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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/38593?offset=130</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37259/epiviz-an-interactive-visualization-tool-for-functional-genomics-data</guid>
	<pubDate>Mon, 09 Jul 2018 05:27:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37259/epiviz-an-interactive-visualization-tool-for-functional-genomics-data</link>
	<title><![CDATA[Epiviz: an interactive visualization tool for functional genomics data.]]></title>
	<description><![CDATA[<p><span>Epiviz is an interactive visualization tool for functional genomics data. It supports genome navigation like other genome browsers, but allows multiple visualizations of data within genomic regions using scatterplots, heatmaps and other user-supplied visualizations. It also includes data from the&nbsp;</span><a href="http://barcode.luhs.org/" target="_blank">Gene Expression Barcode project</a><span>&nbsp;for transcriptome visualization. It has a flexible plugin framework so users can add</span><a href="http://d3js.org/" target="_blank">d3</a><span>&nbsp;visualizations. You can see a video tour&nbsp;</span><a href="http://youtu.be/099c4wUxozA" target="_blank">here</a><span>.</span></p>
<p><span>https://bioconductor.org/packages/release/bioc/html/epivizr.html</span></p>
<p><span>https://github.com/epiviz</span></p>
<p><span>https://github.com/epiviz/epiviz</span></p><p>Address of the bookmark: <a href="https://epiviz.github.io/" rel="nofollow">https://epiviz.github.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38598/zenbu-a-collaborative-omics-data-integration-and-interactive-visualization-system</guid>
	<pubDate>Fri, 04 Jan 2019 13:35:26 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38598/zenbu-a-collaborative-omics-data-integration-and-interactive-visualization-system</link>
	<title><![CDATA[ZENBU: a collaborative, omics data integration and interactive visualization system]]></title>
	<description><![CDATA[<p><span>ZENBU</span><span>&nbsp;</span><span>is a data integration, data analysis, and visualization system enhanced for RNAseq, ChipSeq, CAGE and other types of next-generation-sequence-tag (NGS) based data. ZENBU allows for novel data exploration through "on-demand" data processing and interactive linked-visualizations and is able to make many-views from the same primary sequence alignment data which users can uploaded from BAM, BED, GFF and tab-text files.&nbsp;<br>Please check our&nbsp;<a href="http://fantom.gsc.riken.jp/zenbu/wiki">documentation wiki</a>&nbsp;for details on how to use the system, or check out some of the views above.</span></p><p>Address of the bookmark: <a href="http://fantom.gsc.riken.jp/zenbu/" rel="nofollow">http://fantom.gsc.riken.jp/zenbu/</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39200/omtools-a-software-package-for-visualizing-and-processing-optical-mapping-data</guid>
	<pubDate>Fri, 29 Mar 2019 01:21:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39200/omtools-a-software-package-for-visualizing-and-processing-optical-mapping-data</link>
	<title><![CDATA[OMTools: a software package for visualizing and processing optical mapping data]]></title>
	<description><![CDATA[<p><span>OMTools, an efficient and intuitive data processing and visualization suite to handle and explore large-scale optical mapping profiles. OMTools includes modules for visualization (OMView), data processing and simulation. These modules together form an accessible and convenient pipeline for optical mapping analyses.</span></p>
<p><span><a href="https://github.com/TF-Chan-Lab/OMTools">https://github.com/TF-Chan-Lab/OMTools</a></span></p><p>Address of the bookmark: <a href="https://github.com/TF-Chan-Lab/OMTools" rel="nofollow">https://github.com/TF-Chan-Lab/OMTools</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41209/juicebox-visualization-and-analysis-software-for-hi-c-data</guid>
	<pubDate>Fri, 21 Feb 2020 00:33:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41209/juicebox-visualization-and-analysis-software-for-hi-c-data</link>
