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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37830?offset=350</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38593/excavator-detecting-copy-number-variants-from-whole-exome-sequencing-data</guid>
	<pubDate>Fri, 04 Jan 2019 10:10:48 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38593/excavator-detecting-copy-number-variants-from-whole-exome-sequencing-data</link>
	<title><![CDATA[EXCAVATOR: detecting copy number variants from whole-exome sequencing data]]></title>
	<description><![CDATA[<p><span>EXCAVATOR, for the detection of copy number variants (CNVs) from whole-exome sequencing data. EXCAVATOR combines a three-step normalization procedure with a novel heterogeneous hidden Markov model algorithm and a calling method that classifies genomic regions into five copy number states. We validate EXCAVATOR on three datasets and compare the results with three other methods. These analyses show that EXCAVATOR outperforms the other methods and is therefore a valuable tool for the investigation of CNVs in largescale projects, as well as in clinical research and diagnostics. EXCAVATOR is freely available at&nbsp;</span><span><a href="http://sourceforge.net/projects/excavatortool/" target="_blank"><span>http://sourceforge.net/projects/excavatortool/</span></a></span><span>.</span><br><br><br><span>EXCAVATOR is a novel software package for the detection of copy number variants (CNVs) from whole-exome sequencing data.</span><br><span>EXCAVATOR has been published on Genome Biology (</span><a href="http://genomebiology.com/2013/14/10/R120/abstract" target="_blank">http://genomebiology.com/2013/14/10/R120/abstract<span></span></a><span>).</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/excavatortool/" rel="nofollow">https://sourceforge.net/projects/excavatortool/</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/39827/prof-dr-med-andreas-ramming</guid>
  <pubDate>Wed, 07 Aug 2019 03:25:48 -0500</pubDate>
  <link></link>
  <title><![CDATA[Prof. Dr. med. Andreas Ramming]]></title>
  <description><![CDATA[
<p>In many autoimmune diseases, a misdirected immune response leads to chronic inflammation and subsequently to fibrotic and degenerative tissue remodeling. Therapeutic options are available for inflammatory joint diseases, but only about 40% of patients respond to these existing therapies on a permanent basis. In the remaining cases, these therapies miss their target from the beginning or later during the course of treatment failure. There are currently no causal therapies available for the treatment of fibrotic autoimmune diseases such as systemic sclerosis. Therefore, there is an urgent need to develop new therapeutic options for the treatment of fibrotic and synovitic autoimmune diseases. His group is therefore deal with the molecular mechanisms of these misdirected signaling pathways for the development of novel, targeted therapies</p>

<p>http://www.medizin3.uk-erlangen.de/forschung/arbeitsgruppen/matrixbiologie-entzuendliche-signalwege-in-arthritis-und-fibrose/</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40792/haslr-a-tool-for-rapid-genome-assembly-of-long-sequencing-reads</guid>
	<pubDate>Fri, 31 Jan 2020 05:50:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40792/haslr-a-tool-for-rapid-genome-assembly-of-long-sequencing-reads</link>
	<title><![CDATA[HASLR: a tool for rapid genome assembly of long sequencing reads]]></title>
	<description><![CDATA[<p><span>HASLR is a tool for rapid genome assembly of long sequencing reads. HASLR is a hybrid tool which means it requires long reads generated by Third Generation Sequencing technologies (such as PacBio or Oxford Nanopore) together with Next Generation Sequencing reads (such as Illumina) from the same sample.&nbsp;</span></p><p>Address of the bookmark: <a href="https://github.com/vpc-ccg/haslr" rel="nofollow">https://github.com/vpc-ccg/haslr</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42826/ktrim-an-extra-fast-and-accurate-adapter-and-quality-trimmer-for-sequencing-data</guid>
	<pubDate>Thu, 11 Feb 2021 21:39:05 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42826/ktrim-an-extra-fast-and-accurate-adapter-and-quality-trimmer-for-sequencing-data</link>
	<title><![CDATA[Ktrim: an extra-fast and accurate adapter- and quality-trimmer for sequencing data]]></title>
