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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44672?offset=270</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36373/tools-to-predict-the-impact-of-missense-variants</guid>
	<pubDate>Mon, 23 Apr 2018 12:57:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36373/tools-to-predict-the-impact-of-missense-variants</link>
	<title><![CDATA[Tools to Predict the Impact of Missense Variants !]]></title>
	<description><![CDATA[<p><span>Prioritizing missense variants for further experimental investigation is a key challenge in current sequencing studies for exploring complex and Mendelian diseases. A large number of&nbsp;</span><em>in silico</em><span>&nbsp;tools have been employed for the task of pathogenicity prediction, including PolyPhen‐2, SIFT, FatHMM, MutationTaster‐2, MutationAssessor, Combined Annotation Dependent Depletion, LRT, phyloP, and GERP++, as well as optimized methods of combining tool scores, such as Condel and Logit. Due to the wealth of these methods, an important practical question to answer is which of these tools generalize best, that is, correctly predict the pathogenic character of new variants. </span></p><p><span>Study of 10 tools on five datasets that such a comparative evaluation of these tools is hindered by two types of circularity: they arise due to (1) the same variants or (2) different variants from the same protein occurring both in the datasets used for training and for evaluation of these tools, which may lead to overly optimistic results. Comparative evaluations of predictors that do not address these types of circularity may erroneously conclude that circularity confounded tools are most accurate among all tools, and may even outperform optimized combinations of tools.</span></p><p><span>Following tools are useful for mis sense muation detection ...&nbsp;</span></p><p>PolyPhen‐2 (PP2)<br />&ldquo;Predicts possible impact of an amino acid substitution on the structure and function of a human protein using straightforward physical and comparative considerations&rdquo;</p><p>MutationTaster‐2 (MT2)<br />&ldquo;Evaluation of the disease‐causing potential of DNA sequence alterations&rdquo;</p><p>MutationAssessor (MASS)<br />&ldquo;Predicts the functional impact of amino acid substitutions in proteins, such as mutations discovered in cancer or missense polymorphisms&rdquo;</p><p>LRT<br />&ldquo;Identify a subset of deleterious mutations that disrupt highly conserved amino acids within protein‐coding sequences, which are likely to be unconditionally deleterious&rdquo;</p><p>SIFT<br />&ldquo;Predicts whether an amino acid substitution affects protein function&rdquo;</p><p>GERP++<br />&ldquo;Identifies constrained elements in multiple alignments by quantifying substitution deficits. These deficits represent substitutions that would have occurred if the element were neutral DNA, but did not occur because the element has been under functional constraint. We refer to these deficits as &ldquo;rejected substitutions.&rdquo; Rejected substitutions are a natural measure of constraint that reflects the strength of past purifying selection on the element&rdquo;</p><p>phyloP<br />&ldquo;Compute conservation or acceleration P values based on an alignment and a model of neutral evolution&rdquo;</p><p>FatHMM unweighted (FatHMM‐U)<br />Predicts &ldquo;functional consequences of both coding variants, that is, nonsynonymous single‐nucleotide variants, and noncoding variants&rdquo;</p><p>FatHMM weighted (FatHMM‐W)<br />Predicts &ldquo;functional consequences of both coding variants, that is, nonsynonymous single‐nucleotide variants, and noncoding variants&rdquo; and its weighting scheme attributes higher tolerance scores to SNVs in proteins, related proteins, or domains that already include a high fraction of pathogenic variantsh</p><p>Combined Annotation Dependent Depletion (CADD)<br />&ldquo;CADD is a tool for scoring the deleteriousness of single‐nucleotide variants as well as insertion/deletions variants in the human genome&rdquo;</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36398/tools-for-protein-protein-docking</guid>
	<pubDate>Wed, 25 Apr 2018 05:15:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36398/tools-for-protein-protein-docking</link>
	<title><![CDATA[Tools for Protein-Protein Docking !]]></title>
