursors and provide the masses of the resulting peptides</a></div><p>Predict cleavage sites at basic amino acid locations in neuropeptide precursor sequences.</p></div><div><div><a href="http://www.ebi.ac.uk/patentdata/nr/">Non-Redundant Patent Sequences - Patented Sequence Database</a></div><p>Find information about patented nucleotide and protein sequences.</p></div><div><div><a href="http://www.cbs.dtu.dk/databases/OGLYCBASE/">O-GLYCBASE</a></div><p>Search for information about glycoproteins with O-linked and C-linked glycosylation sites.</p></div><div><div><a href="http://www.pandora.cs.huji.ac.il/">PANDORA -- Protein ANnotation Diagram ORiented Analysis</a></div><p>Find information about protein sequence annotations.</p></div><div><div><a href="http://sunserver.cdfd.org.in:8080/protease/PAR_3D/index.html">PAR-3D -- Protein Active site Residue - 3D structural motif</a></div><p>A server to predict protein active site residues.</p></div><div><div><a href="http://wwwmgs.bionet.nsc.ru/mgs/gnw/pdbsite/">PDBSite -- a database of the 3D structure of protein functional sites</a></div><p>Search for structural and functional information on the protein functional sites.</p></div><div><div><a href="http://wwwmgs.bionet.nsc.ru/mgs/systems/fastprot/pdbsitescan.html">PDBSiteScan -- A program for searching for active, binding and posttranslational modification sites in the 3D structures of proteins</a></div><p>Search 3D protein fragments similar in structure to known active, binding and posttranslational modification sites.</p></div><div><div><a href="http://pedant.gsf.de/">PEDANT -- Protein Extraction, Description and ANalysis Tool</a></div><p>Conduct genome wide functional and structural analysis.</p></div><div><div><a href="http://phosida.org/">PHOSIDA -- Phosphorylation site database</a></div><p>Search for phosphorylation data of any protein of interest.</p></div><div><div><a href="http://www.phosphorylation.biochem.vt.edu/">PHOSPHORYLATION SITE DATABASE</a></div><p>Search for information on prokaryotic proteins that undergo serine, threonine, or tyrosine phosphorylation.</p></div><div><div><a href="http://www.jcvi.org/pn-utility/web/smarty_wrapper/about.php">PNU -- Protein Naming Utility</a></div><p>Determine correct names for proteins.</p></div><div><div><a href="http://mbs.cbrc.jp/poodle/poodle-s.html">POODLE-S -- Predicition Of Order and Disorder by machine LEarning</a></div><p>Web application for predicting protein disorder by using physicochemical features and reduced amino acid set of a position-specific scoring matrix.</p></div><div><div><a href="http://gemdock.life.nctu.edu.tw/ppisearch/">PPISearch -- Protein-Protein Interaction Search</a></div><p>Find homologous protein-protein interactions across multiple species.</p></div><div><div><a href="http://www.ebi.ac.uk/ppsearch/">PPSearch</a></div><p>Search your query sequence against PROSITE pattern database for protein motifs.</p></div><div><div><a href="http://pridb.gdcb.iastate.edu/">PRIDB -- Protein-RNA Interface DataBase</a></div><p>Find information about protein-RNA complexes from the Protein Data Bank (PDB).</p></div><div><div><a href="http://umber.sbs.man.ac.uk/dbbrowser/PRINTS/">PRINTS and its automatic supplement, prePRINTS -- A compendium of protein fingerprints</a></div><p>Search for protein fingerprints.</p></div><div><div><a href="http://www.expasy.org/prosite/">PROSITE</a></div><p>Identify protein families and domains for a given protein sequence.</p></div><div><div><a href="http://www.imtech.res.in/raghava/prrdb/">PRRDB -- Pattern Recognition Receptor Database</a></div><p>A comprehensive database of pattern-recognition receptors and their ligands.</p></div><div><div><a href="http://www.arabidopsis.org/cgi-bin/patmatch/nph-patmatch.pl">PatMatch -- a program for finding patterns in peptide and nucleotide sequences</a></div><p>Search for short nucleotide or peptide sequences such as cis-elements in nucleotide sequences or small domains and motifs in protein sequences.</p></div><div><div><a href="http://pepcyber.umn.edu/PPEP/">PepCyber:P~PEP -- a database of human protein protein interactions mediated by phosphoprotein-binding domains</a></div><p>Database specialized in documenting human PPBD-containing proteins and PPBD-mediated interactions.</p></div><div><div><a href="http://us.expasy.org/tools/peptidecutter/">PeptideCutter -- protein cleavage sites prediction tool</a></div><p>Predicts potential protease cleavage sites and sites cleaved by chemicals in a given protein sequence.