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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44616?offset=50</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37584/mulan-multiple-sequence-local-alignment-and-visualization-for-studying-function-and-evolution</guid>
	<pubDate>Fri, 24 Aug 2018 09:50:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37584/mulan-multiple-sequence-local-alignment-and-visualization-for-studying-function-and-evolution</link>
	<title><![CDATA[Mulan: Multiple-sequence local alignment and visualization for studying function and evolution]]></title>
	<description><![CDATA[<p>Mulan: Multiple-sequence local alignment and visualization for studying function and evolution</p>
<p><span>Mulan (</span><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC540288/#ref44">http://mulan.dcode.org/</a><span>), a novel method and a network server for comparing multiple draft and finished-quality sequences to identify functional elements conserved over evolutionary time. Mulan brings together several novel algorithms: the TBA multi-aligner program for rapid identification of local sequence conservation, and the multiTF program for detecting evolutionarily conserved transcription factor binding sites in multiple alignments. In addition, Mulan supports two-way communication with the GALA database; alignments of multiple species dynamically generated in GALA can be viewed in Mulan, and conserved transcription factor binding sites identified with Mulan/multiTF can be integrated and overlaid with extensive genome annotation data using GALA.</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC540288/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC540288/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38449/koala-keggs-internal-annotation-tool-for-k-number-assignment-of-kegg-genes-using-ssearch-computation</guid>
	<pubDate>Wed, 12 Dec 2018 09:16:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38449/koala-keggs-internal-annotation-tool-for-k-number-assignment-of-kegg-genes-using-ssearch-computation</link>
	<title><![CDATA[KOALA: KEGG&#039;s internal annotation tool for K number assignment of KEGG GENES using SSEARCH computation]]></title>
	<description><![CDATA[<p>KOALA (KEGG Orthology And Links Annotation) is KEGG's internal annotation tool for&nbsp;<a href="https://www.kegg.jp/kegg/ko.html">K number</a>&nbsp;assignment of KEGG GENES using SSEARCH computation. BlastKOALA and GhostKOALA assign K numbers to the user's sequence data by&nbsp;<a href="http://www.ncbi.nlm.nih.gov/blast/">BLAST</a>&nbsp;and&nbsp;<a href="http://www.bi.cs.titech.ac.jp/ghostx/">GHOSTX</a>&nbsp;searches, respectively, against a nonredundant set of KEGG GENES. Annotate Sequence in KEGG Mapper and Pathogen Checker in KEGG Pathogen are special interfaces to the BlastKOALA server and can be executed in an interactive mode. &nbsp;&nbsp; See&nbsp;<a href="https://www.kegg.jp/blastkoala/help_blastkoala.html" target="_blastkoala">Step-by-step Instructions</a>.</p>
<div>Reference: Kanehisa, M., Sato, Y., and Morishima, K. (2016) BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J. Mol. Biol. 428, 726-731. [<a href="http://www.ncbi.nlm.nih.gov/pubmed/26585406">pubmed</a>] [<a href="https://doi.org/10.1016/j.jmb.2015.11.006">pdf</a>]</div><p>Address of the bookmark: <a href="https://www.kegg.jp/blastkoala/" rel="nofollow">https://www.kegg.jp/blastkoala/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/4943/molecular-genetics-lecture</guid>
	<pubDate>Fri, 27 Sep 2013 04:24:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/4943/molecular-genetics-lecture</link>
	<title><![CDATA[Molecular Genetics Lecture]]></title>
	<description><![CDATA[<p><span>"Robert Sapolsky makes interdisciplinary connections between behavioral biology and molecular genetic influences. He relates protein synthesis and point mutations to microevolutionary change, and discusses conflicting theories of gradualism and punctuated equilibrium and the influence of epigenetics on development theories."&nbsp;</span></p>
<p><span>"<span><strong>Robert Sapolsky</strong> is an American neuroendocrinologist, professor of biology, neuroscience, and neurosurgery at Stanford University, researcher and author" ----Wikipedia</span></span></p><p>Address of the bookmark: <a href="http://www.youtube.com/watch?v=_dRXA1_e30o" rel="nofollow">http://www.youtube.com/watch?v=_dRXA1_e30o</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42359/dnasp-dna-sequence-polymorphism-is-a-software-package-for-the-analysis-of-dna-polymorphisms</guid>
	<pubDate>Wed, 25 Nov 2020 19:51:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42359/dnasp-dna-sequence-polymorphism-is-a-software-package-for-the-analysis-of-dna-polymorphisms</link>
	<title><![CDATA[DnaSP: DNA Sequence Polymorphism, is a software package for the analysis of DNA polymorphisms]]></title>
	<description><![CDATA[<p><span>DnaSP, DNA Sequence Polymorphism, is a software package for the analysis of DNA polymorphisms using data from a single locus (a multiple sequence aligned -MSA data), or from several loci (a Multiple-MSA data, such as formats generated by some assembler RAD-seq software). DnaSP can estimate several measures of DNA sequence variation within and between populations in noncoding, synonymous or nonsynonymous sites, or in various sorts of codon positions), as well as linkage disequilibrium, recombination, gene flow and gene conversion parameters.</span></p><p>Address of the bookmark: <a href="http://www.ub.edu/dnasp/" rel="nofollow">http://www.ub.edu/dnasp/</a></p>]]></description>
