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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44497?offset=10</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38745/osprey-network-visualization-system</guid>
	<pubDate>Sun, 20 Jan 2019 05:34:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38745/osprey-network-visualization-system</link>
	<title><![CDATA[Osprey: Network Visualization System]]></title>
	<description><![CDATA[<p>Osprey is a software platform for the visualization of complex biological interaction networks. Osprey builds data-rich graphical representations from&nbsp;<a href="http://geneontology.org/" title="GENE ONTOLOGY CONSORTIUM">Gene Ontology (GO)</a>&nbsp;annotated interaction data maintained by the&nbsp;<a href="https://thebiogrid.org/" title="The BioGRID">BioGRID</a>.</p>
<p>Osprey is developed by the&nbsp;<a href="http://www.tyerslab.com/">TyersLab</a>&nbsp;and is a part of the&nbsp;<a href="https://thebiogrid.org/" title="The BioGRID">BioGRID</a>&nbsp;family of software. It utilizes both&nbsp;<a href="https://www.mysql.com/" title="MySQL Database">MySQL</a>&nbsp;and&nbsp;<a href="http://openjdk.java.net/" title="OpenJDK">Java</a>&nbsp;to operate and is compatible with&nbsp;<a href="https://www.microsoft.com/en-us/windows/" title="Microsoft Windows">Windows</a>,&nbsp;<a href="http://www.ubuntu.com/">Linux</a>, and&nbsp;<a href="http://www.apple.com/" title="Apple">Apple</a>&nbsp;operating systems.</p>
<p>These works were published in&nbsp;<strong>Breitkreutz, BJ., Stark, C., Tyers M. "Osprey: A Network Visualization System." Genome Biology 2003 4(3):R22</strong>&nbsp;<a href="http://genomebiology.com/2003/4/3/R22" title="Genome Biology">[Genome Biology]</a>&nbsp;<a href="http://genomebiology.com/content/pdf/gb-2003-4-3-r22.pdf" title="Osprey PDF">[PDF]</a>&nbsp;<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;list_uids=12620107&amp;dopt=Abstract" title="Pubmed">[PubMed]</a>&nbsp;and supported by the&nbsp;<a href="http://www.nih.gov/" title="NIH">National Institutes of Health</a>,&nbsp;<a href="http://www.cihr-irsc.gc.ca/" title="CIHR">Canadian Institutes of Health Research</a>, and&nbsp;<a href="http://www.genomecanada.ca/en/" title="Genome Canada">Genome Canada</a>.</p><p>Address of the bookmark: <a href="https://osprey.thebiogrid.org/" rel="nofollow">https://osprey.thebiogrid.org/</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
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	<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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39728/patterns-a-modeling-tool-dedicated-to-biological-network-modeling</guid>
	<pubDate>Fri, 26 Jul 2019 01:11:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39728/patterns-a-modeling-tool-dedicated-to-biological-network-modeling</link>
	<title><![CDATA[Patterns: a modeling tool dedicated to biological network modeling]]></title>
	<description><![CDATA[<p>It is designed to work with <strong>patterned data</strong>. Famous examples of problems related to patterned data are:</p>
<ul>
<li>recovering <strong>signals</strong> in networks after a <strong>stimulation</strong> (cascade network reverse engineering),</li>
<li>analysing <strong>periodic signals</strong>.</li>
</ul><p>Address of the bookmark: <a href="https://github.com/fbertran/Patterns" rel="nofollow">https://github.com/fbertran/Patterns</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/41804/useful-links-to-therapy-disease-drug-and-drug-target-network-data</guid>
	<pubDate>Mon, 01 Jun 2020 11:47:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/41804/useful-links-to-therapy-disease-drug-and-drug-target-network-data</link>
	<title><![CDATA[Useful links to therapy, disease, drug and drug-target network data:]]></title>