</p></div><div><div><a href="http://phobius.binf.ku.dk/">Phobius -- A combined transmembrane topology and signal peptide predictor</a></div><p>Predict combined transmembrane topology and signal peptides.</p></div><div><div><a href="http://phospho.elm.eu.org/">Phospho.ELM -- a database of phosphorylation sites</a></div><p>Search for eukaryotic phosphorylation sites.</p></div><div><div><a href="http://www.phospho3d.org/">Phospho3D -- a database of three-dimensional structures of protein phosphorylation sites</a></div><p>Search for 3D structure and functional annotation of phosphorylation sites in proteins.</p></div><div><div><a href="http://www.phosphosite.org/">PhosphoSite -- A bioinformatics resource dedicated to physiological protein phosphorylation.</a></div><p>Search the database of in vivo phosphorylation sites of human and mouse proteins</p></div><div><div><a href="http://pxgrid.med.monash.edu.au/polyq/">PolyQ -- Polyglutamine Database</a></div><p>Find information about polyglutamine (polyQ) repeats.</p></div><div><div><a href="http://www.ebi.ac.uk/pratt/">Pratt Protein motif and pattern discovery</a></div><p>Find the presence of protein motifs and patterns in an amino acid sequence.</p></div><div><div><a href="http://www.predisi.de/">PrediSi -- Prediction of Signal Peptides and their Cleavage Positions</a></div><p>Predict signal peptide sequences and their cleavage positions in bacterial and eukaryotic amino acid sequences.</p></div><div><div><a href="http://www.ebi.ac.uk/thornton-srv/databases/ProFunc/">ProFunc -- a server for predicting protein function from 3D structure</a></div><p>Predict protein functions based on known structures.</p></div><div><div><a href="http://bioinfo41.weizmann.ac.il/promate/promateus.html">ProMateus--an open research approach to protein-binding sites analysis</a></div><p>Predict the location of potential protein-protein binding sites for unbound proteins.</p></div><div><div><a href="http://www.proteus.cs.huji.ac.il/">ProTeus -- identifying signatures in protein termini</a></div><p>Identify short linear signatures in protein termini.</p></div><div><div><a href="http://genius.embnet.dkfz-heidelberg.de/menu/cgi-bin/w2h-open/w2h.open/w2h.startthis?SIMGO=w2h%2ewelcome">ProtSweep -- protein annotation by homology</a></div><p>Analyze and identify newly obtained protein sequences.</p></div><div><div><a href="http://protemot.csbb.ntu.edu.tw/">Protemot -- prediction of protein binding sites with automatically extracted geometrical templates</a></div><p>Predict protein binding sites in a protein sequence based on geometrical analysis of protein tertiary substructures.</p></div><div><div><a href="http://quasimotifinder.tau.ac.il/">QuasiMotiFinder -- protein annotation by searching for evolutionarily conserved motif-like patterns</a></div><p>Search for evolutionarily conserved motif-like patterns in protein sequences.</p></div><div><div><a href="http://bindr.gdcb.iastate.edu/RNABindR">RNABindR -- software for prediction of RNA binding residues in proteins</a></div><p>Web-based server for analyzing and predicting RNA binding sites in proteins.</p></div><div><div><a href="http://caps.ncbs.res.in/scanmot/scanmot.html">SCANMOT -- searching for similar sequences using a simultaneous scan of multiple sequence motifs</a></div><p>Search for similarities between proteins by simultaneous matching of multiple motifs.</p></div><div><div><a href="http://bioinf.fbb.msu.ru/SDPpred/">SDPpred -- A Tool for Prediction of Amino Acid Residues that Determine Differences in Functional Specificity of Homologous Proteins</a></div><p>Predict residues in protein sequences that determine the proteins' functional specificity.</p></div><div><div><a href="http://tamm.mit.edu/SDR/">SDR -- Specificity Determining Residues Database</a></div><p>Predict specificity-determining residues in protein families.</p></div><div><div><a href="http://bioware.ucd.ie/~slimdisc/">SLiMDisc -- Short, Linear Motif Discovery</a></div><p>Find shared motifs in proteins with a common attribute.</p></div><div><div><a href="http://sumosp.biocuckoo.org/">SUMOsp -- a web server for sumoylation site prediction</a></div><p>Conduct in silico sumoylation sites prediction.</p></div><div><div><a href="http://oxytricha.princeton.edu/SWAKK/">SWAKK -- a web server for detecting positive selection in proteins using a sliding window substitution rate analysis</a></div><p>Detect protein sequence section under positive evolution selection.