	<dc:creator>Neel</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/36994/minimap2-a-versatile-pairwise-aligner-for-genomic-and-spliced-nucleotide-sequences</guid>
	<pubDate>Wed, 20 Jun 2018 07:55:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36994/minimap2-a-versatile-pairwise-aligner-for-genomic-and-spliced-nucleotide-sequences</link>
	<title><![CDATA[minimap2: A versatile pairwise aligner for genomic and spliced nucleotide sequences]]></title>
	<description><![CDATA[git clone https://github.com/lh3/minimap2
cd minimap2 &amp;&amp; make
# long sequences against a reference genome
./minimap2 -a test/MT-human.fa test/MT-orang.fa &gt; test.sam
# create an index first and then map
./minimap2 -d MT-human.mmi test/MT-human.fa
./minimap2 -a MT-human.mmi test/MT-orang.fa &gt; test.sam
# use presets (no test data)
./minimap2 -ax map-pb ref.fa pacbio.fq.gz &gt; aln.sam       # PacBio genomic reads
./minimap2 -ax map-ont ref.fa ont.fq.gz &gt; aln.sam         # Oxford Nanopore genomic reads
./minimap2 -ax sr ref.fa read1.fa read2.fa &gt; aln.sam      # short genomic paired-end reads
./minimap2 -ax splice ref.fa rna-reads.fa &gt; aln.sam       # spliced long reads
./minimap2 -ax splice -k14 -uf ref.fa reads.fa &gt; aln.sam  # Nanopore Direct RNA-seq
./minimap2 -cx asm5 asm1.fa asm2.fa &gt; aln.paf             # intra-species asm-to-asm alignment
./minimap2 -x ava-pb reads.fa reads.fa &gt; overlaps.paf     # PacBio read overlap
./minimap2 -x ava-ont reads.fa reads.fa &gt; overlaps.paf    # Nanopore read overlap
# man page for detailed command line options
man ./minimap2.1<p>Address of the bookmark: <a href="https://github.com/lh3/minimap2" rel="nofollow">https://github.com/lh3/minimap2</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44479/doubletrouble-identify-duplicated-genes-from-whole-genome-protein-sequences-and-classify</guid>
	<pubDate>Tue, 05 Mar 2024 00:23:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44479/doubletrouble-identify-duplicated-genes-from-whole-genome-protein-sequences-and-classify</link>
	<title><![CDATA[doubletrouble: identify duplicated genes from whole-genome protein sequences and classify]]></title>
	<description><![CDATA[<p><span>doubletrouble aims to identify duplicated genes from whole-genome protein sequences and classify them based on their modes of duplication. The duplication modes are i. segmental duplication (SD); ii. tandem duplication (TD); iii. proximal duplication (PD); iv. transposed duplication (TRD) and; v. dispersed duplication (DD). Transposon-derived duplicates (TRD) can be further subdivided into rTRD (retrotransposon-derived duplication) and dTRD (DNA transposon-derived duplication). If users want a simpler classification scheme, duplicates can also be classified into SD- and SSD-derived (small-scale duplication) gene pairs. Besides classifying gene pairs, users can also classify genes, so that each gene is assigned a unique mode of duplication. Users can also calculate substitution rates per substitution site (i.e., Ka and Ks) from duplicate pairs, find peaks in Ks distributions with Gaussian Mixture Models (GMMs), and classify gene pairs into age groups based on Ks peaks.</span></p><p>Address of the bookmark: <a href="https://bioconductor.org/packages/release/bioc/html/doubletrouble.html" rel="nofollow">https://bioconductor.org/packages/release/bioc/html/doubletrouble.html</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45349/finding-the-hidden-switches-the-story-of-kinext-and-protein-kinases</guid>
	<pubDate>Thu, 24 Sep 2026 02:51:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45349/finding-the-hidden-switches-the-story-of-kinext-and-protein-kinases</link>
	<title><![CDATA[Finding the Hidden Switches: The Story of KiNext and Protein Kinases]]></title>
	<description><![CDATA[<p>Every newly sequenced genome contains thousands of proteins, but identifying what each protein does is a much harder task. Among these proteins are protein kinases, important molecular regulators that control processes such as cell growth, development, metabolism, stress responses, and signaling. Finding these kinases and determining which families they belong to can reveal important clues about how an organism functions and has evolved.</p><p>This is where KiNext comes into the picture. Introduced in a 2024 study published in BMC Bioinformatics, KiNext is a computational workflow designed to identify and classify protein kinases from predicted protein sequences. Instead of relying on a single search method, it brings together several approaches, including Hidden Markov Models, sequence alignment, phylogenetic analysis, and structural comparison.</p><p>The search begins with a simple question: does a protein contain the characteristics of a kinase? Protein kinases can change considerably during evolution, but important regions of their sequences often retain recognizable patterns. KiNext uses Hidden Markov Models, or HMMs, to detect these patterns. An HMM does not require a protein to be an exact match to a known kinase. Instead, it looks for a statistical sequence signature associated with kinase proteins, making it possible to detect more distant candidates.