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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/39843?</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34501/dnapipete-de-novo-assembly-annotation-pipeline-for-transposable-elements</guid>
	<pubDate>Sat, 02 Dec 2017 18:25:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34501/dnapipete-de-novo-assembly-annotation-pipeline-for-transposable-elements</link>
	<title><![CDATA[dnaPipeTE: de-novo assembly &amp; annotation Pipeline for Transposable Elements]]></title>
	<description><![CDATA[<p>dnaPipeTE (for de-novo assembly &amp; annotation Pipeline for Transposable Elements), is a pipeline designed to find, annotate and quantify Transposable Elements in small samples of NGS datasets. It is very useful to quantify the proportion of TEs in newly sequenced genomes since it does not require genome assembly and works on small datasets (&lt; 1X).</p>
<ul>
<li>
<p>dnaPipeTE is developped by Cl&eacute;ment Goubert, Laurent Modolo and the TREEP team of the LBBE:&nbsp;<a href="http://lbbe.univ-lyon1.fr/-Equipe-Elements-transposables-.html?lang=en">http://lbbe.univ-lyon1.fr/-Equipe-Elements-transposables-.html?lang=en</a></p>
</li>
<li>
<p>You can find the original publication in GBE here:&nbsp;<a href="https://academic.oup.com/gbe/article/7/4/1192/533768">https://academic.oup.com/gbe/article/7/4/1192/533768</a></p>
</li>
</ul>
<p><a href="https://github.com/clemgoub/dnaPipeTE/blob/dev/dnaPipefront.png" target="_blank"><img src="https://github.com/clemgoub/dnaPipeTE/raw/dev/dnaPipefront.png" alt="Front" style="border: 0px;"></a><em>output examples of quantification and TE landscape (relative age) produced by dnaPipeTE</em></p>
<p><em>&nbsp;</em></p><p>Address of the bookmark: <a href="https://github.com/clemgoub/dnaPipeTE" rel="nofollow">https://github.com/clemgoub/dnaPipeTE</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43398/waafle-a-workflow-to-annotate-assemblies-and-find-lgt-events</guid>
	<pubDate>Thu, 23 Sep 2021 14:31:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43398/waafle-a-workflow-to-annotate-assemblies-and-find-lgt-events</link>
	<title><![CDATA[WAAFLE: a Workflow to Annotate Assemblies and Find LGT Events.]]></title>
	<description><![CDATA[<p><span>Lateral gene transfer (LGT) is an important mechanism for genome diversification in microbial communities, including the human microbiome. While methods exist to identify LGTs from sequenced isolate genomes, identifying LGTs from community metagenomes remains an open problem. To address this, we developed&nbsp;</span><span>WAAFLE</span><span>: a&nbsp;</span><span>W</span><span>orkflow to&nbsp;</span><span>A</span><span>nnotate&nbsp;</span><span>A</span><span>ssemblies and&nbsp;</span><span>F</span><span>ind&nbsp;</span><span>L</span><span>GT&nbsp;</span><span>E</span><span>vents.</span></p><p>Address of the bookmark: <a href="http://huttenhower.sph.harvard.edu/waafle" rel="nofollow">http://huttenhower.sph.harvard.edu/waafle</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/43293/josefa-gonzalez-lab</guid>
  <pubDate>Thu, 19 Aug 2021 08:52:56 -0500</pubDate>
  <link></link>
  <title><![CDATA[Josefa González Lab]]></title>
  <description><![CDATA[
<p>Lab focus on understanding how organisms adapt to their environments. They combine omics approaches with detailed molecular and phenotypic analyses to get a comprehensive picture of adaptation. Our aim at being internationally recognized as a leading lab in the field of environmental adaptation.<br />Lab share our passion for science with the general public by leading outreach projects aimed at increasing science awareness.</p>

<p>More at https://www.biologiaevolutiva.org/gonzalez_lab/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44902/hite-a-fast-and-accurate-dynamic-boundary-adjustment-approach-for-full-length-transposable-elements-detection-and-annotation-in-genome-assemblies</guid>
	<pubDate>Sat, 20 Sep 2025 09:34:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44902/hite-a-fast-and-accurate-dynamic-boundary-adjustment-approach-for-full-length-transposable-elements-detection-and-annotation-in-genome-assemblies</link>
	<title><![CDATA[HiTE: a fast and accurate dynamic boundary adjustment approach for full-length Transposable Elements detection and annotation in Genome Assemblies]]></title>
	<description><![CDATA[<p dir="auto"><code>HiTE</code>&nbsp;is a Python software that uses a dynamic boundary adjustment approach to detect and annotate full-length Transposable Elements in Genome Assemblies. In comparison to other tools, HiTE demonstrates superior performance in detecting a greater number of full-length TEs.</p>
<div dir="auto">
<h2 dir="auto">panHiTE</h2>
<a href="https://github.com/CSU-KangHu/HiTE#panhite"></a></div>
