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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/45177?offset=280</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41669/filtlong-quality-filtering-tool-for-long-reads</guid>
	<pubDate>Wed, 13 May 2020 10:23:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41669/filtlong-quality-filtering-tool-for-long-reads</link>
	<title><![CDATA[Filtlong: quality filtering tool for long reads]]></title>
	<description><![CDATA[<p>Filtlong is a tool for filtering long reads by quality. It can take a set of long reads and produce a smaller, better subset. It uses both read length (longer is better) and read identity (higher is better) when choosing which reads pass the filter.</p>
<p>Filtlong builds into a stand-alone executable:</p>
<pre><code>git clone https://github.com/rrwick/Filtlong.git
cd Filtlong
make -j
bin/filtlong -h
</code></pre><p>Address of the bookmark: <a href="https://github.com/rrwick/Filtlong" rel="nofollow">https://github.com/rrwick/Filtlong</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41916/truvari-structural-variant-comparison-tool-for-vcfs</guid>
	<pubDate>Tue, 30 Jun 2020 21:30:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41916/truvari-structural-variant-comparison-tool-for-vcfs</link>
	<title><![CDATA[truvari: Structural variant comparison tool for VCFs]]></title>
	<description><![CDATA[<p>Structural variant comparison tool for VCFs</p>
<p>Given benchmark and comparsion sets of SVs, calculate the recall, precision, and f-measure.</p>
<p><a href="https://github.com/spiralgenetics/www.spiralgenetics.com">Spiral Genetics</a></p>
<p><a href="https://docs.google.com/presentation/d/17mvC1XOpOm7khAbZwF3SgtG2Rl4M9Mro37yF2nN7GhE/edit">Motivation</a></p><p>Address of the bookmark: <a href="https://github.com/spiralgenetics/truvari" rel="nofollow">https://github.com/spiralgenetics/truvari</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42155/clustergrammer-is-a-web-based-tool-for-visualizing-high-dimensional-data-as-an-interactive-and-shareable-hierarchically-clustered-heatmap</guid>
	<pubDate>Sun, 23 Aug 2020 19:30:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42155/clustergrammer-is-a-web-based-tool-for-visualizing-high-dimensional-data-as-an-interactive-and-shareable-hierarchically-clustered-heatmap</link>
	<title><![CDATA[Clustergrammer is a web-based tool for visualizing high-dimensional data as an interactive and shareable hierarchically clustered heatmap]]></title>
	<description><![CDATA[<p><span>Clustergrammer is a web-based tool for visualizing high-dimensional data (e.g. a matrix) as an interactive and shareable hierarchically clustered heatmap. Clustergrammer's front end (</span><a href="http://clustergrammer.readthedocs.io/clustergrammer_js.html#clustergrammer-js">Clustergrammer-JS</a><span>) is built using&nbsp;</span><a href="https://d3js.org/">D3.js</a><span>&nbsp;and its back-end (</span><a href="http://clustergrammer.readthedocs.io/clustergrammer_py.html#clustergrammer-py">Clustergrammer-PY</a><span>) is built using Python. Clustergrammer produces highly interactive visualizations that enable intuitive exploration of high-dimensional data and has several biology-specific features (e.g. enrichment analysis, see&nbsp;</span><a href="http://clustergrammer.readthedocs.io/biology_specific_features.html#biology-specific-features">Biology-Specific Features</a><span>) to facilitate the exploration of gene-level biological data.&nbsp;</span></p><p>Address of the bookmark: <a href="https://github.com/MaayanLab/clustergrammer" rel="nofollow">https://github.com/MaayanLab/clustergrammer</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/43902/interactivenn-a-web-based-tool-for-the-analysis-of-sets-through-venn-diagrams</guid>
	<pubDate>Wed, 29 Jun 2022 03:22:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43902/interactivenn-a-web-based-tool-for-the-analysis-of-sets-through-venn-diagrams</link>
	<title><![CDATA[InteractiVenn: a web-based tool for the analysis of sets through Venn diagrams]]></title>
	<description><![CDATA[<p><span>InteractiVenn, a more flexible tool for interacting with Venn diagrams including up to six sets. It offers a clean interface for Venn diagram construction and enables analysis of set unions while preserving the shape of the diagram. Set unions are useful to reveal differences and similarities among sets and may be guided in our tool by a tree or by a list of set unions. The tool also allows obtaining subsets&rsquo; elements, saving and loading sets for further analyses, and exporting the diagram in vector and image formats. InteractiVenn has been used to analyze two biological datasets, but it may serve set analysis in a broad range of domains.</span></p>
<p><span>More at&nbsp;https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0611-3</span></p>
<p><span><img src="https://media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs12859-015-0611-3/MediaObjects/12859_2015_611_Fig1_HTML.gif?as=webp" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="http://www.interactivenn.net/" rel="nofollow">http://www.interactivenn.net/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44501/minda-a-tool-for-evaluating-structural-variant-sv-callers</guid>
	<pubDate>Sun, 31 Mar 2024 02:43:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44501/minda-a-tool-for-evaluating-structural-variant-sv-callers</link>
	<title><![CDATA[Minda: a tool for evaluating structural variant (SV) callers]]></title>
	<description><![CDATA[<p dir="auto">Minda is a tool for evaluating structural variant (SV) callers that</p>
<ul dir="auto">
<li>standardizes VCF records for compatibility with both germline and somatic SV callers,</li>
<li>benchmarks against a single VCF input file, or</li>
<li>benchmarks against an ensemble call set created from multiple VCF input files.</li>
</ul><p>Address of the bookmark: <a href="https://github.com/KolmogorovLab/minda" rel="nofollow">https://github.com/KolmogorovLab/minda</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<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/researchlabs/view/38682/bourque-lab</guid>
  <pubDate>Mon, 14 Jan 2019 15:39:25 -0600</pubDate>
  <link></link>
  <title><![CDATA[Bourque Lab]]></title>
  <description><![CDATA[
<p>The goal of the lab is to understand mammalian genomes using comparative genomic and epigenomic analyses. Areas of interest include: the evolution of regulatory sequences, the role of transposable elements in gene regulation and the impact of genome rearrangements in evolution and cancer.</p>