</p></div><div><div><a href="http://www.expasy.org/tools/scanprosite/">ScanProsite</a></div><p>Search for motifs and patterns within protein sequences.</p></div><div><div><a href="http://www.expasy.org/tools/scanprosite/">ScanProsite -- detection of PROSITE signature matches and ProRule-associated functional and structural residues in proteins</a></div><p>Detect patterns, profiles and motifs in a protein sequence.</p></div><div><div><a href="http://scansite.mit.edu/">ScanSite 2.0 -- Proteome-wide prediction of cell signaling interactions using short sequence motifs</a></div><p>Search for motifs within proteins that are likely to be phosphorylated by specific protein kinases or bind to domains such as SH2 domains, 14-3-3 domains or PDZ domains.</p></div><div><div><a href="http://sepresa.bio-x.cn/">SePreSA -- SErver for the PREdiction of populations susceptible to Serious Adverse drug reaction</a></div><p>Find information about populations carrying polymorphisms within protein binding pockets that make them susceptible to serious adverse drug reaction (SADR).</p></div><div><div><a href="http://motif.genome.jp/">Sequence Motif Search</a></div><p>Search the presence of a motif in either amino acid sequence or nucleotide sequence.</p></div><div><div><a href="http://www.csbio.sjtu.edu.cn/bioinf/Signal-3L/">Signal-3L -- A 3-layer approach for predicting signal peptides</a></div><p>Predict signal peptides.</p></div><div><div><a href="http://www.cbs.dtu.dk/services/SignalP/">SignalP -- Machine learning approaches to the prediction of signal peptides, their cleavage sites, and other protein sorting signals</a></div><p>Predict signal peptides and their cleavage sites.</p></div><div><div><a href="http://us.expasy.org/tools/sulfinator/">Sulfinator -- tyrosine sulfation sites prediction tool</a></div><p>Predict the presence of tyrosine sulfation sites in protein sequences</p></div><div><div><a href="http://bioinf-services.charite.de/supersite/">SuperSite -- Ligand Binding Site Database</a></div><p>Look at protein structure from a ligand and binding site perspective.</p></div><div><div><a href="http://www.ch.embnet.org/">Swiss EMBnet node web server</a></div><p>Use a collection of bioinformatics tools at this portal site.</p></div><div><div><a href="http://bioinfo.montp.cnrs.fr/?r=t-reks">T-REKS -- identification of Tandem REpeats in sequences with a K-meanS based algorithm</a></div><p>Find information about tandem repeats in proteins that carry fundamental biological functions and are related to a number of human diseases.</p></div><div><div><a href="http://tmbeta-genome.cbrc.jp/TMFunction/">TMFunction -- The Functional Database of Membrane Proteins</a></div><p>Find information about functional residues in alpha-helical and beta-barrel membrane proteins.</p></div><div><div><a href="http://topdom.enzim.hu/">TOPDOM -- Conservatively Located Domains and Motifs in Transmembrane Proteins</a></div><p>Database of domains and motifs with conservative location in transmembrane proteins.</p></div><div><div><a href="http://motif.stanford.edu/distributions/emotif/">The EMOTIF database</a></div><p>Search for highly conserved and specific protein sequence motifs.</p></div><div><div><a href="http://treedetv2.bioinfo.cnio.es/treedet/index.html">TreeDet -- Predicting Functional Residues in Protein Sequence Alignments</a></div><p>Predict functional sites in protein sequence alignments use different methodologies.</p></div><div><div><a href="http://motif.bmi.ohio-state.edu/ChIPMotifs/">W-ChIPMotifs -- ChIP-based protein Motif discovery web server</a></div><p>Find de novo protein motifs from chromatin immunoprecipitation data.</p></div><div><div><a href="http://feature.stanford.edu/webfeature/">WebFEATURE -- an interactive web tool for identifying and visualizing functional sites on macromolecular structures</a></div><p>Scan query structures for functional sites in both proteins and nucleic acids.</p></div><div><div><a href="http://wwwmgs.bionet.nsc.ru/mgs/programs/panalyst/">WebProAnalyst -- an interactive tool for analysis of quantitative structurex96activity relationships in protein families</a></div><p>Analyze quantitative structure-activity relationship of related protein families.</p></div><div><div><a href="http://motif.stanford.edu/distributions/eblocks/">eBLOCKs -- enumerating conserved protein blocks to achieve maximal sensitivity and specificity</a></div><p>Search for ungapped alignments of highly conserved regions among a protein family or superfamily.