<p dir="auto">We have developed panHiTE, a comprehensive and accurate pipeline for TE detection in large-scale population genomes. It has been successfully applied to hundreds of plant population genomes, demonstrating its effectiveness and scalability.</p>
<p dir="auto">For detailed instructions, please refer to the&nbsp;<a href="https://github.com/CSU-KangHu/HiTE/wiki/panHiTE-tutorial">panHiTE tutorial</a>.</p><p>Address of the bookmark: <a href="https://github.com/CSU-KangHu/HiTE" rel="nofollow">https://github.com/CSU-KangHu/HiTE</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28844/teannot</guid>
	<pubDate>Thu, 18 Aug 2016 10:02:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28844/teannot</link>
	<title><![CDATA[TEannot]]></title>
	<description><![CDATA[<p>We advise to run first the TEdenovo pipeline but it is not compulsory. We suppose you begin by running the TEannot pipeline on the example provided in the directory "db/" rather than directly on your own genomic sequences. Thus, from now on, the project name is "DmelChr4".</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://urgi.versailles.inra.fr/Tools/REPET/TEannot-tuto" rel="nofollow">https://urgi.versailles.inra.fr/Tools/REPET/TEannot-tuto</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35294/httdb-horizontally-transferred-transposable-elements-database</guid>
	<pubDate>Tue, 23 Jan 2018 12:07:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35294/httdb-horizontally-transferred-transposable-elements-database</link>
	<title><![CDATA[HTTDB - Horizontally transferred transposable elements database]]></title>
	<description><![CDATA[<p><span>Transposons or Transposable elements (TEs) are "mobile genes" capable of mobilization from one genomic location to another through non-homologous recombination. As this movement is mediated by its own proteins and does not contribute to the survival of the host that it inhabits, they are known as selfish genomic parasites. Despite their capacity for transposition inside genomes, they can frequently transpose the species boundaries and consequently migrate from one species to another. Such phenomenon is called Horizontal Transposons Transfer. HTT was first discovered by Daniels et al. (1984) when analysing a&nbsp;</span><em>P</em><span>&nbsp;element that was transferred from&nbsp;</span><em>Drosophila willistoni</em><span>&nbsp;to&nbsp;</span><em>D. melanogaster</em><span>. Since then, many more cases have been documented in the literature. Moreover, in the last years, such discoveries have been boosted by the unprecedented amount of new genomes available. Despite the recognition of HTT as a common phenomenon in recent years, it is still difficult to draw major conclusions about HTT patterns, such as where in the tree of life these cases are more frequently found. This is mainly due to the historical bias and lack of studies in many taxa. To date, there has been no easy way to visualise each TE or host species, and should be further analysed in order to provide a more comprehensive view of such phenomena. Based on these concerns, we developed the HTT database to keep an updated repository of HTT events in all eukaryotes, allowing not only TE specialists to add new events and search the database, but also non-specialists. Moreover, we expanded the database to include Horizontal-Virus Transfer also known as endogenization events which is characterized by the stable integration a viral genomic fragment into the host genome.</span></p>
<p><span>https://www.ncbi.nlm.nih.gov/pubmed/29315358</span></p><p>Address of the bookmark: <a href="http://lpa.saogabriel.unipampa.edu.br:8080/httdatabase/" rel="nofollow">http://lpa.saogabriel.unipampa.edu.br:8080/httdatabase/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38666/mcat-motif-combining-and-association-tool</guid>
	<pubDate>Sun, 13 Jan 2019 06:27:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38666/mcat-motif-combining-and-association-tool</link>
	<title><![CDATA[MCAT: Motif Combining and Association Tool]]></title>
	<description><![CDATA[<p>This is a pipeline for finding motifs in fasta files.<br>It can be run from the command line as follows:</p>
<p>usage: orange_pipeline_refine.py [-h] [-w W] [--nmotifs NMOTIFS] [--iter ITER] [-c C]<br>[-s S] [-d] [-ff] [-v V]<br>positive_seq negative_seq</p>
<p>positional arguments:<br>positive_seq the fasta file for the positive sequences<br>negative_seq the fasta file for the negative sequences</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/yanshen43/MCAT" rel="nofollow">https://github.com/yanshen43/MCAT</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/42023/encode3-a-collection-of-research-articles-and-related-content-describing-the-encyclopedia-of-dna-elements-its-datasets-and-tools</guid>
