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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31087?offset=1170</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43815/kebabs-package-provides-functionality-for-kernel-based-analysis-of-biological-sequences-via-support-vector-machine-svm-based-methods</guid>
	<pubDate>Fri, 04 Mar 2022 00:14:11 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43815/kebabs-package-provides-functionality-for-kernel-based-analysis-of-biological-sequences-via-support-vector-machine-svm-based-methods</link>
	<title><![CDATA[kebabs: package provides functionality for kernel based analysis of biological sequences via Support Vector Machine (SVM) based methods]]></title>
	<description><![CDATA[<p><span>The&nbsp;</span><tt>kebabs</tt><span>&nbsp;package provides functionality for kernel based analysis of biological sequences via Support Vector Machine (SVM) based methods. Biological sequences include DNA, RNA, and amino acid (AA) sequences. Sequence kernels define similarity measures between sequences. The package implements some of the most important kernels for sequence analysis in a very flexible and efficient way and extends the standard position-independent functionality of these kernels in a novel way to take the position of patterns in the sequences into account for the similarity measure.</span></p>
<p>http://www.bioinf.jku.at/software/kebabs/</p>
<p>http://bioconductor.org/packages/release/bioc/vignettes/kebabs/inst/doc/kebabs.pdf</p><p>Address of the bookmark: <a href="http://www.bioinf.jku.at/software/kebabs/" rel="nofollow">http://www.bioinf.jku.at/software/kebabs/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44541/powerful-books-for-learning-data-analysis-with-r</guid>
	<pubDate>Tue, 28 May 2024 07:42:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44541/powerful-books-for-learning-data-analysis-with-r</link>
	<title><![CDATA[Powerful books for learning data analysis with R]]></title>
	<description><![CDATA[<p><span>R is powerful tool for data analysis, visualization, and machine learning. And it costs $0 to use! Here are six FREE books you can use to learn R today:</span></p>
<p><span>https://csgillespie.github.io/efficientR/</span></p>
<p><span>https://r-graphics.org/</span></p>
<p><span>https://rstudio-education.github.io/hopr/</span></p>
<p><span>https://r-pkgs.org/</span></p>
<p><span>https://r4ds.had.co.nz/</span></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://r-graphics.org/" rel="nofollow">https://r-graphics.org/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/30331/16th-congress-of-the-european-society-for-evolutionary-biology-eseb</guid>
  <pubDate>Thu, 22 Dec 2016 08:08:37 -0600</pubDate>
  <link></link>
  <title><![CDATA[16th Congress of the European Society for Evolutionary Biology (ESEB)]]></title>
  <description><![CDATA[
<p>Abstract submissions for our upcoming symposium on the Genomics of Adaptation that will take place as part of the 16th Congress of the European Society for Evolutionary Biology (ESEB). The conference will take place from August 20th - August 25th, 2017 in Groningen, the Netherlands. </p>

<p>SYMPOSIUM DESCRIPTION: Genomics of Adaptation [S16] Model organisms for life-history research are mainly studied in the lab where functional genetics is assessable. In general, however, knowledge about their eco-evolutionary dynamics, such as biotic interactions, is rare. By contrast, in organisms for which the ecology and adaptation strategies in the field are well known, we typically lack the appropriate genetic tools to investigate functionality. Advances in genomics and statistics as well as investments in evolutionary model organisms are now providing access to putatively adaptive genome-wide variation within species from across the tree of life. In this symposium, we focus on integrating life-history biology, genetics and evolutionary ecology in the genomics era. </p>

<p>We wish to (1) highlight the role of genetic architecture of complex traits, such as adaptations to biotic interactions or life-history traits; (2) contrast this to morphological traits which are generally thought to have a less complex genetic architecture; and (3) discuss the opportunities and drawbacks of specific model systems. </p>

<p>INVITED SPEAKERS: Josephine Pemberton, University of Cambridge (http://bit.ly/2hJWytJ ) Peter Tiffin, University of Minnesota (http://bit.ly/2hK7HuS ) </p>