	<description><![CDATA[<p>Predicting the structure of protein&ndash;protein complexes using docking approaches is a difficult problem whose major challenges include identifying correct solutions, and properly dealing with molecular flexibility and conformational changes. Following are the tools to predict&nbsp;<span>the structure of protein&ndash;protein complexes:</span></p><p><a href="http://www.sbg.bio.ic.ac.uk/docking/index.html" target="_blank">3D-Dock Suite</a></p><p>Global rigid search: FFTShape complementarity and electrostatics</p><p>Re-scoring and clustering. Refinement of interface side-chains</p><p><a href="http://www.sbg.bio.ic.ac.uk/~3dgarden/" target="_blank">3D-Garden</a></p><p>Global rigid search in ensamble</p><p>Shape complementarity and Lennard&ndash;Jones potential</p><p>Side chain and backbone dihedral refinement</p><p><a href="http://www.sdsc.edu/CCMS/DOT/" target="_blank">DOT</a></p><p>Global rigid search: FFTShape complementarity, electrostatics and VDWNone</p><p><a href="http://users.unimi.it/~ddl/escherng/index.htm" target="_blank">Escher NG</a></p><p>Global rigid searchShape complementarity, hydrogen bonds and electrostatic</p><p>Integrated in&nbsp;<a href="http://users.unimi.it/~ddl/vega/download.htm" target="_blank">VEGA</a></p><p><a href="http://vakser.bioinformatics.ku.edu/resources/gramm/gramm1" target="_blank">GRAMM</a>&nbsp;</p><p>Global rigid search: FFT. smooth protein surface representation for soft docking</p><p>Shape complementarity and Lennard-Jones potential</p><p>Clustering of conformations</p><p><a href="http://vakser.bioinformatics.ku.edu/resources/gramm/grammx/" target="_blank">GRAMM-X</a>&nbsp;</p><p>Global rigid search: FFT. smooth protein surface representation for soft docking</p><p>Shape complementarity and Lennard-Jones potentialminimization and re-scoring with multiple filters</p><p><a href="http://www.loria.fr/~ritchied/hex_server/" target="_blank">HEX</a></p><p>Global rigid search: Fourier correlation of spherical harmonics</p><p>Shape complementarity</p><p><a href="http://www.csd.abdn.ac.uk/hex/" target="_blank"></a><a href="http://haddock.chem.uu.nl/Haddock/haddock.php" target="_blank">HADDOCK</a></p><p>Global rigid searchElectrostatic ,VDW and desolvation energy termsMD simulated annealing refinement . Filtering based on external data.&nbsp;</p><p><a href="http://www.molsoft.com/docking.html">ICM</a></p><p>Global rigid search: Monte CarloEmpirical scoring function</p><p>Clustering and selection of conformations. Refinement of interface side-chains and re-scoring</p><p><a href="http://www.weizmann.ac.il/Chemical_Research_Support/molfit/" target="_blank">MolFit&nbsp;</a></p><p>Global rigid search: FFTShape complementarity</p><p>Clustering of good solutions, filtering using&nbsp;<em>a priori&nbsp;</em>information and small, local rigid rotations around selected conformations</p><p><a href="http://bioinfo3d.cs.tau.ac.il/PatchDock/" target="_blank">PatchDock</a></p><p>Global rigid searchShape complementarity and atomic desolvation energy</p><p>Clustering of conformations</p><p><a href="http://inb.bsc.es/gn6/PyDock" target="_blank">PyDock</a></p><p>Global rigid search:FFTShape complementarity</p><p>rescoring by binding electrostatics and desolvation energy</p><p><a href="http://bioinfo3d.cs.tau.ac.il/PatchDock/" target="_blank"></a><a href="http://rosettadock.graylab.jhu.edu/" target="_blank">RosettaDock</a></p><p>Local rigid search: Monte Carlo with low and high resolution structure representation levels</p><p>Different scoring parameters for the different resolutions&nbsp;</p><p><a href="http://zlab.bu.edu/zdock/" target="_blank">ZDOCK</a></p><p>Global rigid search: FFTShape complementarity, desolvation energy, and electrostatics.</p><p>Energy minimization and re-scoringFree for academics</p><p>&nbsp;</p><p>Point to note:</p><p>The proper treatment of flexibility in protein&ndash;protein docking is still an active field of research. You first should analyzed your proteins in order to define their conformational space and then choose the most suitable method for your docking problem.</p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36514/evidentialgene-tr2aacds-mrna-transcript-assembly-software</guid>
	<pubDate>Tue, 08 May 2018 04:39:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36514/evidentialgene-tr2aacds-mrna-transcript-assembly-software</link>
	<title><![CDATA[EvidentialGene: tr2aacds, mRNA Transcript Assembly Software]]></title>