	<pubDate>Sat, 08 Aug 2020 08:25:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/42023/encode3-a-collection-of-research-articles-and-related-content-describing-the-encyclopedia-of-dna-elements-its-datasets-and-tools</link>
	<title><![CDATA[ENCODE3: A collection of research articles and related content describing the Encyclopedia of DNA Elements, its datasets and tools.]]></title>
	<description><![CDATA[<p>How cells, tissues and organisms interpret the information encoded in the genome has vital implications for our understanding of development, health and disease. Launched in 2003, the ENCyclopedia Of DNA Elements (ENCODE) project has the aim of mapping the functional elements in the human genome (later expanded to include model organisms).</p><p>During the first phase of ENCODE, published in 2007, microarray-based technologies were used to detect regions associated with transcription factors, certain histone modifications and open chromatin within a pre-specified 1% of the human genome.</p><p>ENCODE&rsquo;s second phase saw a switch to sequencing-based technologies, the addition of new assay types and the analysis of functional elements genome-wide, described in a collection of research articles in 2012.</p><p><span>The&nbsp;</span><a href="https://www.nature.com/articles/s41586-020-2493-4">Encyclopedia paper of ENCODE 3</a><span>, published in&nbsp;</span><em>Nature</em><span>, gives an overview of the various assays that were performed in human and mouse cell lines and tissues and describes a Registry of human and mouse candidate&nbsp;</span><em>cis</em><span>-regulatory elements (cCREs).</span></p><p>More at&nbsp;<a href="https://www.nature.com/immersive/d42859-020-00027-2/index.html">https://www.nature.com/immersive/d42859-020-00027-2/index.html</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/2839/look-up-a-biological-numbers</guid>
	<pubDate>Fri, 23 Aug 2013 03:27:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/2839/look-up-a-biological-numbers</link>
	<title><![CDATA[Look up a biological numbers]]></title>
	<description><![CDATA[<p><strong>Did you ever need to look up a number</strong><span>&nbsp;like the volume of a cell or the cellular concentration of ATP, only to find yourself spending much more time than you wanted on the Internet or flipping through textbooks - all without much success?&nbsp;</span><br><br><span>Well, it didn&rsquo;t happen only to you. It is often surprising how difficult it can be to find concrete biological numbers, even for properties that have been measured numerous times. To help solve this for one and all, BioNumbers (</span><strong>the database of key numbers in molecular biology</strong><span>) was created. Along with the numbers, you'll find the relevant&nbsp;</span><strong>references to the original literature</strong><span>, useful comments, and related numbers.&nbsp;</span></p>
<p><span><span>To cite BioNumbers please refer to: Milo et al. Nucl. Acids Res. (2010) 38: D750-D753. When using a specific entry from the database it is highly recommended that you also specify the BioNumbers 6 digit ID, e.g. "BNID 100986, Milo et al 2010".&nbsp;</span></span></p><p>Address of the bookmark: <a href="http://bionumbers.hms.harvard.edu/" rel="nofollow">http://bionumbers.hms.harvard.edu/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44366/mitofinder</guid>
	<pubDate>Tue, 29 Aug 2023 02:13:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44366/mitofinder</link>
	<title><![CDATA[MitoFinder]]></title>
	<description><![CDATA[<p dir="auto">Allio, R., Schomaker-Bastos, A., Romiguier, J., Prosdocimi, F., Nabholz, B., &amp; Delsuc, F. (2020) Mol Ecol Resour. 20, 892-905. (<a href="https://doi.org/10.1111/1755-0998.13160">publication link</a>)</p>
<p dir="auto" style="text-align: center;"><a href="https://github.com/RemiAllio/MitoFinder/blob/master/image/logo.png" target="_blank"><img src="https://github.com/RemiAllio/MitoFinder/raw/master/image/logo.png" alt="Drawing" width="250" style="border: 0px;"></a></p>
<p dir="auto"><span>Mitofinder</span>&nbsp;is a pipeline to&nbsp;<span>assemble</span>&nbsp;mitochondrial genomes and&nbsp;<span>annotate</span>&nbsp;mitochondrial genes from trimmed read sequencing data.</p>
<p dir="auto"><span>MitoFinder</span>&nbsp;is also designed to&nbsp;<span>find</span>&nbsp;and&nbsp;<span>annotate</span>&nbsp;mitochondrial sequences in existing genomic assemblies (generated from Hifi/PacBio/Nanopore/Illumina sequencing data...)</p>
<p dir="auto"><span>MitoFinder</span>&nbsp;is distributed under the&nbsp;<a href="https://github.com/RemiAllio/MitoFinder/blob/master/License/LICENSE">license</a>.</p><p>Address of the bookmark: <a href="https://github.com/RemiAllio/MitoFinder" rel="nofollow">https://github.com/RemiAllio/MitoFinder</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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