<p>ABSTRACT SUBMISSION The deadline for abstract submission is January 10, 2017. For more information and to submit abstracts online, please visit: http://bit.ly/2fBXlvN We look forward to an exciting symposium and seeing you all in Groningen! Sincerely, Ben Blackman, UC Berkeley Maaike de Jong, University of Bristol Bart Pannebakker, Wageningen University Noah Whiteman, UC Berkeley Jelle Zandveld, Wageningen University</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/2726/comparison-of-short-read-de-novo-alignment-algorithms</guid>
	<pubDate>Wed, 21 Aug 2013 07:56:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/2726/comparison-of-short-read-de-novo-alignment-algorithms</link>
	<title><![CDATA[Comparison of Short Read De Novo Alignment Algorithms]]></title>
	<description><![CDATA[<p>Excellent article to introduce different sequencing methods along with tools for de novo assembly of sequencing reads and their relevant references.</p>
<p>Title:&nbsp;<strong>Comparison of Short Read De Novo Alignment Algorithms&nbsp;</strong></p>
<p>Author<strong>: Nikhil Gopal</strong></p><p>Address of the bookmark: <a href="http://biochem218.stanford.edu/Projects%202011/Gopal%202011.pdf" rel="nofollow">http://biochem218.stanford.edu/Projects%202011/Gopal%202011.pdf</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30680/easybuild</guid>
	<pubDate>Fri, 27 Jan 2017 16:00:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30680/easybuild</link>
	<title><![CDATA[EasyBuild]]></title>
	<description><![CDATA[<p><a href="https://github.com/hpcugent/easybuild">EasyBuild</a><span>&nbsp;is a software build and installation framework that allows you to manage (scientific) software on High Performance Computing (HPC) systems in an efficient way.</span><br><span>A full list of supported software packages is available&nbsp;</span><a href="http://easybuild.readthedocs.io/en/latest/version-specific/Supported_software.html">here</a><span>.</span></p><p>Address of the bookmark: <a href="https://hpcugent.github.io/easybuild/" rel="nofollow">https://hpcugent.github.io/easybuild/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/30747/11th-international-joint-conference-on-biomedical-engineering-systems-and-technologies</guid>
  <pubDate>Wed, 01 Feb 2017 17:39:27 -0600</pubDate>
  <link></link>
  <title><![CDATA[11th International Joint Conference on Biomedical Engineering Systems and Technologies]]></title>
  <description><![CDATA[
<p>BIOSTEC, the 11th International Joint Conference on Biomedical Engineering Systems and Technologies.<br /> Registration to BIOINFORMATICS allows free access to all other BIOSTEC conferences. </p>

<p>Upcoming Deadlines<br />Regular Paper Submission: July 31, 2017 <br />Regular Paper Authors Notification: October 16, 2017 <br />Regular Paper Camera Ready and Registration: October 30, 2017 </p>