	<description><![CDATA[<p><span>EvidentialGene is a genome informatics project, "Evidence Directed Gene Construction for Eukaryotes", to construct high quality, accurate gene sets for animals and plants, developed by Don Gilbert at Indiana University, see</span><br><a href="http://arthropods.eugenes.org/EvidentialGene/" target="_blank">http://arthropods.eugenes.org/EvidentialGene/<span></span></a><br><br><span>Construction refers to the combination of classical gene prediction, and more recent gene assembly (de-novo and genome-assisted) methods. The basic Evigene methods involve using available best-of-breed gene prediction and assembly software, combining all evidence for genes, from expressed sequences, genome assembly sequences, related species protein sequences, and any other, to annotate and score gene constructions. Over-produced constructions are classified by gene evidence for best qualities per "locus", including genome-aligned and gene-transcript aligned (genome-free) locus identification. All software developed for EvidentialGene is publicly available. See project wiki/blog for notes.</span></p>
<p><span>Download&nbsp;</span></p>
<p>http://arthropods.eugenes.org/EvidentialGene/trassembly.html</p>
<p>https://sourceforge.net/p/evidentialgene/blog/</p><p>Address of the bookmark: <a href="http://arthropods.eugenes.org/EvidentialGene/trassembly.html" rel="nofollow">http://arthropods.eugenes.org/EvidentialGene/trassembly.html</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43546/introduction-to-phylogenies-in-r</guid>
	<pubDate>Wed, 13 Oct 2021 02:27:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43546/introduction-to-phylogenies-in-r</link>
	<title><![CDATA[Introduction to phylogenies in R]]></title>
	<description><![CDATA[<p><span>R phylogenetics is built on the contributed packages for phylogenetics in R, and there are many such packages. Let's begin today by installing a few critical packages, such as ape, phangorn, phytools, and geiger. To get the most recent CRAN version of these packages, you will need to have R 3.3.x installed on your computer!</span></p><p>Address of the bookmark: <a href="http://www.phytools.org/Cordoba2017/ex/2/Intro-to-phylogenies.html" rel="nofollow">http://www.phytools.org/Cordoba2017/ex/2/Intro-to-phylogenies.html</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43999/tools-for-differential-expression-analysis</guid>
	<pubDate>Tue, 08 Nov 2022 03:40:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43999/tools-for-differential-expression-analysis</link>
	<title><![CDATA[Tools for Differential expression analysis]]></title>
	<description><![CDATA[<p><span>apeglm</span>&nbsp;-&nbsp;<a href="https://bioconductor.org/packages/release/bioc/html/apeglm.html" target="_blank">https://bioconductor.org/packages/release/bioc/html/apeglm.html</a></p><p><span>ashr</span>&nbsp;-&nbsp;<a href="https://github.com/stephens999/ashr" target="_blank">https://github.com/stephens999/ashr</a>,&nbsp;<a href="https://cran.r-project.org/web/packages/ashr/index.html" target="_blank">https://cran.r-project.org/web/packages/ashr/index.html</a></p><p><span>consensusDE</span>&nbsp;-&nbsp;<a href="https://bioconductor.org/packages/release/bioc/html/consensusDE.html" target="_blank">https://bioconductor.org/packages/release/bioc/html/consensusDE.html</a></p><p><span>DESeq2</span>&nbsp;-&nbsp;<a href="https://bioconductor.org/packages/release/bioc/html/DESeq2.html" target="_blank">https://bioconductor.org/packages/release/bioc/html/DESeq2.html</a></p><p><span>edgeR</span>&nbsp;-&nbsp;<a href="https://bioconductor.org/packages/release/bioc/html/edgeR.html" target="_blank">https://bioconductor.org/packages/release/bioc/html/edgeR.html</a></p><p><span>limma</span>&nbsp;-&nbsp;<a href="https://kasperdanielhansen.github.io/genbioconductor/html/limma.html" target="_blank">https://kasperdanielhansen.github.io/genbioconductor/html/limma.html</a>&nbsp;&nbsp;<a href="https://bioconductor.org/packages/release/bioc/html/limma.html" target="_blank">https://bioconductor.org/packages/release/bioc/html/limma.html</a></p><p><span>MetaCycle</span>&nbsp;-&nbsp;<a href="https://cran.r-project.org/web/packages/MetaCycle/index.html" target="_blank">https://cran.r-project.org/web/packages/MetaCycle/index.html</a>,&nbsp;<a href="https://github.com/gangwug/MetaCycle" target="_blank">https://github.com/gangwug/MetaCycle</a></p><p><span>RUVSeq</span>&nbsp;-&nbsp;<a href="https://bioconductor.org/packages/release/bioc/html/RUVSeq.html" target="_blank">https://bioconductor.org/packages/release/bioc/html/RUVSeq.html</a></p><p><span>SARTools</span>&nbsp;-&nbsp;<a href="https://github.com/PF2-pasteur-fr/SARTools" target="_blank">https://github.com/PF2-pasteur-fr/SARTools</a></p><p><span>tximport</span>&nbsp;-&nbsp;<a href="https://github.com/mikelove/tximport" target="_blank">https://github.com/mikelove/tximport</a></p><p>&nbsp;</p>]]></description>