	<description><![CDATA[<p>Useful links to therapy, disease, drug and drug-target network data:</p><p><strong>DrugBank:</strong></p><p>a bioinformatics- cheminformatics resource combining detailed drug data with comprehensive drug target information with &gt;4900 drug (~3500 experimental) and &gt;1500 non-redundant protein entries http://www.drugbank.ca/</p><p><strong>Drug-Target Network:</strong></p><p>network data of 890 drugs and 394 target human proteins http://www.nature.com/nbt/journal/v25/ n10/suppinfo/nbt1338_S1.html</p><p><strong>Drug-Therapy Network:</strong></p><p>three layers of drug-therapy networks according to the ATC classification http://www.biomedcentral.com/1471-2210/8/5/additional/</p><p><strong>FDA Orange Book:</strong></p><p>approved drug products with therapeutic equivalence evaluations http://www.fda.gov/cder/ob/HIDdb: Thomson Investigational drugs database including information on 107000 patents, 25000 investigational drugs and 80000 chemical structures http://scientific.thomson.com/products/iddb/HOMIM: a knowledgebase of human genes and genetic disorders http://www.ncbi.nlm.nih.gov/ sites/entrez?db=omim</p><p><strong>PDTD:</strong></p><p>3D drug target structure database with a target identification option http://www.dddc.ac.cn/pdtd/</p><p><strong>Predicted drug targets:</strong></p><p>a set of 1383 predicted drug targets http://www.biomedcentral.com/1471-2105/8/353/additional/ [25] Protein ligand network: a network of 4208 ligands and ~15000 binding sites http://pbil.kaist.ac.kr/~parkkw/Lnet/</p><p><strong>TDR Targets Database:</strong></p><p>identification and ranking targets against neglected tropical diseases http://tdrtargets.org/</p><p><strong>Therapeutic Target Database:</strong></p><p>lists &gt;1500 therapeutic targets, disease conditions and corresponding drugs http://xin.cz3.nus.edu.sg/group/cjttd/ttd.asp</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29635/r-graphs</guid>
	<pubDate>Fri, 04 Nov 2016 10:48:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29635/r-graphs</link>
	<title><![CDATA[R Graphs !!]]></title>
	<description><![CDATA[<p><span>The blog is a collection of script examples with example data and output plots. R produce excellent quality graphs for data analysis, science and business presentation, publications and other purposes. Self-help codes and examples are provided. Enjoy nice graphs !!</span></p><p>Address of the bookmark: <a href="http://rgraphgallery.blogspot.be/" rel="nofollow">http://rgraphgallery.blogspot.be/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35896/phylographer-graph-visualization-tool</guid>
	<pubDate>Wed, 07 Mar 2018 18:11:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35896/phylographer-graph-visualization-tool</link>
	<title><![CDATA[PhyloGrapher - Graph Visualization Tool]]></title>
	<description><![CDATA[<p><strong>PhyloGrapher</strong><span>&nbsp;is a program designed to visualize and study evolutionary relationships within families of homologous genes or proteins (elements).&nbsp;</span><strong>PhyloGrapher</strong><span>&nbsp;is a drawing tool that generates custom graphs for a given set of elements. In general, it is possible to use&nbsp;</span><strong>PhyloGrapher</strong><span>&nbsp;to visualize any type of relations between elements.&nbsp;</span></p>
<p><span>https://www.youtube.com/watch?v=WgufqYMHCvM</span></p><p>Address of the bookmark: <a href="http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html" rel="nofollow">http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44445/ppanggolin-depicting-microbial-species-diversity-via-a-partitioned-pangenome-graph-of-linked-neighbors</guid>
	<pubDate>Thu, 01 Feb 2024 00:24:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44445/ppanggolin-depicting-microbial-species-diversity-via-a-partitioned-pangenome-graph-of-linked-neighbors</link>
	<title><![CDATA[PPanGGOLiN: Depicting microbial species diversity via a Partitioned PanGenome Graph Of Linked Neighbors]]></title>
	<description><![CDATA[<p dir="auto"><span>PPanGGOLiN</span>&nbsp;(<a href="https://doi.org/10.1371/journal.pcbi.1007732">Gautreau et al. 2020</a>) is a software suite used to create and manipulate prokaryotic pangenomes from a set of either genomic DNA sequences or provided genome annotations. It is designed to scale up to tens of thousands of genomes. It has the specificity to partition the pangenome using a statistical approach rather than using fixed thresholds which gives it the ability to work with low-quality data such as&nbsp;<em>Metagenomic Assembled Genomes (MAGs)</em>&nbsp;or&nbsp;<em>Single-cell Amplified Genomes (SAGs)</em>&nbsp;thus taking advantage of large scale environmental studies and letting users study the pangenome of uncultivable species.</p>