</p></div><div><div><a href="http://ef-site.hgc.jp/eF-seek/">eF-seek -- prediction of the functional sites of proteins by searching for similar electrostatic potential and molecular surface shape</a></div><p>Predict the functional sites of proteins.</p></div><div><div><a href="http://firedb.bioinfo.cnio.es/Php/FireStar.php">firestar -- prediction of functionally important residues using structural templates and alignment reliability</a></div><p>An expert system for predicting ligand-binding residues in protein structures.</p></div><div><div><a href="http://caps.ncbs.res.in/imotdb/">iMOTdb -- a comprehensive collection of spatially interacting motifs in proteins</a></div><p>Automatically identify spatially interacting motifs among distantly related proteins sharing similar folds and possessing common ancestral lineage.</p></div>]]></description>
	<dc:creator>Neel</dc:creator>
</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/bookmarks/view/42570/breeding-insight</guid>
	<pubDate>Wed, 06 Jan 2021 19:49:21 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42570/breeding-insight</link>
	<title><![CDATA[Breeding Insight]]></title>
	<description><![CDATA[<p><span><span>Breeding Insight&nbsp;at Cornell University will leverage recent improvements in genomics and open source informatics components, and in&nbsp;partnership with small breeding programs, will enable these programs to harness&nbsp;&nbsp;powerful digital tools to accelerate their genetic gains</span></span></p>
<p><span>Breeding Insight is funded by&nbsp;the&nbsp;</span><span><a href="https://www.ars.usda.gov/about-ars/" target="_blank">U.S. Department of Agriculture (USDA) Agricultural Research Service (ARS)</a></span><span>&nbsp;through Cornell University. The USDA ARS delivers scientific solutions to national and global agricultural challenges. As a global leader&nbsp;in agricultural discovery through scientific excellence, ARS is committed to delivering cutting-edge, scientific tools and innovative solutions for American farmers, producers, industry, and communities to support the nourishment and well-being of all people; sustaining our nation&rsquo;s agroecosystems and natural resources; and ensuring the economic competitiveness and excellence of our agriculture.</span></p><p>Address of the bookmark: <a href="https://www.breedinginsight.org/" rel="nofollow">https://www.breedinginsight.org/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44288/upset-plots</guid>
	<pubDate>Fri, 24 Mar 2023 22:30:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44288/upset-plots</link>
	<title><![CDATA[Upset plots !]]></title>
	<description><![CDATA[<p>Upset plots are a type of visualization used to analyze the intersection of sets or categories. They are particularly useful for displaying data with multiple categories and analyzing their overlaps.</p>
<p>In an upset plot, each row represents a category or set, and each column represents a data point. The length of the bar for each category indicates the number of data points that belong to that category. The plot also shows the intersections between categories, represented by overlapping bars.</p>
<p>Upset plots are useful for visualizing complex data with multiple categories and intersections, and can help identify patterns and relationships between categories. They are often used in fields such as bioinformatics, where they can be used to analyze gene expression data or to compare the results of different experimental conditions.</p>
<p>https://jokergoo.github.io/ComplexHeatmap-reference/book/upset-plot.html#example-with-the-genomic-regions</p><p>Address of the bookmark: <a href="https://jokergoo.github.io/ComplexHeatmap-reference/book/upset-plot.html#example-with-the-genomic-regions" rel="nofollow">https://jokergoo.github.io/ComplexHeatmap-reference/book/upset-plot.html#example-with-the-genomic-regions</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32946/grass-a-generic-algorithm-for-scaffolding-next-generation-sequencing-assemblies</guid>
	<pubDate>Tue, 23 May 2017 05:20:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32946/grass-a-generic-algorithm-for-scaffolding-next-generation-sequencing-assemblies</link>
	<title><![CDATA[GRASS: a generic algorithm for scaffolding next-generation sequencing assemblies.]]></title>