	<dc:creator>Abhi</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44518/virus-bioinformatics-tools</guid>
	<pubDate>Wed, 24 Apr 2024 06:19:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44518/virus-bioinformatics-tools</link>
	<title><![CDATA[Virus Bioinformatics Tools]]></title>
	<description><![CDATA[<p><span>Bioinformatics tools play a crucial role in studying viruses, enabling researchers to analyze their genetic makeup, structure, function, and evolution. Here are some commonly used bioinformatics tools for virus research</span></p>
<p>https://evirusbioinfc.notion.site/18e21bc49827484b8a2f84463cb40b8d?v=92e7eb6703be4720abf17a901bc9a947</p><p>Address of the bookmark: <a href="https://evirusbioinfc.notion.site/18e21bc49827484b8a2f84463cb40b8d?v=92e7eb6703be4720abf17a901bc9a947" rel="nofollow">https://evirusbioinfc.notion.site/18e21bc49827484b8a2f84463cb40b8d?v=92e7eb6703be4720abf17a901bc9a947</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44718/mycology-research-resources-for-bioinformaticians-unlocking-the-fungal-kingdom</guid>
	<pubDate>Fri, 13 Dec 2024 11:21:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44718/mycology-research-resources-for-bioinformaticians-unlocking-the-fungal-kingdom</link>
	<title><![CDATA[Mycology Research Resources for Bioinformaticians: Unlocking the Fungal Kingdom]]></title>
	<description><![CDATA[<p>Mycology, the study of fungi, is a field that bridges ecology, medicine, and biotechnology. With advancements in bioinformatics, researchers now have unprecedented opportunities to explore the fungal kingdom at molecular, genetic, and ecological levels. From understanding pathogenic fungi to harnessing fungal enzymes for industrial applications, the potential is vast.</p><p>To fully leverage these opportunities, bioinformaticians require specialized tools and databases. This blog highlights essential resources for mycology research, focusing on databases, tools, and platforms tailored for fungal biology.</p><h4><strong>1. Fungal Databases</strong></h4><h5><strong>1.1. MycoCosm</strong></h5><p><strong>Website</strong>: <a target="_new">MycoCosm</a><br />Developed by the DOE Joint Genome Institute, MycoCosm is a comprehensive portal for fungal genomics. It offers genomic and transcriptomic data for a wide range of fungi, including saprobes, pathogens, and symbionts.</p><ul>
<li><strong>Key Features</strong>: Genome browsers, comparative genomics tools, and functional annotations.</li>
<li><strong>Best For</strong>: Large-scale studies on fungal evolution and ecology.</li>
</ul><h5><strong>1.2. FungiDB</strong></h5><p><strong>Website</strong>: <a href="https://fungidb.org/" target="_new">FungiDB</a><br />FungiDB is an integrated genomic resource for fungal pathogens and non-pathogens. It provides access to genome sequences, transcriptomic data, and functional annotations.</p><ul>
<li><strong>Key Features</strong>: Advanced search options, BLAST, and pathway analysis tools.</li>
<li><strong>Best For</strong>: Studying fungal pathogenesis and host-pathogen interactions.</li>
</ul><h5><strong>1.3. Index Fungorum</strong></h5><p><strong>Website</strong>: <a href="http://www.indexfungorum.org/" target="_new">Index Fungorum</a><br />This nomenclatural database provides information on the scientific names of fungi. It&rsquo;s an essential resource for taxonomists and researchers focused on fungal biodiversity.</p><ul>
<li><strong>Key Features</strong>: Taxonomic hierarchy and synonymy tracking.</li>
<li><strong>Best For</strong>: Identifying and classifying fungal species.</li>
</ul><h5><strong>1.4. UNITE</strong></h5><p><strong>Website</strong>: <a target="_new">UNITE</a><br />UNITE is a specialized database for fungal ITS (Internal Transcribed Spacer) sequences, often used in fungal identification and phylogenetics.</p><ul>
<li><strong>Key Features</strong>: Curated reference datasets and community annotations.</li>
<li><strong>Best For</strong>: Environmental mycology and microbial ecology studies.</li>
</ul><h4><strong>2. Analytical Tools</strong></h4><h5><strong>2.1. Funannotate</strong></h5><p><strong>Repository</strong>: <a href="https://github.com/nextgenusfs/funannotate" target="_new">GitHub - Funannotate</a><br />Funannotate is a genome annotation tool designed for fungi. It supports tasks like gene prediction, functional annotation, and orthology analysis.</p><ul>
<li><strong>Best For</strong>: Annotating newly sequenced fungal genomes.</li>