	<description><![CDATA[<p>Ktrim&nbsp;is written in&nbsp;<code style="font-size: 13.6px; padding: 0.2em 0.4em; margin: 0px; background-color: var(--color-markdown-code-bg);">C++</code>&nbsp;for GNU Linux/Unix platforms. After uncompressing the source package, you can find an executable file&nbsp;<code style="font-size: 13.6px; padding: 0.2em 0.4em; margin: 0px; background-color: var(--color-markdown-code-bg);">ktrim</code>&nbsp;under&nbsp;<code style="font-size: 13.6px; padding: 0.2em 0.4em; margin: 0px; background-color: var(--color-markdown-code-bg);">bin/</code>&nbsp;directory compiled using&nbsp;<code style="font-size: 13.6px; padding: 0.2em 0.4em; margin: 0px; background-color: var(--color-markdown-code-bg);">g++ v4.8.5</code>&nbsp;and linked with&nbsp;<code style="font-size: 13.6px; padding: 0.2em 0.4em; margin: 0px; background-color: var(--color-markdown-code-bg);">libz v1.2.7</code>&nbsp;for Linux x86_64 system. If you could not run it (which is usually caused by low version of&nbsp;<code style="font-size: 13.6px; padding: 0.2em 0.4em; margin: 0px; background-color: var(--color-markdown-code-bg);">libc++</code>&nbsp;or&nbsp;<code style="font-size: 13.6px; padding: 0.2em 0.4em; margin: 0px; background-color: var(--color-markdown-code-bg);">libz</code>&nbsp;library) or you want to build a version optimized for your system, you can re-compile the programs:</p>
<p>user@linux$ make clean &amp;&amp; make</p><p>Address of the bookmark: <a href="https://github.com/hellosunking/Ktrim" rel="nofollow">https://github.com/hellosunking/Ktrim</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37820/s-plot2-rapid-visual-and-statistical-analysis-of-genomic-sequences</guid>
	<pubDate>Tue, 02 Oct 2018 17:57:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37820/s-plot2-rapid-visual-and-statistical-analysis-of-genomic-sequences</link>
	<title><![CDATA[S-plot2: Rapid Visual and Statistical Analysis of Genomic Sequences]]></title>
	<description><![CDATA[<p><span>S-plot2 creates an interactive, two-dimensional heatmap capturing the similarities and dissimilarities in nucleotide usage between genomic sequences (partial or complete). In S-plot2, whole eukaryotic chromosomes and smaller prokaryotic genomes can be efficiently compared. The tool includes functionality to extract, analyze, and automate BLAST queries of regions of interest within the heatmap. This facilitates the investigation of quickly evolving coding regions, novel coding regions, and laterally transferred elements.</span></p><p>Address of the bookmark: <a href="https://bitbucket.org/lkalesinskas/splot" rel="nofollow">https://bitbucket.org/lkalesinskas/splot</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40948/bio7-an-integrated-development-environment-for-ecological-modeling-scientific-image-analysis-and-statistical-analysis</guid>
	<pubDate>Fri, 07 Feb 2020 23:32:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40948/bio7-an-integrated-development-environment-for-ecological-modeling-scientific-image-analysis-and-statistical-analysis</link>
	<title><![CDATA[Bio7: an integrated development environment for ecological modeling, scientific image analysis and statistical analysis]]></title>
	<description><![CDATA[<p><span>The application Bio7 is an integrated development environment for ecological modeling, scientific image analysis and statistical analysis. The application itself is based on an RCP-Eclipse-Environment (Rich-Client-Platform) which offers a huge flexibility in configuration and extensibility because of its plug-in structure and the possibility of customization.</span></p>
<p><a href="https://bio7.org/about/">https://bio7.org/about/</a></p><p>Address of the bookmark: <a href="https://bio7.org/home-2/" rel="nofollow">https://bio7.org/home-2/</a></p>]]></description>
	<dc:creator>Nidhi Rajput</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44876/dna2bit-an-ultra-fast-and-accurate-genomic-distance-estimation-software</guid>
	<pubDate>Wed, 13 Aug 2025 19:56:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44876/dna2bit-an-ultra-fast-and-accurate-genomic-distance-estimation-software</link>
	<title><![CDATA[dna2bit: an ultra-fast and accurate genomic distance estimation software]]></title>
	<description><![CDATA[<p dir="auto">dna2bit: an ultra-fast and accurate genomic distance estimation software</p>
<div dir="auto"><a href="https://github.com/lijuzeng/dna2bit#compilation"></a></div>
<p dir="auto">dna2bit is a software tool developed in C++11, leveraging the capabilities of OpenMP for parallel computing and the popcount technique for efficient bit manipulation.&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/lijuzeng/dna2bit" rel="nofollow">https://github.com/lijuzeng/dna2bit</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35119/frontend-perl-web-framework-documentation-andrej-sali-lab</guid>