<p dir="auto">A complete documentation is available&nbsp;<a href="https://ppanggolin.readthedocs.io/">here</a>.</p>
<p dir="auto" style="text-align: center;"><a href="https://github.com/labgem/PPanGGOLiN/blob/master/docs/_static/logo.png" target="_blank"><img src="https://github.com/labgem/PPanGGOLiN/raw/master/docs/_static/logo.png" alt="logo" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/labgem/PPanGGOLiN" rel="nofollow">https://github.com/labgem/PPanGGOLiN</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38212/megahit-an-ultra-fast-single-node-solution-for-large-and-complex-metagenomics-assembly-via-succinct-de-bruijn-graph</guid>
	<pubDate>Wed, 14 Nov 2018 04:50:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38212/megahit-an-ultra-fast-single-node-solution-for-large-and-complex-metagenomics-assembly-via-succinct-de-bruijn-graph</link>
	<title><![CDATA[MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph]]></title>
	<description><![CDATA[<p><span>MEGAHIT is a single node assembler for large and complex metagenomics NGS reads, such as soil. It makes use of succinct&nbsp;</span><em>de Bruijn</em><span>&nbsp;graph (SdBG) to achieve low memory assembly. MEGAHIT can&nbsp;</span><span>optionally</span><span>&nbsp;utilize a CUDA-enabled GPU to accelerate its SdBG contstruction. The GPU-accelerated version of MEGAHIT has been tested on NVIDIA GTX680 (4G memory) and Tesla K40c (12G memory) with CUDA 5.5, 6.0 and 6.5. MEGAHIT v1.0 or greater also supports IBM Power PC and has been tested on IBM POWER8.</span></p>
<p><span>https://academic.oup.com/bioinformatics/article/31/10/1674/177884</span></p><p>Address of the bookmark: <a href="https://github.com/voutcn/megahit" rel="nofollow">https://github.com/voutcn/megahit</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42806/graphunzip-phases-an-assembly-graph-using-hi-c-data-andor-long-reads</guid>
	<pubDate>Fri, 05 Feb 2021 21:22:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42806/graphunzip-phases-an-assembly-graph-using-hi-c-data-andor-long-reads</link>
	<title><![CDATA[GraphUnzip: Phases an assembly graph using Hi-C data and/or long reads.]]></title>
	<description><![CDATA[<p>GraphUnzip, a fast, memory-efficient and accurate tool to unzip assembly graphs into their constituent haplotypes using long reads and/or Hi-C data. As GraphUnzip only connects sequences in the assembly graph that already had a potential link based on overlaps, it yields high-quality gap-less supercontigs. To demonstrate the efficiency of GraphUnzip, we tested it on a simulated diploid Escherichia coli genome, and on two real datasets for the genomes of the rotifer Adineta vaga and the potato Solanum tuberosum. In all cases, GraphUnzip yielded highly continuous phased assemblies.</p>
<p>https://www.biorxiv.org/content/biorxiv/early/2021/02/01/2021.01.29.428779.full.pdf</p><p>Address of the bookmark: <a href="https://github.com/nadegeguiglielmoni/GraphUnzip" rel="nofollow">https://github.com/nadegeguiglielmoni/GraphUnzip</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44887/alfapang-alignment-free-algorithm-for-pangenome-graph-construction</guid>
	<pubDate>Thu, 28 Aug 2025 02:56:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44887/alfapang-alignment-free-algorithm-for-pangenome-graph-construction</link>
	<title><![CDATA[AlfaPang: alignment free algorithm for pangenome graph construction]]></title>
	<description><![CDATA[<p><span>AlfaPang constructs variation graphs, leveraging its alignment-free and reference-free approach, based solely on intrinsic sequence properties. This design allows AlfaPang's runtime and memory usage to scale linearly with the size of input sequences, enabling it to handle significantly larger genome sets compared to other methods.</span></p><p>Address of the bookmark: <a href="https://github.com/AdamCicherski/AlfaPang" rel="nofollow">https://github.com/AdamCicherski/AlfaPang</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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