</ul><h5><strong>2.2. BUSCO (Benchmarking Universal Single-Copy Orthologs)</strong></h5><p><strong>Website</strong>: <a target="_new">BUSCO</a><br />BUSCO evaluates genome assembly and annotation completeness using orthologs. It includes a fungal-specific dataset.</p><ul>
<li><strong>Best For</strong>: Assessing the quality of fungal genome assemblies.</li>
</ul><h5><strong>2.3. Pathogen-Host Interactions Database (PHI-base)</strong></h5><p><strong>Website</strong>: <a href="http://www.phi-base.org/" target="_new">PHI-base</a><br />PHI-base is a manually curated resource containing information on pathogen-host interactions, including fungal pathogens.</p><ul>
<li><strong>Best For</strong>: Exploring virulence factors and host-pathogen relationships.</li>
</ul><h4><strong>3. Visualization Platforms</strong></h4><h5><strong>3.1. Cytoscape</strong></h5><p><strong>Website</strong>: <a href="https://cytoscape.org/" target="_new">Cytoscape</a><br />A powerful tool for visualizing molecular interaction networks, Cytoscape can be used to study protein-protein interactions, gene networks, and metabolic pathways in fungi.</p><ul>
<li><strong>Best For</strong>: Network biology and functional genomics.</li>
</ul><h5><strong>3.2. iTOL (Interactive Tree of Life)</strong></h5><p><strong>Website</strong>: <a target="_new">iTOL</a><br />iTOL is an interactive tool for visualizing phylogenetic trees.</p><ul>
<li><strong>Best For</strong>: Displaying fungal phylogenies and comparing evolutionary relationships.</li>
</ul><h4><strong>4. Community Resources</strong></h4><h5><strong>4.1. Mycological Society of America (MSA)</strong></h5><p><strong>Website</strong>: <a href="https://msafungi.org/" target="_new">MSA</a><br />The MSA promotes fungal research and provides access to resources, conferences, and publications.</p><ul>
<li><strong>Best For</strong>: Networking with fungal researchers and accessing recent studies.</li>
</ul><h5><strong>4.2. OpenFungi</strong></h5><p><strong>Website</strong>: <a href="https://openfungi.org/" target="_new">OpenFungi</a><br />OpenFungi is an open-source initiative providing fungal genomic and transcriptomic datasets for research and education.</p><ul>
<li><strong>Best For</strong>: Sharing and accessing public fungal datasets.</li>
</ul><h4><strong>5. Genomics Workflows</strong></h4><h5><strong>5.1. Galaxy</strong></h5><p><strong>Website</strong>: <a href="https://usegalaxy.org/" target="_new">Galaxy Project</a><br />Galaxy offers a web-based platform for reproducible bioinformatics workflows, including tools for fungal genome and transcriptome analysis.</p><ul>
<li><strong>Best For</strong>: User-friendly analysis pipelines without requiring coding skills.</li>
</ul><h5><strong>5.2. Snakemake</strong></h5><p><strong>Repository</strong>: <a target="_new">Snakemake</a><br />A flexible pipeline management tool that supports fungal data processing and analysis.</p><ul>
<li><strong>Best For</strong>: Custom workflows for large-scale fungal datasets.</li>
</ul><h4><strong>Conclusion</strong></h4><p>Fungal research is a rapidly growing field with vast implications for medicine, agriculture, and industry. For bioinformaticians, the availability of specialized resources&mdash;databases, tools, and community platforms&mdash;opens doors to innovative discoveries. Whether you are investigating fungal genomics, studying host-pathogen interactions, or exploring fungal biodiversity, the resources outlined above will empower your research journey.</p><p>Dive into these resources and help unravel the mysteries of the fungal kingdom!</p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/35395/comprehensive-list-of-visualization-tools-for-biological-pathways</guid>
	<pubDate>Tue, 30 Jan 2018 06:01:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/35395/comprehensive-list-of-visualization-tools-for-biological-pathways</link>
	<title><![CDATA[Comprehensive list of visualization tools for biological pathways]]></title>
