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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44527?offset=190</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32853/progressivecactus</guid>
	<pubDate>Thu, 18 May 2017 05:29:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32853/progressivecactus</link>
	<title><![CDATA[progressiveCactus]]></title>
	<description><![CDATA[<p><span>Progressive Cactus is a whole-genome alignment package.</span></p>
<p><span><span>Distribution package for the Prgressive Cactus multiple genome aligner. Dependencies are linked as submodules</span></span></p>
<p>https://github.com/glennhickey/progressiveCactus</p><p>Address of the bookmark: <a href="https://github.com/glennhickey/progressiveCactus" rel="nofollow">https://github.com/glennhickey/progressiveCactus</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34404/sima-c-implementation-simultaneous-multiple-alignment-of-lcms-peak-lists</guid>
	<pubDate>Thu, 23 Nov 2017 17:15:52 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34404/sima-c-implementation-simultaneous-multiple-alignment-of-lcms-peak-lists</link>
	<title><![CDATA[SIMA C++ Implementation: Simultaneous Multiple Alignment of LC/MS Peak Lists]]></title>
	<description><![CDATA[<p style="text-align: justify;">This is the c++ implementation for SIMA - Simultaneous Multiple Alignment of LC/MS Peak Lists. The package contains C++ source code as well as two binary files. The latter were tested under various operating systems, including Windows XP SP3 32bit, Windows Vista 32bit, Windows 2008 Server, Windows 7 32bit and 64bit, Ubuntu 10.04 64bit, Ubuntu 10.10 64bit, and gentoo AMD64.</p>
<p style="text-align: justify;">The corresponding publication can be found here:</p>
<p style="text-align: justify;">B. Voss*, M. Hanselmann*, B.Y. Renard, M.S. Lindner, U. K&ouml;the, M. Kirchner, F.A. Hamprecht (2011). SIMA: Simultaneous Muliple Alignment of LC/MS Peak Lists, Bioinformatics 27(7):987-993.&nbsp;<a href="http://dx.doi.org/10.1093/bioinformatics/btr051">[doi]</a>&nbsp;<a href="https://hciweb.iwr.uni-heidelberg.de/sites/default/files/node/files/517307327/hanselmann_11_sima.pdf">[techreport]</a></p><p>Address of the bookmark: <a href="https://hciweb.iwr.uni-heidelberg.de/hci/softwares/sima" rel="nofollow">https://hciweb.iwr.uni-heidelberg.de/hci/softwares/sima</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43799/kast</guid>
	<pubDate>Wed, 23 Feb 2022 08:28:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43799/kast</link>
	<title><![CDATA[KAST]]></title>
	<description><![CDATA[<p><span>Perform Alignment-free k-tuple frequency comparisons from sequences. This can be in the form of two input files (e.g. a reference and a query) or a single file for pairwise comparisons to be made.</span></p><p>Address of the bookmark: <a href="https://github.com/martinjvickers/KAST" rel="nofollow">https://github.com/martinjvickers/KAST</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34038/quota-synteny-alignment</guid>
	<pubDate>Mon, 31 Jul 2017 04:11:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34038/quota-synteny-alignment</link>
	<title><![CDATA[Quota synteny alignment]]></title>
	<description><![CDATA[<p><span>Typically in comparative genomics, we can identify anchors, chain them into syntenic blocks and interpret these blocks as derived from a common descent. However, when comparing two genomes undergone ancient genome duplications (plant genomes in particular), we have large number of blocks that are not orthologous, but are paralogous. This has forced us sometimes to use&nbsp;</span><em>ad-hoc</em><span>&nbsp;rules to screen these blocks. So the question is:&nbsp;</span><span>given the expected depth (quota) along both x- and y-axis, select a subset of the anchors with maximized total score</span><span>.</span></p><p>Address of the bookmark: <a href="https://github.com/tanghaibao/quota-alignment" rel="nofollow">https://github.com/tanghaibao/quota-alignment</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36512/hisat2-a-fast-and-sensitive-alignment-program-for-mapping-next-generation-sequencing-reads</guid>
