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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/41442?offset=190</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44896/jaeger-an-accurate-and-fast-deep-learning-tool-to-detect-bacteriophage-sequences</guid>
	<pubDate>Sun, 31 Aug 2025 06:30:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44896/jaeger-an-accurate-and-fast-deep-learning-tool-to-detect-bacteriophage-sequences</link>
	<title><![CDATA[Jaeger : an accurate and fast deep-learning tool to detect bacteriophage sequences]]></title>
	<description><![CDATA[<p><span>Jaeger is a tool that utilizes homology-free machine learning to identify phage genome sequences that are hidden within metagenomes. It is capable of detecting both phages and prophages within metagenomic assemblies.</span></p><p>Address of the bookmark: <a href="https://github.com/MGXlab/Jaeger" rel="nofollow">https://github.com/MGXlab/Jaeger</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29487/shinyheatmap</guid>
	<pubDate>Fri, 21 Oct 2016 05:12:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29487/shinyheatmap</link>
	<title><![CDATA[Shinyheatmap]]></title>
	<description><![CDATA[<p><span>Background: Transcriptomics, metabolomics, metagenomics, and other various next-generation sequencing (-omics) fields are known for their production of large datasets. Visualizing such big data has posed technical challenges in biology, both in terms of available computational resources as well as programming acumen. Since heatmaps are used to depict high-dimensional numerical data as a colored grid of cells, efficiency and speed have often proven to be critical considerations in the process of successfully converting data into graphics. For example, rendering interactive heatmaps from large input datasets (e.g., 100k+ rows) has been computationally infeasible on both desktop computers and web browsers. In addition to memory requirements, programming skills and knowledge have frequently been barriers-to-entry for creating highly customizable heatmaps. Results: We propose shinyheatmap: an advanced user-friendly heatmap software suite capable of efficiently creating highly customizable static and interactive biological heatmaps in a web browser. shinyheatmap is a low memory footprint program, making it particularly well-suited for the interactive visualization of extremely large datasets that cannot typically be computed in-memory due to size restrictions. Conclusions: shinyheatmap is hosted online as a freely available web server with an intuitive graphical user interface: http://shinyheatmap.com. The methods are implemented in R, and are available as part of the shinyheatmap project at: https://github.com/Bohdan-Khomtchouk/shinyheatmap.</span></p>
<p><span>More at&nbsp;http://biorxiv.org/content/early/2016/09/21/076463&nbsp;</span></p><p>Address of the bookmark: <a href="http://shinyheatmap.com/" rel="nofollow">http://shinyheatmap.com/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37460/revigo-reduced-visualize-gene-ontology</guid>
	<pubDate>Tue, 31 Jul 2018 05:28:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37460/revigo-reduced-visualize-gene-ontology</link>
	<title><![CDATA[REVIGO: Reduced Visualize gene ontology]]></title>
	<description><![CDATA[<div>REViGO can take long lists of Gene Ontology terms and summarize them by removing redundant GO terms. The remaining terms can be visualized in semantic similarity-based scatterplots, interactive graphs, or tag clouds.&nbsp;<a href="http://dx.doi.org/10.1371/journal.pone.0021800">More about REViGO...</a>&nbsp;|&nbsp;<a href="http://revigo.irb.hr/about_hr.jsp"><img src="http://revigo.irb.hr/gfx/croatian-wCrown.png" alt="In Croatian" title="" width="12" height="15" style="border: 0px;"></a></div>
<div>Please enter a list of Gene Ontology IDs below, each on its own line. The GO IDs may be followed by p-values or another quantity which describes the GO term in a way meaningful to you.&nbsp;<img src="http://revigo.irb.hr/gfx/qmark.png" alt="For instance, you may provide a p-value          (statistical significance), a fold change, enrichment, or some          directly measured quantity such as average signal intensity from          microarrays, ion count from mass spec, or read count from RNA-seq.          You may also provide more than one value per line, although only the          first value will be used in GO term selection/clustering." title="" width="16" height="15" style="border: 0px;"></div><p>Address of the bookmark: <a href="http://revigo.irb.hr/" rel="nofollow">http://revigo.irb.hr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40583/trelliscope-flexibly-visualize-large-complex-data-in-great-detail-from-within-the-r-statistical-programming-environment</guid>