	<description><![CDATA[<p>The study of biological pathways is a key to understand the different processes inside a cell: proteins exert their function not in isolation but in a tightly controlled network of interactions and reactions. Activation of a pathway typically leads to a change of state in the cell. Pathways come in different flavors, depending on their functions in the cell &ndash; the three main types are metabolic pathways, gene regulatory pathways, and signaling pathways. These biological pathways and networks are not only an appropriate approach to visualize molecular reactions. They have also become one leading method in -omics data analysis and visualization.</p><p><img src="https://photos-1.dropbox.com/t/2/AABemz29qAuSTqSzr5mEsQE7JIMxZlU1CBy0E5n0yUVYbA/12/85115969/png/32x32/1/_/1/2/pathway.png/EOfXoUIYrJ8CIAcoBw/01qsT2eykyPvSH-rNpy3cqioDzZPc4i-xULG3BEZvCk?preserve_transparency=1&amp;size=1280x960&amp;size_mode=3" width="800" height="533" alt="image" style="border: 0px;"></p><p>Following are the comprehensive list of visualization tools for biological pathways:</p><p>BiNA</p><p>Drawings of metabolic networks supporting hiding of cofactors and drawing of chemical structures</p><p>http://bina.unipax.info/</p><p>BioTapestry</p><p>Interactive tool for building, visualizing and sharing gene regulatory network models over the web</p><p>http://www.biotapestry.org/</p><p>Caleydo</p><p>Visual analysis framework targeted at biomolecular data. Visualization of interdependencies between multiple datasets</p><p>http://www.caleydo.org/</p><p>CellDesigner</p><p>A modeling tool for biochemical networks</p><p>http://www.celldesigner.org/</p><p>Edinburgh Pathway Editor</p><p>Edit and draw pathway diagrams</p><p>http://epe.sourceforge.net/SourceForge/EPE.html</p><p>GenMAPP</p><p>Visualization of gene expression and other genomic data on maps representing biological pathways and groupings of genes</p><p>http://www.genmapp.org/</p><p>Ingenuity IPA</p><p>Data integration platform and manually annotated pathways</p><p>http://tinyurl.com/IngenuityPath</p><p>JDesigner</p><p>Graphical modeling environment for biochemical reaction networks</p><p>http://jdesigner.sourceforge.net/Site/JDesigner.html</p><p>KaPPA View</p><p>Plant pathways</p><p>http://kpv.kazusa.or.jp/</p><p>KEGG Atlas</p><p>Interactive Kyoto Encyclopedia of Genes and Genomes pathways</p><p>http://www.genome.jp/kegg/</p><p>Omix&nbsp;</p><p>Visualizing multi-omics data in metabolic networks</p><p>https://www.omix-visualization.com</p><p>PathVisio&nbsp;</p><p>Biological pathway analysis software that allows drawing, editing and analysis of biological pathways</p><p>http://www.pathvisio.org/</p><p>VitaPad&nbsp;</p><p>Application to visualize biological pathways and map experimental data to them</p><p>http://tinyurl.com/vitapad/</p><p>Web tools for pathways</p><p>ArrayXPath&nbsp;</p><p>Mapping and visualizing microarray gene-expression data and integrated biological pathway resources using SVG</p><p>http://tinyurl.com/ArrayXPath/</p><p>GEPAT&nbsp;</p><p>Integrated analysis of transcriptome data in genomic, proteomic and metabolic contexts</p><p>http://gepat.sourceforge.net/</p><p>iPath&nbsp;</p><p>Web-based tool for the visualization, analysis and customization of pathway maps</p><p>http://pathways.embl.de/</p><p>Kegg-Based Viewer&nbsp;</p><p>KEGG-based pathway visualization tool for complex high-throughput data</p><p>http://www.g-language.org/data/marray/</p><p>MapMan&nbsp;</p><p>User-driven tool that displays large datasets onto diagrams of metabolic pathways or other processes</p><p>http://mapman.gabipd.org/web/guest/mapman</p><p>MetPA&nbsp;</p><p>Analysis and visualization of metabolomic data within the biological context of metabolic pathways</p><p>http://metpa.metabolomics.ca</p><p>Omics Viewer&nbsp;</p><p>Data mapping on BioCyc pathways (collection of 5500 pathway/genome databases)</p><p>http://www.biocyc.org/</p><p>Pathway Explorer</p><p>Interactive Java drawing tool for the construction of biological pathway diagrams in a visual way and the annotation of the components and interactions between them</p><p>http://genome.tugraz.at/pathwayexplorer/pathwayexplorer_description.shtml</p><p>Pathway projector&nbsp;</p><p>Zoomable pathway browser using KEGG atlas and Google Maps API</p><p>http://www.g-language.org/PathwayProjector/</p><p>PATIKA&nbsp;</p><p>Integrated environment composed of a central database and a visual editor, built around an extensive ontology and an integration framework</p><p>http://www.cs.bilkent.edu.tr/~patikaweb/</p><p>Reactome SkyPainter&nbsp;</p><p>Visualization of over-represented pathways and reactions from gene lists</p><p>http://www.reactome.org/skypainter-2</p><p>WikiPathways</p><p>Wiki-based, open, public platform dedicated to the curation of biological pathways by and for the scientific community</p><p>http://www.wikipathways.org/</p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/35386/list-of-visualization-tools-for-network-biology</guid>
	<pubDate>Mon, 29 Jan 2018 05:12:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/35386/list-of-visualization-tools-for-network-biology</link>
	<title><![CDATA[List of visualization tools for network biology]]></title>