<p>The purpose of the International Conference on Bioinformatics Models, Methods and Algorithms is to bring together researchers and practitioners interested in the application of computational systems, algorithmic concepts and information technologies to address challenging problems in Biomedical research with a particular focus on the emerging problems in Bioinformatics and computational biology. There is a tremendous need to explore how mathematical, statistical and computational models can be used to better understand biological processes and systems, while developing new methodologies and tools to analysis the massive currently-available biological data. Areas of interest to this community include systems biology, sequence analysis, biostatistics, image analysis, network and graph models, scientific data management and data mining, machine learning, pattern recognition, computational evolutionary biology, computational genomics and proteomics, and related areas.</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34931/3d-dna-3d-de-novo-assembly-3d-dna-pipeline</guid>
	<pubDate>Thu, 28 Dec 2017 10:09:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34931/3d-dna-3d-de-novo-assembly-3d-dna-pipeline</link>
	<title><![CDATA[3d-dna: 3D de novo assembly (3D DNA) pipeline]]></title>
	<description><![CDATA[<p>This code is designed to enable anyone to reproduce the Hs2-HiC and the AaegL4 genomes reported in:&nbsp;<a href="http://science.sciencemag.org/content/early/2017/03/22/science.aal3327.full">Dudchenko et al., De novo assembly of the Aedes aegypti genome using Hi-C yields chromosome-length scaffolds. Science, 2017.</a></p>
<p>Unless otherwise noted, all terminology below is consistent with this paper, and all references to figures and tables in this readme refer to this paper. Specifically, some of the terminology used below is outlined in&nbsp;<code>Figure S2</code>. The assembly procedure is described in detail in the&nbsp;<a href="http://science.sciencemag.org/content/suppl/2017/03/22/science.aal3327.DC1?_ga=1.9816115.760837492.1490574064">Supporting Online Materials</a>, specifically in the section labelled &ldquo;Pipeline description&rdquo;.</p>
<p>In addition, the pipeline uses tools and methods from&nbsp;<a href="http://www.cell.com/cell-systems/abstract/S2405-4712(16)30219-8">Juicer (Durand &amp; Shamim et al., Cell Systems, 2016)</a>&nbsp;and&nbsp;<a href="http://www.cell.com/cell-systems/abstract/S2405-4712(15)00054-X">Juicebox (Durand &amp; Robinson et al., Cell Systems, 2016)</a>, as well as additional dependencies noted below.</p>
<p>Feel free to post your questions and comments at:&nbsp;<a href="http://www.aidenlab.org/forum.html">http://www.aidenlab.org/forum.html</a></p>
<p>http://aidenlab.org/documentation.html</p><p>Address of the bookmark: <a href="https://github.com/theaidenlab/3d-dna" rel="nofollow">https://github.com/theaidenlab/3d-dna</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30897/finestructure-v2-globetrotter</guid>
	<pubDate>Mon, 13 Feb 2017 08:40:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30897/finestructure-v2-globetrotter</link>
	<title><![CDATA[fineSTRUCTURE v2 &amp; GLOBETROTTER]]></title>
	<description><![CDATA[<p>Software available at this site</p>
<div>
<ul>
<li><a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/finestructure_info.html">FineSTRUCTURE version 2</a>, a pipeline for running ChromoPainter and FineSTRUCTURE for population inference. A GUI is available for interpretation. Download from the <a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/finestructure.html">Downloads</a> page.</li>
<li><a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/finestructureR.html">FineSTRUCTURE R scripts</a>, a facility for exploring the results when the GUI is unavailable.</li>
<li><a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/globetrotter.html">GLOBETROTTER</a>, the admixture dating method based on ChromoPainter. Download from the <a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/finestructure.html">Downloads</a> page.</li>
<li><a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/admixture.html">AdmixturePainting</a>, A set of R tools to inmterpret the results of ADMIXTURE and STRUCTURE-like mixture models.</li>
<li><a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/radpainter.html">RADpainter</a>, finestructure and ChromoPainter for RAD tag data used for non-model organisms.</li>
<li>Scripts to perform many types of conversion. Included in the main software download from the <a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/finestructure.html">Downloads</a> page.</li>
</ul>
What this page is This page provides information about and downloads for <strong>methodology for Chromosome Painting</strong>. It is not a facility to analyse your genome. Sorry if you were misled by the punchy name!<br> About Chromosome Painting Painting is an efficient way of identifying important haplotype information from dense genotype data. It describes ancestry in an efficient way suitable for a range of further analyses, including population identification and admixture dating.</div><p>Address of the bookmark: <a href="http://paintmychromosomes.com/" rel="nofollow">http://paintmychromosomes.com/</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36456/alpaca-a-hybrid-strategy-for-assembly-of-genomic-dna-shotgun-sequencing-reads</guid>
	<pubDate>Mon, 30 Apr 2018 04:38:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36456/alpaca-a-hybrid-strategy-for-assembly-of-genomic-dna-shotgun-sequencing-reads</link>
	<title><![CDATA[ALPACA: A hybrid strategy for assembly of genomic DNA shotgun sequencing reads.]]></title>
	<description><![CDATA[<p><span>ALPACA requires Celera Assembler 8.3 or later. It is recommended to build Celera Assembler from source. (Why? The pre-built binaries CA_8.3rc1 and CA8.3rc2 will work for any large data set.&nbsp;</span></p>
<p><span>Detail paper at&nbsp;https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-017-3927-8</span></p><p>Address of the bookmark: <a href="https://github.com/VicugnaPacos/ALPACA" rel="nofollow">https://github.com/VicugnaPacos/ALPACA</a></p>]]></description>
	<dc:creator>Seema Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31123/biodownloader</guid>
	<pubDate>Sat, 25 Feb 2017 17:52:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31123/biodownloader</link>
	<title><![CDATA[BioDownloader]]></title>
	<description><![CDATA[<p><strong><em>BioDownloader</em></strong> is a program for downloading and/or updating files from ftp/http servers. The program has unique features that are specifically designed to deal with bioinformatics data files and servers:</p>
<ul>
<li>optimized to work with vast amount of data and very large file sets (~ 10,000 - 100,000).</li>
<li>allows the selective retrieval of only the required files (file masks, ls-lR parsing, recursive search, updates)</li>
<li>has a built-in repository containing the settings for the most common bioinformatics download needs</li>
<li>built-in wizard for batch post-processing of downloaded files (archive extraction, file conversion, etc.)</li>
<li>capable of performing multiple download or update tasks simultaneously</li>
</ul>
<p>BioDownloader has a built-in repository containing the settings for common bioinformatics file-synchronization needs, including the Protein Data Bank (PDB) and National Center for Biotechnology Information (NCBI) databases. It can post-process downloaded files, including archive extraction and file conversions.</p>
<p>http://dunbrack.fccc.edu/BioDownloader/</p><p>Address of the bookmark: <a href="http://dunbrack.fccc.edu/BioDownloader/" rel="nofollow">http://dunbrack.fccc.edu/BioDownloader/</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>

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