	<pubDate>Tue, 21 Jan 2020 04:22:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40583/trelliscope-flexibly-visualize-large-complex-data-in-great-detail-from-within-the-r-statistical-programming-environment</link>
	<title><![CDATA[Trelliscope: flexibly visualize large, complex data in great detail from within the R statistical programming environment.]]></title>
	<description><![CDATA[<p>Trelliscope provides a way to flexibly visualize large, complex data in great detail from within the R statistical programming environment. Trelliscope is a component in the<span>&nbsp;</span><a href="http://deltarho.org/docs-trelliscope/deltarho.org">DeltaRho</a><span>&nbsp;</span>environment.</p>
<p>For those familiar with<span>&nbsp;</span><a href="http://cm.bell-labs.com/cm/ms/departments/sia/project/trellis/">Trellis Display</a>,<span>&nbsp;</span><a href="http://docs.ggplot2.org/0.9.3.1/facet_wrap.html">faceting in ggplot</a>, or the notion of<span>&nbsp;</span><a href="http://en.wikipedia.org/wiki/Small_multiple">small multiples</a>, Trelliscope provides a scalable way to break a set of data into pieces, apply a plot method to each piece, and then arrange those plots in a grid and interactively sort, filter, and query panels of the display based on metrics of interest. With Trelliscope, we are able to create multipanel displays on data with a very large number of subsets and view them in an interactive and meaningful way.</p><p>Address of the bookmark: <a href="http://deltarho.org/docs-trelliscope/#introduction" rel="nofollow">http://deltarho.org/docs-trelliscope/#introduction</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44307/genomenotebook</guid>
	<pubDate>Thu, 20 Apr 2023 13:19:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44307/genomenotebook</link>
	<title><![CDATA[genomenotebook]]></title>
	<description><![CDATA[<p><a href="https://dbikard.github.io/genomenotebook/">https://dbikard.github.io/genomenotebook/</a></p>
<h2>Install<a href="https://dbikard.github.io/genomenotebook/#install"></a></h2>
<pre><code>pip install genomenotebook</code></pre>
<h2>How to use<a href="https://dbikard.github.io/genomenotebook/#how-to-use"></a></h2>
<p>Create a simple genome browser with a search bar. The sequence appears when zooming in.</p>
<div>
<div id="cb2">
<pre><code><span><a href="https://dbikard.github.io/genomenotebook/#cb2-1"></a><span>import</span> genomenotebook <span>as</span> gn</span>
<span><a href="https://dbikard.github.io/genomenotebook/#cb2-2"></a></span>
<span><a href="https://dbikard.github.io/genomenotebook/#cb2-3"></a>g<span>=</span>gn.GenomeBrowser(genome_path, gff_path, init_pos<span>=</span><span>10000</span>)</span>
<span><a href="https://dbikard.github.io/genomenotebook/#cb2-4"></a>g.show()</span></code><button title="Copy to Clipboard"></button></pre>
</div>
</div>
<p>Tracks can be added to visualize your favorite genomics data. See&nbsp;<code>Examples</code>&nbsp;for more !!!!</p><p>Address of the bookmark: <a href="https://dbikard.github.io/genomenotebook/" rel="nofollow">https://dbikard.github.io/genomenotebook/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35108/mobyle-a-new-full-web-bioinformatics-framework</guid>
	<pubDate>Sun, 07 Jan 2018 19:33:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35108/mobyle-a-new-full-web-bioinformatics-framework</link>
	<title><![CDATA[Mobyle: a new full web bioinformatics framework]]></title>
	<description><![CDATA[<p><span>Mobyle, to provide a flexible and usable Web environment for defining and running bioinformatics analyses. It embeds simple yet powerful data management features that allow the user to reproduce analyses and to combine tools using a hierarchical typing system. Mobyle offers invocation of services distributed over remote Mobyle servers, thus enabling a federated network of curated bioinformatics portals without the user having to learn complex concepts or to install sophisticated software.</span></p><p>Address of the bookmark: <a href="https://academic.oup.com/bioinformatics/article/25/22/3005/179064" rel="nofollow">https://academic.oup.com/bioinformatics/article/25/22/3005/179064</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37965/kobas-a-web-server-for-geneprotein-functional-annotation-and-functional-gene-set-enrichment</guid>