	<description><![CDATA[<p>Network analysis&nbsp;is any structured technique used to mathematically analyze a circuit (a &ldquo;network&rdquo; of interconnected components). The&nbsp;<span>Network analysis provides the ability to quantify associations between individuals, which makes it possible to infer details about the network as a whole at the species and/or population level.&nbsp;</span>Few tools published in BMC are listed here https://bmcbioinformatics.biomedcentral.com/articles/sections/networks-analysis.</p><p><img src="https://www.dropbox.com/pri/get/Public/Link%20to%20network.gif?_subject_uid=85115969&amp;raw=1&amp;revision_id=BBqs9eYx7G_faj5J33ExdjmtF8nXK2xrN5dUBsKyTLZQ9RB_hGM-YFmWZMBzbQZfRvjYzfs65HbQYrHRyoikxsQscSFTn1Nud2QeJ8KGfVI5wv4Kzp6froKOmPZu8ZygfKo&amp;size=1280x960&amp;size_mode=3&amp;w=AABQaErsFIz5ZjVZSxXvKaSVUkY5ob1Yjk0x7dghy0X7zw" alt="image" style="border: 0px; border: 0px;"></p><p>Following are the list of standalone applications for network analysis:</p><p>Arena 3D</p><p>3D visualization of multi-layer networks</p><p>http://www.arena3d.org</p><p>Biana</p><p>Data integration and network management</p><p>http://sbi.imim.es/web/BIANA.php</p><p>BioLayout Express 3D&nbsp;</p><p>2D/3D network visualization</p><p>http://www.biolayout.org/</p><p>BiologicalNetworks&nbsp;</p><p>Efficient integrated multi-level analysis of microarray, sequence, regulatory and other data</p><p>http://www.biologicalnetworks.org</p><p>BioMiner</p><p>Modeling, analyzing and visualizing biochemical pathways and networks</p><p>http://www.zbi.uni-saarland.de/chair/projects/BioMiner</p><p>Cell Illustrator&nbsp;</p><p>Petri nets for modeling and simulating biological networks</p><p>http://www.cellillustrator.com</p><p>COPASI</p><p>Analysis of biochemical networks and their dynamics</p><p>http://www.copasi.org/</p><p>Cytoscape&nbsp;</p><p>Network visualization and analysis. Over 200 plugins [60]</p><p>http://www.cytoscape.org/</p><p>Dizzy</p><p>Chemical kinetics stochastic simulation software</p><p>http://magnet.systemsbiology.net/software/Dizzy/</p><p>DyCoNet</p><p>Gephi plugin that can be used to identify dynamic communities in networks</p><p>https://github.com/juliemkauffman/DyCoNet</p><p>GENeVis&nbsp;</p><p>Network and pathway visualization</p><p>http://tinyurl.com/genevis/</p><p>GEPHI&nbsp;</p><p>Interactive visualization and exploration for any network and complex system, dynamic and hierarchical graph.</p><p>https://gephi.org</p><p>Igraph</p><p>Collection of network analysis tools with the emphasis on efficiency, portability and ease of use</p><p>http://igraph.sourceforge.net</p><p>Medusa</p><p>Semantic and multi-edged simple networks</p><p>https://sites.google.com/site/medusa3visualization/</p><p>NAViGaTOR</p><p>Visualizing and analyzing protein-protein interaction networks</p><p>http://tinyurl.com/navigator1/</p><p>N-Browse</p><p>Interactive graphical browser for biological networks</p><p>http://www.gnetbrowse.org/</p><p>NeAT</p><p>Topological and clustering analysis of networks</p><p>http://rsat.ulb.ac.be/neat/</p><p>Ondex&nbsp;</p><p>Data integration and visualization of large networks</p><p>http://www.ondex.org/</p><p>Osprey</p><p>Visualization and annotation of biological networks</p><p>http://biodata.mshri.on.ca/osprey/servlet/Index</p><p>Pajek&nbsp;</p><p>Analysis and visualization of large networks and social network analysis</p><p>http://vlado.fmf.uni-lj.si/pub/networks/pajek/</p><p>PathwayAssist&nbsp;</p><p>Navigation and analysis of biological pathways, gene regulation networks and protein interaction maps.</p><p>http://www.ariadnegenomics.com/downloads/</p><p>PIVOT&nbsp;</p><p>Layout algorithms for visualizing protein interactions and families</p><p>http://acgt.cs.tau.ac.il/pivot/</p><p>ProCope&nbsp;</p><p>Prediction and evaluation of protein complexes from purification data experiments</p><p>http://www.bio.ifi.lmu.de/Complexes/ProCope/</p><p>ProViz&nbsp;</p><p>Visualization and exploration of interaction networks. Gene Ontology and PSI-MI formats supported</p><p>http://cbi.labri.fr/eng/proviz.htm</p><p>SpectralNET&nbsp;</p><p>Network analysis and visualizations. Scatter plots and dimensionality reduction algorithms</p><p>https://www.broadinstitute.org/software/spectralnet</p><p>Tulip&nbsp;</p><p>Enables the development of algorithms, visual encodings, interaction techniques, data models and domain-specific visualizations</p><p>http://tulip.labri.fr/TulipDrupal/</p><p>VANESA&nbsp;</p><p>Automatic reconstruction and analysis of biological networks and Petri nets based on life-science database