	<pubDate>Mon, 08 Jan 2018 22:32:03 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35119/frontend-perl-web-framework-documentation-andrej-sali-lab</link>
	<title><![CDATA[Frontend: Perl Web framework documentation - Andrej Sali Lab]]></title>
	<description><![CDATA[<p><span>The frontend is a set of Perl classes that displays the web interface, allowing a user to upload their input files, start a job, display a list of all jobs in the system, and get back job results. The main&nbsp;</span><a href="https://saliweb.readthedocs.io/en/latest/modules/frontend.html#saliwebfrontend" title="saliwebfrontend"><code><span>saliwebfrontend</span></code></a><span>&nbsp;class must be subclassed for each web service. This class is then used to display the web pages using a set of CGI scripts that are set up automatically by the build system.</span></p><p>Address of the bookmark: <a href="https://saliweb.readthedocs.io/en/latest/frontend.html" rel="nofollow">https://saliweb.readthedocs.io/en/latest/frontend.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38489/biotite-a-general-framework-for-computational-biology</guid>
	<pubDate>Mon, 17 Dec 2018 18:52:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38489/biotite-a-general-framework-for-computational-biology</link>
	<title><![CDATA[Biotite: A general framework for computational biology]]></title>
	<description><![CDATA[<p><span>The package is open source and freely available at GitHub (</span><span><a href="https://github.com/biotite-dev/biotite" target="_blank">https://github.com/biotite-dev/biotite</a></span><span>). This package is simple to use especially for the beginners in programming and computationally efficient because of the implementation of Numpy and Cython.&nbsp;Biotite consists of four sub packages: sequence, structure, databases, and application. The&nbsp;</span><em>sequence</em><span>&nbsp;and&nbsp;</span><em>structure</em><span>&nbsp;modules serve for the analysis of sequence and structural data analysis respectively,&nbsp;</span><em>database</em><span>&nbsp;downloads files from the other databases such as RCSB PDB, and&nbsp;</span><em>application</em><span>&nbsp;provides interface for external software.&nbsp;</span></p>
<p><span><span>The&nbsp;</span><em>Biotite</em><span>&nbsp;package bundles popular tasks in computational biology into an unifying framework, which is easy to use on the one hand side, but is also computationally efficient due to intensive usage of&nbsp;</span><em>NumPy</em><span>&nbsp;and&nbsp;</span><em>Cython</em><span>. This package focuses on working with sequence and structure data and supports various file formats and analysis and manipulation functions.</span></span></p><p>Address of the bookmark: <a href="https://github.com/biotite-dev/biotite" rel="nofollow">https://github.com/biotite-dev/biotite</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42201/rosettaantibodydesign-rabd-a-general-framework-for-computational-antibody-design</guid>
	<pubDate>Sun, 20 Sep 2020 06:03:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42201/rosettaantibodydesign-rabd-a-general-framework-for-computational-antibody-design</link>
	<title><![CDATA[RosettaAntibodyDesign (RAbD): A general framework for computational antibody design]]></title>
	<description><![CDATA[<p><strong>RosettaAntibodyDesign (RAbD)</strong>&nbsp;is a generalized framework for the design of antibodies, in which a user can easily tailor the run to their project needs.&nbsp;<strong>The algorithm is meant to sample the diverse sequence, structure, and binding space of an antibody-antigen complex.</strong>&nbsp;It can be used for a multitude of project types, from denovo design to redesigns that improve binding affinity, optimize stability, or manipulate function.</p>
<p>The framework is based on rigorous bioinformatic analysis and rooted very much on our&nbsp;<a href="https://www.ncbi.nlm.nih.gov/pubmed/21035459">recent clustering</a>&nbsp;of antibody CDR regions. It uses the&nbsp;<strong>North/Dunbrack CDR definition</strong>&nbsp;as outlined in the North/Dunbrack clustering paper.</p>
<p>More at</p>
<p>https://www.rosettacommons.org/docs/latest/application_documentation/antibody/RosettaAntibodyDesign</p>
<p>https://bio-jade.readthedocs.io/en/latest/installation.html</p><p>Address of the bookmark: <a href="https://www.rosettacommons.org/docs/latest/application_documentation/antibody/RosettaAntibodyDesign" rel="nofollow">https://www.rosettacommons.org/docs/latest/application_documentation/antibody/RosettaAntibodyDesign</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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