	<description><![CDATA[<p><span>GRASS (GeneRic ASsembly Scaffolder)-a novel algorithm for scaffolding second-generation sequencing assemblies capable of using diverse information sources. GRASS offers a mixed-integer programming formulation of the contig scaffolding problem, which combines contig order, distance and orientation in a single optimization objective. The resulting optimization problem is solved using an expectation-maximization procedure and an unconstrained binary quadratic programming approximation of the original problem. We compared GRASS with existing HTS scaffolders using Illumina paired reads of three bacterial genomes. Our algorithm constructs a comparable number of scaffolds, but makes fewer errors. This result is further improved when additional data, in the form of related genome sequences, are used.</span></p><p>Address of the bookmark: <a href="https://github.com/AlexeyG/GRASS" rel="nofollow">https://github.com/AlexeyG/GRASS</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41920/liftoff-an-accurate-tool-that-maps-annotations-in-gff-or-gtf-between-assemblies</guid>
	<pubDate>Tue, 30 Jun 2020 21:40:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41920/liftoff-an-accurate-tool-that-maps-annotations-in-gff-or-gtf-between-assemblies</link>
	<title><![CDATA[Liftoff: an accurate tool that maps annotations in GFF or GTF between assemblies]]></title>
	<description><![CDATA[<p><span>&nbsp;Liftoff, an accurate tool that maps annotations in GFF or GTF between assemblies of the same, or closely-related species. Unlike current coordinate lift-over tools which require a pre-generated &ldquo;chain&rdquo; file as input, Liftoff is a standalone tool that takes two genome assemblies and a reference annotation as input and outputs an annotation of the target genome.&nbsp;</span></p><p>Address of the bookmark: <a href="https://github.com/agshumate/Liftoff" rel="nofollow">https://github.com/agshumate/Liftoff</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34416/miniasm-very-fast-olc-based-de-novo-assembler-for-noisy-long-reads</guid>
	<pubDate>Mon, 27 Nov 2017 07:58:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34416/miniasm-very-fast-olc-based-de-novo-assembler-for-noisy-long-reads</link>
	<title><![CDATA[miniasm: very fast OLC-based de novo assembler for noisy long reads]]></title>
	<description><![CDATA[<p>Miniasm is a very fast OLC-based&nbsp;<em>de novo</em>&nbsp;assembler for noisy long reads. It takes all-vs-all read self-mappings (typically by&nbsp;<a href="https://github.com/lh3/minimap">minimap</a>) as input and outputs an assembly graph in the&nbsp;<a href="https://github.com/pmelsted/GFA-spec/blob/master/GFA-spec.md">GFA</a>&nbsp;format. Different from mainstream assemblers, miniasm does not have a consensus step. It simply concatenates pieces of read sequences to generate the final&nbsp;<a href="http://wgs-assembler.sourceforge.net/wiki/index.php/Celera_Assembler_Terminology">unitig</a>&nbsp;sequences. Thus the per-base error rate is similar to the raw input reads.</p>
<p>So far miniasm is in early development stage. It has only been tested on a dozen of PacBio and Oxford Nanopore (ONT) bacterial data sets. Including the mapping step, it takes about 3 minutes to assemble a bacterial genome. Under the default setting, miniasm assembles 9 out of 12 PacBio datasets and 3 out of 4 ONT datasets into a single contig. The 12 PacBio data sets are&nbsp;<a href="https://github.com/PacificBiosciences/DevNet/wiki/E.-coli-Bacterial-Assembly">PacBio E. coli sample</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS473430">ERS473430</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS544009">ERS544009</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS554120">ERS554120</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS605484">ERS605484</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS617393">ERS617393</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS646601">ERS646601</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS659581">ERS659581</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS670327">ERS670327</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS685285">ERS685285</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS743109">ERS743109</a>&nbsp;and a&nbsp;<a href="https://github.com/PacificBiosciences/DevNet/wiki/E.-coli-20kb-Size-Selected-Library-with-P6-C4/ce0533c1d2a957488594f0b29da61ffa3e4627e8">deprecated PacBio E. coli data set</a>. ONT data are acquired from the&nbsp;<a href="http://lab.loman.net/2015/09/24/first-sqk-map-006-experiment/">Loman Lab</a>.</p>