information</p><p>http://agbi.techfak.uni-bielefeld.de/vanesa/</p><p>VANTED&nbsp;</p><p>Network reconstruction, data visualization, integration of various data types, network simulation</p><p>http://tinyurl.com/vanted/</p><p>yEd</p><p>Creation of diagrams manually and import external data</p><p>http://tinyurl.com/yEdGraph/</p><p>Web tools for network analysis</p><p>APID&nbsp;</p><p>Unified protein-protein interactions from BIND, BioGRID, DIP, HPRD, IntAct and MINT</p><p>http://bioinfow.dep.usal.es/apid/</p><p>Arcadia&nbsp;</p><p>Translates text-based descriptions of biological networks (SBML files) into standardized diagrams (Systems Biology Graphical Notation Process Description maps)</p><p>http://arcadiapathways.sourceforge.net/</p><p>AVIS&nbsp;</p><p>Viewer for signaling networks</p><p>http://actin.pharm.mssm.edu/AVIS2</p><p>bioPIXIE&nbsp;</p><p>Discovery of biological networks from diverse functional genomic data</p><p>http://pixie.princeton.edu/pixie</p><p>CellPublisher</p><p>Interactive representations of biochemical processes</p><p>http://cellpublisher.gobics.de/</p><p>Graphle</p><p>Distributed network exploration and visualization of interactive large, dense graphs</p><p>http://tinyurl.com/graphle/</p><p>GraphWeb&nbsp;</p><p>Web server for graph-based analysis of biological networks</p><p>http://biit.cs.ut.ee/graphweb/</p><p>Hubba</p><p>Web-based service to explore the essential nodes in a network</p><p>http://hub.iis.sinica.edu.tw/Hubba</p><p>NetworkBLAST&nbsp;</p><p>Analysis of protein interaction networks across species to infer protein complexes that are conserved in evolution</p><p>http://www.cs.tau.ac.il/~bnet/networkblast.htm</p><p>Pathview&nbsp;</p><p>Tool set for pathway-based data integration and visualization</p><p>http://Pathview.r-forge.r-project.org/</p><p>PINA&nbsp;</p><p>Integrated platform for protein interaction network construction, filtering, analysis, visualization and management</p><p>http://cbg.garvan.unsw.edu.au/pina/home.do</p><p>ReMatch&nbsp;</p><p>Web-based tool for integration of user-given stoichiometric metabolic models into a database collected from public data sources</p><p>http://www.cs.helsinki.fi/group/sysfys/software/rematch/</p><p>SNOW&nbsp;</p><p>Gene mapping on a reference or human protein-protein interaction network that SNOW hosts</p><p>http://snow.bioinfo.cipf.es</p><p>STITCH&nbsp;</p><p>Resource to explore known and predicted interactions of chemicals and proteins</p><p>http://stitch.embl.de/</p><p>STRING</p><p>Protein interaction networks and integration of data such as genomic context, high-throughput experiments, conserved coexpression and previous knowledge derived from the literature</p><p>http://string-db.org</p><p>TVNViewer&nbsp;</p><p>An interactive visualization tool for exploring networks that change over time or space</p><p>http://www.sailing.cs.cmu.edu/main/?page_id=545</p><p>tYNA&nbsp;</p><p>System for managing, comparing and mining multiple networks</p><p>http://tyna.gersteinlab.org/tyna/</p><p>VisANT&nbsp;</p><p>Visualization, mining, analysis and modeling of biological networks, metabolic networks and ecosystems</p><p>http://visant.bu.edu/</p><p>&nbsp;</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37915/dna-nucleotide-counter</guid>
	<pubDate>Fri, 12 Oct 2018 04:37:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37915/dna-nucleotide-counter</link>
	<title><![CDATA[DNA Nucleotide Counter]]></title>
	<description><![CDATA[<p style="margin: 2px 5px 4px 6px; color: #000011; font-size: 12px; font-style: normal; font-weight: 400; text-align: justify;">DNA Nucleotide Counter is delivered in a DNA Baser package together with other free molecular biology tools.<span>&nbsp;</span><a href="http://www.dnabaser.com/download/biology-tools-package-download-count.html">Download</a><span>&nbsp;</span>the package and double click it. The programs inside the package will be extracted to the destination folder (specified by you). Go to the destination folder&nbsp;and double click the program you want to use.</p>
<p style="margin: 2px 5px 4px 6px; color: #000011; font-size: 12px; font-style: normal; font-weight: 400; text-align: justify;">It<span>&nbsp;</span><a href="http://www.dnabaser.com/download/install-anywhere.html">installs in any computer</a><span>&nbsp;</span>even if you don't have administrator rights!</p><p>Address of the bookmark: <a href="http://www.dnabaser.com/download/DNA-Counter/index.html" rel="nofollow">http://www.dnabaser.com/download/DNA-Counter/index.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

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