	<title><![CDATA[Juicebox: Visualization and analysis software for Hi-C data]]></title>
	<description><![CDATA[<p>Juicebox is visualization software for Hi-C data. This distribution includes the source code for Juicebox,&nbsp;<a href="https://github.com/theaidenlab/juicer/wiki/Download">Juicer Tools</a>, and&nbsp;<a href="https://aidenlab.org/assembly/">Assembly Tools</a>.&nbsp;<a href="https://github.com/theaidenlab/juicebox/wiki/Download">Download Juicebox here</a>, or use&nbsp;<a href="https://aidenlab.org/juicebox">Juicebox on the web</a>. Detailed documentation is available&nbsp;<a href="https://github.com/theaidenlab/juicebox/wiki">on the wiki</a>. Instructions below pertain primarily to usage of command line tools and the Juicebox jar files.</p>
<p>Juicebox can now be used to visualize and interactively (re)assemble genomes. Check out the Juicebox Assembly Tools Module website&nbsp;<a href="https://aidenlab.org/assembly">https://aidenlab.org/assembly</a>&nbsp;for more details on how to use Juicebox for assembly.</p>
<p>GUI at&nbsp;<a href="https://aidenlab.org/juicebox/">https://aidenlab.org/juicebox/</a></p><p>Address of the bookmark: <a href="https://github.com/aidenlab/Juicebox" rel="nofollow">https://github.com/aidenlab/Juicebox</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42362/magic-a-tool-for-predicting-transcription-factors-and-cofactors-driving-gene-sets-using-encode-data</guid>
	<pubDate>Thu, 26 Nov 2020 11:05:04 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42362/magic-a-tool-for-predicting-transcription-factors-and-cofactors-driving-gene-sets-using-encode-data</link>
	<title><![CDATA[MAGIC: A tool for predicting transcription factors and cofactors driving gene sets using ENCODE data]]></title>
	<description><![CDATA[<p><span>The algorithm presented herein,&nbsp;</span><strong>M</strong><span>ining&nbsp;</span><strong>A</strong><span>lgorithm for&nbsp;</span><strong>G</strong><span>enet</span><strong>I</strong><span>c&nbsp;</span><strong>C</strong><span>ontrollers (MAGIC), uses ENCODE ChIP-seq data to look for statistical enrichment of TFs and cofactors in gene bodies and flanking regions in gene lists without an&nbsp;</span><em>a priori</em><span>&nbsp;binary classification of genes as targets or non-targets. When compared to other TF mining resources, MAGIC displayed favourable performance in predicting TFs and cofactors that drive gene changes in 4 settings: </span></p>
<p><span>1) A cell line expressing or lacking single TF, </span></p>
<p><span>2) Breast tumors divided along PAM50 designations </span></p>
<p><span>3) Whole brain samples from WT mice or mice lacking a single TF in a particular neuronal subtype </span></p>
<p><span>4) Single cell RNAseq analysis of neurons divided by Immediate Early Gene expression levels. </span></p>
<p><span>In summary, MAGIC is a standalone application that produces meaningful predictions of TFs and cofactors in transcriptomic experiments.</span></p>
<p><span>More at&nbsp;https://uwmadison.app.box.com/s/8j90e5h2rjrsz3bacaxnq8kor2o64vyg</span></p><p>Address of the bookmark: <a href="https://github.com/asroopra/MAGIC" rel="nofollow">https://github.com/asroopra/MAGIC</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43090/loretta-a-user-friendly-tool-for-assembling-viral-genomes-from-pacbio-sequence-data</guid>
	<pubDate>Wed, 23 Jun 2021 07:54:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43090/loretta-a-user-friendly-tool-for-assembling-viral-genomes-from-pacbio-sequence-data</link>
	<title><![CDATA[LoReTTA, a user-friendly tool for assembling viral genomes from PacBio sequence data]]></title>
	<description><![CDATA[<p>LoReTTA (Long Read Template-Targeted Assembler), a tool designed for performing <em>de novo</em> assembly of long reads generated from viral genomes on the PacBio platform. LoReTTA exploits a reference genome to guide the assembly process, an approach that has been successful with short reads.</p>