<p>As a computational genomicists our work involves examining billions of DNA base pairs and interpreting how variation impacts basic biology and disease. We develop computational methods and resources for the functional annotation of genomes with a special emphasis on sequencing-based assays (e.g. ChIP-seq, RNA-Seq, exome- and whole-genome sequencing, single-cell analysis).</p>

<p>http://www.computationalgenomics.ca</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/856/papenfuss-lab</guid>
  <pubDate>Sun, 14 Jul 2013 12:22:28 -0500</pubDate>
  <link></link>
  <title><![CDATA[Papenfuss Lab]]></title>
  <description><![CDATA[
<p>The human genome project and similar projects in disease-causing organisms such as Plasmodium falciparum, which causes malaria in humans, have provided new tools for discovery in biology and have accelerated the development of understanding in human disease.</p>

<p>Research Area: <br />Analysis of Next Generation sequence data in cancer<br />Methods for analysis of structural variation in cancer genomes<br />Next Generation sequencing in malaria<br />Computational comparative genomics<br />Sensitive genomic sequence search techniques using hidden Markov models<br />Tasmanian devil facial tumour disease</p>

<p>Link @ http://www.wehi.edu.au/faculty_members/dr_tony_papenfuss</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/869/bioinformatics-phd-studentship-available-in-new-zealand</guid>
  <pubDate>Sun, 14 Jul 2013 13:36:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics PhD studentship available in New Zealand]]></title>
  <description><![CDATA[
<p>Bioinformatics PhD studentship available in New Zealand</p>

<p>The importance of transcriptional control has been explored in a burgeoning line of research over several decades; nevertheless, we are still far from having a complete picture of the regulatory mechanisms of genes and non-coding RNAs, and their influences on different phenotypes and disease states of a cell. Recent shifts towards large-scale analyses of transcriptional regulation on a sequence and epigenetic level are at the forefront of research, mainly due to sequencing technology advancements and a deeper understanding of the fundamental regulatory processes involved.</p>

<p>Arriving at a better understanding of the influence of specific parts of the overall regulatory machinery on disease states is a high priority of the group’s research agenda.</p>

<p>We are seeking an enthusiastic student to join the group as a PhD student. Applicants must have a BSc(Hons) or MSc degree in a relevant discipline and a willingness to learn and apply new techniques and work in a team. Both local and international students are encouraged to apply.</p>

<p>The studentship covers all university fees and an annual tax-exempt stipend of NZ$22,000 for three years.</p>

<p>Sebastian Schmeier recently joined Massey University and started his own research group in Auckland, New Zealand, a city regularly ranked one of the most livable in the world. This is your chance to experience the amazing Auckland lifestyle and the excitement of joining a young new science team, while staying connected to world class scientific networks.</p>

<p>To apply for the post, please send a cover letter stating your interest in the position and why you think you would be a good candidate, a Curriculum Vitae, a copy of your academic transcript, a sample of your written scientific work, and the names of three referees. Applications will be accepted until the position is filled.</p>

<p>Enquiries and applications to Sebastian Schmeier (s.schmeier@massey.ac.nz).</p>
]]></description>
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