<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/42965?offset=170</link>
	<atom:link href="https://bioinformaticsonline.com/related/42965?offset=170" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39821/gvolante-completeness-assessment-of-genometranscriptome-sequences</guid>
	<pubDate>Tue, 06 Aug 2019 21:37:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39821/gvolante-completeness-assessment-of-genometranscriptome-sequences</link>
	<title><![CDATA[gVolante: Completeness Assessment of Genome/Transcriptome Sequences]]></title>
	<description><![CDATA[<p><strong>gVolante</strong><span>&nbsp;provides an online interface for completeness assessment of user&rsquo;s original or publicly available sequence datasets as well as for browsing results of completeness assessment performed on publicly available genome and transcriptome assemblies.</span></p>
<p><img src="https://gvolante.riken.jp/images/assessment.png" width="937" height="545" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="https://gvolante.riken.jp/" rel="nofollow">https://gvolante.riken.jp/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36994/minimap2-a-versatile-pairwise-aligner-for-genomic-and-spliced-nucleotide-sequences</guid>
	<pubDate>Wed, 20 Jun 2018 07:55:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36994/minimap2-a-versatile-pairwise-aligner-for-genomic-and-spliced-nucleotide-sequences</link>
	<title><![CDATA[minimap2: A versatile pairwise aligner for genomic and spliced nucleotide sequences]]></title>
	<description><![CDATA[git clone https://github.com/lh3/minimap2
cd minimap2 &amp;&amp; make
# long sequences against a reference genome
./minimap2 -a test/MT-human.fa test/MT-orang.fa &gt; test.sam
# create an index first and then map
./minimap2 -d MT-human.mmi test/MT-human.fa
./minimap2 -a MT-human.mmi test/MT-orang.fa &gt; test.sam
# use presets (no test data)
./minimap2 -ax map-pb ref.fa pacbio.fq.gz &gt; aln.sam       # PacBio genomic reads
./minimap2 -ax map-ont ref.fa ont.fq.gz &gt; aln.sam         # Oxford Nanopore genomic reads
./minimap2 -ax sr ref.fa read1.fa read2.fa &gt; aln.sam      # short genomic paired-end reads
./minimap2 -ax splice ref.fa rna-reads.fa &gt; aln.sam       # spliced long reads
./minimap2 -ax splice -k14 -uf ref.fa reads.fa &gt; aln.sam  # Nanopore Direct RNA-seq
./minimap2 -cx asm5 asm1.fa asm2.fa &gt; aln.paf             # intra-species asm-to-asm alignment
./minimap2 -x ava-pb reads.fa reads.fa &gt; overlaps.paf     # PacBio read overlap
./minimap2 -x ava-ont reads.fa reads.fa &gt; overlaps.paf    # Nanopore read overlap
# man page for detailed command line options
man ./minimap2.1<p>Address of the bookmark: <a href="https://github.com/lh3/minimap2" rel="nofollow">https://github.com/lh3/minimap2</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38012/cosine-non-seeding-method-for-mapping-long-noisy-sequences</guid>
	<pubDate>Fri, 26 Oct 2018 00:41:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38012/cosine-non-seeding-method-for-mapping-long-noisy-sequences</link>
	<title><![CDATA[COSINE: non-seeding method for mapping long noisy sequences]]></title>
	<description><![CDATA[<p><span>Third generation sequencing (TGS) are highly promising technologies but the long and noisy reads from TGS are difficult to align using existing algorithms. Here, we present COSINE, a conceptually new method designed specifically for aligning long reads contaminated by a high level of errors.</span></p><p>Address of the bookmark: <a href="https://github.com/SUwonglab/COSINE" rel="nofollow">https://github.com/SUwonglab/COSINE</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38678/upho-scripts-for-homology-and-orthology-assessment-from-genomic-sequences</guid>
	<pubDate>Mon, 14 Jan 2019 10:36:42 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38678/upho-scripts-for-homology-and-orthology-assessment-from-genomic-sequences</link>
	<title><![CDATA[UPhO: Scripts for homology and orthology assessment from genomic sequences.]]></title>