<p>https://academic.oup.com/ve/article/7/1/veab042/6248116</p><p>Address of the bookmark: <a href="https://academic.oup.com/ve/article/7/1/veab042/6248116" rel="nofollow">https://academic.oup.com/ve/article/7/1/veab042/6248116</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44313/orthovenn3-an-integrated-platform-for-exploring-and-visualizing-orthologous-data-across-genomes</guid>
	<pubDate>Tue, 02 May 2023 00:48:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44313/orthovenn3-an-integrated-platform-for-exploring-and-visualizing-orthologous-data-across-genomes</link>
	<title><![CDATA[OrthoVenn3: an integrated platform for exploring and visualizing orthologous data across genomes]]></title>
	<description><![CDATA[<p><span>OrthoVenn3 is a powerful tool for comparative genomics analysis, used as a web server for full genome comparisons, annotation, and evolutionary analysis of orthologous clusters across multiple species. It has already been used by thousands of users from over 60 countries.</span></p><p>Address of the bookmark: <a href="https://orthovenn3.bioinfotoolkits.net/" rel="nofollow">https://orthovenn3.bioinfotoolkits.net/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44581/biokit-a-set-of-tools-dedicated-to-bioinformatics-data-visualisation</guid>
	<pubDate>Tue, 18 Jun 2024 02:04:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44581/biokit-a-set-of-tools-dedicated-to-bioinformatics-data-visualisation</link>
	<title><![CDATA[BioKit: a set of tools dedicated to bioinformatics, data visualisation]]></title>
	<description><![CDATA[<p><span>BioKit is a set of tools dedicated to bioinformatics, data visualisation (</span><a href="https://biokit.readthedocs.io/en/latest/references.html#module-biokit.viz" title="biokit.viz"><code><span>biokit.viz</span></code></a><span>), access to online biological data (e.g. UniProt, NCBI thanks to bioservices). It also contains more advanced tools related to data analysis (e.g.,&nbsp;</span><a href="https://biokit.readthedocs.io/en/latest/references.html#module-biokit.stats" title="biokit.stats"><code><span>biokit.stats</span></code></a><span>). Since R is quite common in bioinformatics, we also provide a convenient module to run R inside your Python scripts or shell (:mod:biokit.rtools module).</span></p><p>Address of the bookmark: <a href="https://biokit.readthedocs.io/en/latest/index.html" rel="nofollow">https://biokit.readthedocs.io/en/latest/index.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44873/bakrep-denglish-blend-of-bakterien-repository-simplifies-access-to-this-data</guid>
	<pubDate>Wed, 13 Aug 2025 02:31:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44873/bakrep-denglish-blend-of-bakterien-repository-simplifies-access-to-this-data</link>
	<title><![CDATA[BakRep (Denglish blend of Bakterien &amp; Repository) simplifies access to this data]]></title>
	<description><![CDATA[<p>2,438,386 bacterial genomes at your fingertips consistently processed &amp; characterized, enriched with metadata, accessible via a flexible search engine.</p>
<p>BakRep (Denglish blend of Bakterien &amp; Repository) simplifies access to this data. It integrates enriched genomic information with metadata accessible via a flexible search-engine.</p>
<h1>Key features</h1>
<ul>
<li>Assembly statistics: ensure data quality with genome-based key metrics</li>
<li>Taxonomic classification: robust, purely genome-based classifications (<a href="https://gtdb.ecogenomic.org/" target="_blank">GTDB</a>)</li>
<li><a href="https://pubmlst.org/">MLST</a>: subtyping for deeper insights into genetic variation</li>
<li>Annotation: comprehensive &amp; taxonomy-independent (<a href="https://bakta.computational.bio/" target="_blank">Bakta</a>)</li>
<li>Metadata: full original submission records</li>
</ul>
<div>&nbsp;</div><p>Address of the bookmark: <a href="https://bakrep.computational.bio/" rel="nofollow">https://bakrep.computational.bio/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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