</p><p>Once potential kinases are identified, KiNext takes the analysis further. It distinguishes conventional eukaryotic protein kinases from atypical protein kinases and then attempts to classify them into different kinase groups and families. This distinction is important because simply identifying a protein as a kinase does not tell the complete story. Different kinase families can have very different evolutionary histories and biological functions.</p><p>The next stage brings evolution into the picture. KiNext can align kinase sequences and construct phylogenetic trees, allowing researchers to examine how newly identified proteins are related to previously characterized kinases. When sequence evidence alone is difficult to interpret, structural information can provide another clue. The workflow can incorporate AlphaFold-predicted structures and Foldseek-based structural comparisons to investigate whether an unusual protein resembles known kinase structures.</p><p>The researchers tested KiNext using two very different organisms: the Pacific oyster, Crassostrea gigas, and the green alga Ostreococcus tauri. In C. gigas, KiNext recovered previously reported kinases while identifying additional candidates. Structural analysis provided further evidence for many of the newly detected proteins. In O. tauri, the workflow similarly recovered most previously reported kinases and identified additional candidates while refining some of their classifications.</p><p>What makes KiNext particularly interesting is not just its ability to find kinases, but how the entire analysis is organized. The workflow uses Nextflow, allowing the different computational steps to be connected into a reproducible pipeline. Containers can also help manage software dependencies, making it easier to run the workflow across different computing environments.</p><p>This reproducibility becomes increasingly important as the number of available genomes continues to grow. A researcher studying one organism may be able to perform an analysis manually, but repeating the same process across hundreds or thousands of genomes quickly becomes impractical. A standardized workflow provides a way to perform the analysis consistently while keeping track of how the results were generated.</p><p>At its core, KiNext demonstrates a broader change taking place in modern genomics. Sequencing a genome provides an enormous amount of information, but the real scientific challenge begins afterward: understanding what all those sequences mean. Protein kinases are only one part of this larger puzzle, yet they are particularly important because they act as molecular switches throughout the cell.</p><p>By combining sequence profiles, evolutionary analysis, and structural evidence within a reproducible computational framework, KiNext provides researchers with a systematic way to uncover these molecular switches. Its real value lies not only in finding more kinases, but in making the process scalable, repeatable, and easier to apply to new genomes.</p><p>As genome sequencing continues to expand across the tree of life, tools such as KiNext can help turn enormous collections of protein sequences into meaningful biological stories&mdash;one kinase at a time.</p><p>Read more about it @</p><p>https://link.springer.com/article/10.1186/s12859-024-05953-w</p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39372/irnad-a-computational-tool-for-identifying-d-modification-sites-in-rna-sequence</guid>
	<pubDate>Thu, 16 May 2019 00:20:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39372/irnad-a-computational-tool-for-identifying-d-modification-sites-in-rna-sequence</link>
	<title><![CDATA[iRNAD: a computational tool for identifying D modification sites in RNA sequence]]></title>
	<description><![CDATA[<p><span>iRNAD, for identifying D modification sites in RNA sequence. In this predictor, the RNA samples derived from five species were encoded by nucleotide chemical property and nucleotide density. Support vector machine was utilized to perform the classification.&nbsp;</span></p>
<p><span><a href="http://lin-group.cn/server/iRNAD/">http://lin-group.cn/server/iRNAD/</a></span></p><p>Address of the bookmark: <a href="http://lin-group.cn/server/iRNAD/" rel="nofollow">http://lin-group.cn/server/iRNAD/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37796/grsr-a-tool-for-deriving-genome-rearrangement-scenarios-from-multiple-unichromosomal-genome-sequences</guid>
	<pubDate>Fri, 28 Sep 2018 09:35:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37796/grsr-a-tool-for-deriving-genome-rearrangement-scenarios-from-multiple-unichromosomal-genome-sequences</link>
	<title><![CDATA[GRSR: a tool for deriving genome rearrangement scenarios from multiple unichromosomal genome sequences]]></title>
	<description><![CDATA[<p>GRSR is a Tool for Deriving Genome Rearrangement Scenarios for Multiple Uni-chromosomal Genomes. This tool will do the following steps:</p>
<ul>
<li>Step 1. Run mugsy to get multiple sequence alignment results.</li>
<li>Step 2 &amp; 3. Extraction of the Coordinates of Core Blocks, Construction of Synteny Blocks and Generating Signed Permutations.</li>
<li>Step 4. Generate pairwise genome rearrangement scenarios and find repeats at the breakpoints of each rearrangement events.</li>
<li></li>
<li></li>
</ul>
<p>https://github.com/DanwangJessica/GRSR</p><p>Address of the bookmark: <a href="https://github.com/DanwangJessica/GRSR" rel="nofollow">https://github.com/DanwangJessica/GRSR</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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