<p>For a&nbsp;<em>C. elegans</em>&nbsp;<a href="https://github.com/PacificBiosciences/DevNet/wiki/C.-elegans-data-set">PacBio data set</a>&nbsp;(only 40X are used, not the whole dataset), miniasm finishes the assembly, including reads overlapping, in ~10 minutes with 16 CPUs. The total assembly size is 105Mb; the N50 is 1.94Mb. In comparison, the&nbsp;<a href="https://github.com/PacificBiosciences/Bioinformatics-Training/wiki/HGAP">HGAP3</a>produces a 104Mb assembly with N50 1.61Mb.&nbsp;<a href="http://lh3lh3.users.sourceforge.net/download/ce-miniasm.png">This dotter plot</a>&nbsp;gives a global view of the miniasm assembly (on the X axis) and the HGAP3 assembly (on Y). They are broadly comparable. Of course, the HGAP3 consensus sequences are much more accurate. In addition, on the whole data set (assembled in ~30 min), the miniasm N50 is reduced to 1.79Mb. Miniasm still needs improvements.</p>
<p>Miniasm confirms that at least for high-coverage bacterial genomes, it is possible to generate long contigs from raw PacBio or ONT reads without error correction. It also shows that&nbsp;<a href="https://github.com/lh3/minimap">minimap</a>&nbsp;can be used as a read overlapper, even though it is probably not as sensitive as the more sophisticated overlapers such as&nbsp;<a href="https://github.com/marbl/MHAP">MHAP</a>&nbsp;and&nbsp;<a href="https://github.com/thegenemyers/DALIGNER">DALIGNER</a>. Coupled with long-read error correctors and consensus tools, miniasm may also be useful to produce high-quality assemblies.</p>
<p>Minimap and miniasm are ultrafast tools for (i) mapping and (ii) assembly. Designed for long, noisy reads, they do not have a correction or consensus step, and therefore the resulting assemblies are contiguous (i.e. long) but very noisy (i.e. full of errors)</p>
<p>We start with an all against all comparison:</p>
<div>
<pre><code>minimap -Sw5 -L100 -m0 -t8 reads.fq reads.fq | gzip -1 &gt; reads.paf.gz
</code></pre>
</div>
<p>Then we can assemble</p>
<div>
<pre><code>miniasm -f reads.fq reads.paf.gz &gt; reads.gfa
</code></pre>
</div>
<p>Convert GFA to FASTA:</p>
<div>
<pre><code>awk <span>'/^S/{print "&gt;"$2"\n"$3}'</span> reads.gfa | fold &gt; reads.fa
</code></pre>
</div>
<p>And then count how many contigs:</p>
<div>
<pre><code>grep <span>"&gt;"</span> reads.fa | wc -l</code></pre>
</div>
<p>&nbsp;</p>
<pre><span><span>#</span> Download sample PacBio from the PBcR website</span>
wget -O- http://www.cbcb.umd.edu/software/PBcR/data/selfSampleData.tar.gz <span>|</span> tar zxf -
ln -s selfSampleData/pacbio_filtered.fastq reads.fq
<span><span>#</span> Install minimap and miniasm (requiring gcc and zlib)</span>
git clone https://github.com/lh3/minimap <span>&amp;&amp;</span> (cd minimap <span>&amp;&amp;</span> make)
git clone https://github.com/lh3/miniasm <span>&amp;&amp;</span> (cd miniasm <span>&amp;&amp;</span> make)
<span><span>#</span> Overlap</span>
minimap/minimap -Sw5 -L100 -m0 -t8 reads.fq reads.fq <span>|</span> gzip -1 <span>&gt;</span> reads.paf.gz
<span><span>#</span> Layout</span>
miniasm/miniasm -f reads.fq reads.paf.gz <span>&gt;</span> reads.gfa</pre><p>Address of the bookmark: <a href="https://github.com/lh3/miniasm" rel="nofollow">https://github.com/lh3/miniasm</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37957/base-a-practical-de-novo-assembler-for-large-genomes-using-long-ngs-reads</guid>
	<pubDate>Fri, 19 Oct 2018 07:25:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37957/base-a-practical-de-novo-assembler-for-large-genomes-using-long-ngs-reads</link>
	<title><![CDATA[BASE: a practical de novo assembler for large genomes using long NGS reads]]></title>
	<description><![CDATA[<p><span>new&nbsp;</span><em>de novo</em><span>&nbsp;assembler called BASE. It enhances the classic seed-extension approach by indexing the reads efficiently to generate adaptive seeds that have high probability to appear uniquely in the genome. Such seeds form the basis for BASE to build extension trees and then to use reverse validation to remove the branches based on read coverage and paired-end information, resulting in high-quality consensus sequences of reads sharing the seeds. Such consensus sequences are then extended to contigs.</span></p><p>Address of the bookmark: <a href="https://github.com/dhlbh/BASE" rel="nofollow">https://github.com/dhlbh/BASE</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

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