	<pubDate>Tue, 08 May 2018 04:27:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36512/hisat2-a-fast-and-sensitive-alignment-program-for-mapping-next-generation-sequencing-reads</link>
	<title><![CDATA[HISAT2: a fast and sensitive alignment program for mapping next-generation sequencing reads]]></title>
	<description><![CDATA[<p><strong>HISAT2</strong><span>&nbsp;is a fast and sensitive alignment program for mapping next-generation sequencing reads (both DNA and RNA) to a population of human genomes (as well as to a single reference genome). Based on an extension of BWT for graphs&nbsp;</span><a href="http://dl.acm.org/citation.cfm?id=2674828">[Sir&eacute;n et al. 2014]</a><span>, we designed and implemented a graph FM index (GFM), an original approach and its first implementation to the best of our knowledge. In addition to using one global GFM index that represents a population of human genomes, HISAT2 uses a large set of small GFM indexes that collectively cover the whole genome (each index representing a genomic region of 56 Kbp, with 55,000 indexes needed to cover the human population). These small indexes (called local indexes), combined with several alignment strategies, enable rapid and accurate alignment of sequencing reads. This new indexing scheme is called a Hierarchical Graph FM index (HGFM).&nbsp;</span></p>
<p><span>more at&nbsp;https://ccb.jhu.edu/software/hisat2/index.shtml</span></p><p>Address of the bookmark: <a href="https://github.com/infphilo/hisat2" rel="nofollow">https://github.com/infphilo/hisat2</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36846/gblocks-eliminates-poorly-aligned-positions-and-divergent-regions-of-a-dna-or-protein-alignment</guid>
	<pubDate>Sat, 02 Jun 2018 07:36:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36846/gblocks-eliminates-poorly-aligned-positions-and-divergent-regions-of-a-dna-or-protein-alignment</link>
	<title><![CDATA[Gblocks: eliminates poorly aligned positions and divergent regions of a DNA or protein alignment]]></title>
	<description><![CDATA[<p><a href="http://molevol.cmima.csic.es/castresana/Gblocks.html">Gblocks</a><span>&nbsp;eliminates poorly aligned positions and divergent regions of a DNA or protein alignment so that it becomes more suitable for phylogenetic analysis. This server implements the most important features of the Gblocks program to make its use as simple as possible without loosing the functionality that it is necessary in most of the cases. Other options can be changed in the stand-alone program. You can see here an&nbsp;</span><a href="http://molevol.cmima.csic.es/castresana/Gblocks_server/nad3.pir-gb.htm">example output file</a><span>&nbsp;showing the blocks selected from a protein alignment. Further information can be found in the&nbsp;</span><a href="http://molevol.cmima.csic.es/castresana/Gblocks/Gblocks_documentation.html">online documentation</a><span>.&nbsp;</span></p><p>Address of the bookmark: <a href="http://molevol.cmima.csic.es/castresana/Gblocks_server.html" rel="nofollow">http://molevol.cmima.csic.es/castresana/Gblocks_server.html</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37584/mulan-multiple-sequence-local-alignment-and-visualization-for-studying-function-and-evolution</guid>
	<pubDate>Fri, 24 Aug 2018 09:50:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37584/mulan-multiple-sequence-local-alignment-and-visualization-for-studying-function-and-evolution</link>
	<title><![CDATA[Mulan: Multiple-sequence local alignment and visualization for studying function and evolution]]></title>
	<description><![CDATA[<p>Mulan: Multiple-sequence local alignment and visualization for studying function and evolution</p>
<p><span>Mulan (</span><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC540288/#ref44">http://mulan.dcode.org/</a><span>), a novel method and a network server for comparing multiple draft and finished-quality sequences to identify functional elements conserved over evolutionary time. Mulan brings together several novel algorithms: the TBA multi-aligner program for rapid identification of local sequence conservation, and the multiTF program for detecting evolutionarily conserved transcription factor binding sites in multiple alignments. In addition, Mulan supports two-way communication with the GALA database; alignments of multiple species dynamically generated in GALA can be viewed in Mulan, and conserved transcription factor binding sites identified with Mulan/multiTF can be integrated and overlaid with extensive genome annotation data using GALA.</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC540288/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC540288/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39689/msaprobs-parallel-and-accurate-multiple-sequence-alignment</guid>