	<description><![CDATA[<p>UPhO finds orthologs with and without inparalogs from input gene family trees. Refer to the Documentation.pdf for more detailed explanations on its usage, installation and dependencies. Type UPhO.py -h for help.</p>
<p>The only input requierement for UPhO is a tree (or trees) in Newick format in which the leaves are named with a species idenfifier, a field separator, and sequence identifier. By default, the field separator is the character "|" but custom delimiters can be defined. Examples of trees to test UPhO are provided in the TestData folder.</p><p>Address of the bookmark: <a href="https://github.com/ballesterus/UPhO" rel="nofollow">https://github.com/ballesterus/UPhO</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41405/sequence-tube-maps-displays-multiple-genomic-sequences-in-the-form-of-a-tube-map</guid>
	<pubDate>Wed, 11 Mar 2020 01:12:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41405/sequence-tube-maps-displays-multiple-genomic-sequences-in-the-form-of-a-tube-map</link>
	<title><![CDATA[Sequence Tube Maps: displays multiple genomic sequences in the form of a tube map]]></title>
	<description><![CDATA[<p>A JavaScript module for the visualization of genomic sequence graphs. It automatically generates a "tube map"-like visualization of sequence graphs which have been created with <a href="https://github.com/vgteam/vg">vg</a>. (<a href="https://github.com/vgteam/vg">https://github.com/vgteam/vg</a>)</p>
<h3>Link to working demo: <a href="https://vgteam.github.io/sequenceTubeMap/">https://vgteam.github.io/sequenceTubeMap/</a></h3>
<p><img src="https://raw.githubusercontent.com/vgteam/sequenceTubeMap/master/images/header.png" alt="image" style="border: 0px; border: 0px;"></p><p>Address of the bookmark: <a href="https://github.com/vgteam/sequenceTubeMap" rel="nofollow">https://github.com/vgteam/sequenceTubeMap</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44234/steps-to-find-palindrome-in-genomes</guid>
	<pubDate>Thu, 09 Mar 2023 02:56:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44234/steps-to-find-palindrome-in-genomes</link>
	<title><![CDATA[Steps to find palindrome in genomes !]]></title>
	<description><![CDATA[<div><div><div><div><div><div><div><div><div><div><p>Palindromes are sequences of nucleotides that read the same backward as forward. They can be present in genomes and have various biological functions. Here are some methods for discovering palindromes in genomes:</p><ol>
<li>
<p>Direct sequence search: One of the simplest ways to discover palindromes is to search the genome sequence directly for palindromic sequences using pattern matching tools, such as regular expressions or string algorithms. This approach can be useful for discovering simple palindromes, but may miss more complex palindromic structures.</p>
</li>
<li>
<p>Dot plot analysis: Dot plot analysis is a graphical method that can be used to identify palindromic regions in a genome. It involves plotting the genome sequence against itself and examining the diagonal patterns that emerge. Palindromic regions will appear as symmetrical patterns along the diagonal.</p>
</li>
<li>
<p>Restriction enzyme analysis: Some restriction enzymes, such as EcoRI and HindIII, recognize palindromic sequences and cleave DNA at these sites. By digesting the genome with these enzymes and examining the resulting fragments, palindromic regions can be identified.</p>
</li>
<li>
<p>Next-generation sequencing: High-throughput sequencing technologies, such as PacBio and Oxford Nanopore, can generate long reads that can span entire palindromic regions. By mapping these reads to the genome, palindromic regions can be identified and characterized.</p>
</li>
<li>
<p>Comparative genomics: Comparing the genomes of related species can also reveal palindromic regions that are conserved across evolutionarily divergent lineages. This approach can help identify functional palindromes that are under selective pressure.</p>
</li>