	<pubDate>Fri, 19 Oct 2018 09:36:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37965/kobas-a-web-server-for-geneprotein-functional-annotation-and-functional-gene-set-enrichment</link>
	<title><![CDATA[KOBAS: a web server for gene/protein functional annotation and functional gene set enrichment]]></title>
	<description><![CDATA[<p><span>KOBAS 3.0 is a web server for gene/protein functional annotation (</span><a href="http://kobas.cbi.pku.edu.cn/annotate.php">Annotate</a><span>&nbsp;module) and functional gene set enrichment(Enrichment module). For Annotate module, it accepts gene list as input, including IDs or sequences, and generates annotations for each gene based on multiple databases about pathways, diseases, and Gene Ontology. For Enrichment module, it can accept either gene list or gene expression data as input, and generates enriched gene sets, corresponding name, p-value or a probability of enrichment and enrichment score based on results of multiple methods.</span></p><p>Address of the bookmark: <a href="http://kobas.cbi.pku.edu.cn/" rel="nofollow">http://kobas.cbi.pku.edu.cn/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40221/dash-a-web-application-framework-that-provides-pure-python-abstraction-around-html-css-and-javascript</guid>
	<pubDate>Tue, 05 Nov 2019 06:39:48 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40221/dash-a-web-application-framework-that-provides-pure-python-abstraction-around-html-css-and-javascript</link>
	<title><![CDATA[Dash: a web application framework that provides pure Python abstraction around HTML, CSS, and JavaScript.]]></title>
	<description><![CDATA[<p style="margin-top: 0px; margin-bottom: 0.75rem;">Dash is a web application framework that provides pure Python abstraction around HTML, CSS, and JavaScript.</p>
<p style="margin-top: 0px; margin-bottom: 0.75rem;">Dash Bio is a suite of bioinformatics components that make it simpler to analyze and visualize bioinformatics data and interact with them in a Dash application.</p>
<p style="margin-top: 0px; margin-bottom: 0.75rem;">The source can be found on GitHub at<span>&nbsp;</span><a href="https://github.com/plotly/dash-bio">plotly/dash-bio</a>.</p>
<p style="margin-top: 0px; margin-bottom: 0.75rem;">These docs are using Dash Bio version 0.1.4.</p><p>Address of the bookmark: <a href="https://dash.plot.ly/dash-bio" rel="nofollow">https://dash.plot.ly/dash-bio</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41863/ppai-a-web-server-for-predicting-protein-aptamer-interactions</guid>
	<pubDate>Fri, 12 Jun 2020 07:26:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41863/ppai-a-web-server-for-predicting-protein-aptamer-interactions</link>
	<title><![CDATA[PPAI: a web server for predicting protein-aptamer interactions]]></title>
	<description><![CDATA[<p><span>PPAI can query aptamers and proteins, predict aptamers and predict protein-aptamer interactions in batch mode precisely and efficiently, which would be a novel bioinformatics tool for the research of protein-aptamer interactions. PPAI web-server is freely available at&nbsp;</span><a href="http://39.96.85.9/PPAI">http://39.96.85.9/PPAI</a></p><p>Address of the bookmark: <a href="http://39.96.85.9/PPAI/" rel="nofollow">http://39.96.85.9/PPAI/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33983/web-apollo-a-web-based-genomic-annotation-editing-platform</guid>
	<pubDate>Fri, 28 Jul 2017 04:48:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33983/web-apollo-a-web-based-genomic-annotation-editing-platform</link>
	<title><![CDATA[Web Apollo: a web-based genomic annotation editing platform]]></title>
	<description><![CDATA[<p><span>Web Apollo is the first instantaneous, collaborative genomic annotation editor available on the web. One of the natural consequences following from current advances in sequencing technology is that there are more and more researchers sequencing new genomes. These researchers require tools to describe the functional features of their newly sequenced genomes. With Web Apollo researchers can use any of the common browsers (for example, Chrome or Firefox) to jointly analyze and precisely describe the features of a genome in real time, whether they are in the same room or working from opposite sides of the world.</span></p><p>Address of the bookmark: <a href="http://genomearchitect.github.io/" rel="nofollow">http://genomearchitect.github.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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