	<pubDate>Tue, 09 Jul 2019 23:58:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39689/msaprobs-parallel-and-accurate-multiple-sequence-alignment</link>
	<title><![CDATA[MSAProbs - Parallel and accurate multiple sequence alignment]]></title>
	<description><![CDATA[<p><strong>MSAProbs</strong><span>&nbsp;is a well-established state-of-the-art multiple sequence alignment algorithm for protein sequences. The design of MSAProbs is based on a combination of pair hidden Markov models and partition functions to calculate posterior probabilities. Assessed using the popular benchmarks: BAliBASE, PREFAB, SABmark and OXBENCH, MSAProbs achieves statistically significant accuracy improvements over the existing top performing aligners, including ClustalW, MAFFT, MUSCLE, ProbCons and Probalign. In addition, MSAProbs is optimized for shared-memory CPUs by employing a multi-threaded design, and further parallelized for distributed-memory systems using MPI to overcome high memory overhead barrier and achieve good parallel and data-size scalability.</span></p><p>Address of the bookmark: <a href="http://msaprobs.sourceforge.net/homepage.htm#latest" rel="nofollow">http://msaprobs.sourceforge.net/homepage.htm#latest</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40711/vg-variation-graph-data-structures-interchange-formats-alignment-genotyping-and-variant-calling-methods</guid>
	<pubDate>Tue, 28 Jan 2020 03:53:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40711/vg-variation-graph-data-structures-interchange-formats-alignment-genotyping-and-variant-calling-methods</link>
	<title><![CDATA[VG: variation graph data structures, interchange formats, alignment, genotyping, and variant calling methods]]></title>
	<description><![CDATA[<p><em>Variation graphs</em>&nbsp;provide a succinct encoding of the sequences of many genomes. A variation graph (in particular as implemented in vg) is composed of:</p>
<ul>
<li><em>nodes</em>, which are labeled by sequences and ids</li>
<li><em>edges</em>, which connect two nodes via either of their respective ends</li>
<li><em>paths</em>, describe genomes, sequence alignments, and annotations (such as gene models and transcripts) as walks through nodes connected by edges</li>
</ul><p>Address of the bookmark: <a href="https://github.com/vgteam/vg" rel="nofollow">https://github.com/vgteam/vg</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44481/unialigner-a-parameter-free-framework-for-fast-sequence-alignment</guid>
	<pubDate>Fri, 08 Mar 2024 23:36:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44481/unialigner-a-parameter-free-framework-for-fast-sequence-alignment</link>
	<title><![CDATA[UniAligner: a parameter-free framework for fast sequence alignment]]></title>
	<description><![CDATA[<p>UniAligner (formerly, TandemAligner) is the first parameter-free algorithm for sequence alignment that introduces a sequence-dependent alignment scoring that automatically changes for any pair of compared sequences. Classical alignment approaches, such as the Smith-Waterman algorithm, that work well for most sequences, fail to construct biologically adequate alignments of extra-long tandem repeats (ETRs), such as human centromeres and immunoglobulin loci. This limitation was overlooked in the previous studies since the sequences of the centromeres and other ETRs across multiple genomes only became available recently.</p>
<p>More at https://www.nature.com/articles/s41592-023-01970-4</p><p>Address of the bookmark: <a href="https://github.com/seryrzu/unialigner" rel="nofollow">https://github.com/seryrzu/unialigner</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>

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