</ol><p>Overall, the discovery of palindromic sequences in genomes can be accomplished using a variety of methods, each with their own advantages and limitations. A combination of these methods can provide a comprehensive understanding of the palindromic landscape of a genome.</p></div></div></div></div></div></div></div></div></div></div>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34049/libsvm-a-library-for-support-vector-machines</guid>
	<pubDate>Wed, 02 Aug 2017 06:49:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34049/libsvm-a-library-for-support-vector-machines</link>
	<title><![CDATA[LIBSVM -- A Library for Support Vector Machines]]></title>
	<description><![CDATA[<p><strong>LIBSVM&nbsp;</strong>is an integrated software for support vector classification, (C-SVC,&nbsp;<a href="https://www.csie.ntu.edu.tw/~cjlin/libsvm/#nuandone">nu-SVC</a>), regression (epsilon-SVR,&nbsp;<a href="https://www.csie.ntu.edu.tw/~cjlin/libsvm/#nuandone">nu-SVR</a>) and distribution estimation (<a href="https://www.csie.ntu.edu.tw/~cjlin/libsvm/#nuandone">one-class SVM</a>). It supports multi-class classification.</p>
<p>Since version 2.8, it implements an SMO-type algorithm proposed in this paper:<br>R.-E. Fan, P.-H. Chen, and C.-J. Lin.&nbsp;<a href="https://www.csie.ntu.edu.tw/~cjlin/papers/quadworkset.pdf">Working set selection using second order information for training SVM</a>. Journal of Machine Learning Research 6, 1889-1918, 2005. You can also find a pseudo code there. (<a href="https://www.csie.ntu.edu.tw/~cjlin/libsvm/faq.html#f203">how to cite LIBSVM</a>)</p>
<p><span style="color: #ff0000;">Our goal is to help users from other fields to easily use SVM as a tool.&nbsp;</span><strong>LIBSVM&nbsp;</strong>provides a simple interface where users can easily link it with their own programs. Main features of&nbsp;<strong>LIBSVM</strong>&nbsp;include</p>
<ul>
<li>Different SVM formulations</li>
<li>Efficient multi-class classification</li>
<li>Cross validation for model selection</li>
<li>Probability estimates</li>
<li>Various kernels (including precomputed kernel matrix)</li>
<li>Weighted SVM for unbalanced data</li>
<li>Both C++ and&nbsp;<a href="https://www.csie.ntu.edu.tw/~cjlin/libsvm/#java">Java</a>&nbsp;sources</li>
<li><a href="https://www.csie.ntu.edu.tw/~cjlin/libsvm/#GUI">GUI</a>&nbsp;demonstrating SVM classification and regression</li>
<li><a href="https://www.csie.ntu.edu.tw/~cjlin/libsvm/#python">Python</a>,&nbsp;<a href="https://www.csie.ntu.edu.tw/~cjlin/libsvm/#R">R</a>,&nbsp;<a href="https://www.csie.ntu.edu.tw/~cjlin/libsvm/#matlab">MATLAB</a>,&nbsp;<a href="https://www.csie.ntu.edu.tw/~cjlin/libsvm/#perl">Perl</a>,&nbsp;<a href="https://www.csie.ntu.edu.tw/~cjlin/libsvm/#ruby">Ruby</a>,&nbsp;<a href="https://www.csie.ntu.edu.tw/~cjlin/libsvm/#weka">Weka</a>,&nbsp;<a href="https://www.csie.ntu.edu.tw/~cjlin/libsvm/#lisp">Common LISP</a>,&nbsp;<a href="https://www.csie.ntu.edu.tw/~cjlin/libsvm/#clisp">CLISP</a>,&nbsp;<a href="https://www.csie.ntu.edu.tw/~cjlin/libsvm/#haskell">Haskell</a>,&nbsp;<a href="https://www.csie.ntu.edu.tw/~cjlin/libsvm/#ocaml">OCaml</a>,&nbsp;<a href="https://www.csie.ntu.edu.tw/~cjlin/libsvm/#labview">LabVIEW</a>, and&nbsp;<a href="https://www.csie.ntu.edu.tw/~cjlin/libsvm/#PHP">PHP</a>&nbsp;interfaces.&nbsp;<a href="https://www.csie.ntu.edu.tw/~cjlin/libsvm/#csharp">C# .NET</a>&nbsp;code and&nbsp;<a href="https://www.csie.ntu.edu.tw/~cjlin/libsvm/#cuda">CUDA</a>&nbsp;extension is available.&nbsp;<br>It's also included in some data mining environments:&nbsp;<a href="http://rapid-i.com/">RapidMiner</a>,&nbsp;<a href="http://pcp.sourceforge.net/">PCP</a>, and&nbsp;<a href="http://lionoso.org/">LIONsolver</a>.</li>
<li>Automatic model selection which can generate contour of cross validation accuracy.</li>
<li></li>
</ul>
<p>https://www.csie.ntu.edu.tw/~cjlin/libsvm/</p><p>Address of the bookmark: <a href="https://www.csie.ntu.edu.tw/~cjlin/libsvm/" rel="nofollow">https://www.csie.ntu.edu.tw/~cjlin/libsvm/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

</channel>
</rss>