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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27110?offset=340</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43850/merfin-improved-variant-filtering-assembly-evaluation-and-polishing-via-k-mer-validation</guid>
	<pubDate>Sun, 03 Apr 2022 20:35:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43850/merfin-improved-variant-filtering-assembly-evaluation-and-polishing-via-k-mer-validation</link>
	<title><![CDATA[Merfin: improved variant filtering, assembly evaluation and polishing via k-mer validation]]></title>
	<description><![CDATA[<p><span>Merfin, a&nbsp;</span><em>k</em><span>-mer based variant-filtering algorithm for improved accuracy in genotyping and genome assembly polishing. Merfin evaluates each variant based on the expected&nbsp;</span><em>k</em><span>-mer multiplicity in the reads, independently of the quality of the read alignment and variant caller&rsquo;s internal score. Merfin increased the precision of genotyped calls in several benchmarks, improved consensus accuracy and reduced frameshift errors when applied to human and nonhuman assemblies built from Pacific Biosciences HiFi and continuous long reads or Oxford Nanopore reads, including the first complete human genome. Moreover, we introduce assembly quality and completeness metrics that account for the expected genomic copy numbers.</span></p>
<p><span>More at&nbsp;https://www.nature.com/articles/s41592-022-01445-y</span></p>
<p><img src="https://media.springernature.com/full/springer-static/image/art%3A10.1038%2Fs41592-022-01445-y/MediaObjects/41592_2022_1445_Fig1_HTML.png" alt="image" style="border: 0px; border: 0px;"></p><p>Address of the bookmark: <a href="https://github.com/arangrhie/merfin" rel="nofollow">https://github.com/arangrhie/merfin</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29917/gojs</guid>
	<pubDate>Tue, 22 Nov 2016 08:25:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29917/gojs</link>
	<title><![CDATA[GoJS]]></title>
	<description><![CDATA[<p><strong>GoJS</strong> is a feature-rich JavaScript library for implementing custom interactive diagrams and complex visualizations across modern web browsers and platforms. <strong>GoJS</strong> makes constructing JavaScript diagrams of complex nodes, links, and groups easy with customizable templates and layouts.</p>
<p><strong>GoJS</strong> offers many advanced features for user interactivity such as drag-and-drop, copy-and-paste, in-place text editing, tooltips, context menus, automatic layouts, templates, data binding and models, transactional state and undo management, palettes, overviews, event handlers, commands, and an extensible tool system for custom operations.</p>
<p><strong>GoJS</strong> is pure JavaScript, so users get interactivity without requiring round-trips to servers and without plugins. <strong>GoJS</strong> normally runs completely in the browser, rendering to an HTML5 Canvas element or SVG without any server-side requirements. <strong>GoJS</strong> does not depend on any JavaScript libraries or frameworks, so it should work with any HTML or JavaScript framework or with no framework at all. &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</p>
<p>More at&nbsp;http://gojs.net/latest/index.html</p><p>Address of the bookmark: <a href="http://gojs.net/latest/index.html" rel="nofollow">http://gojs.net/latest/index.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44373/mitohifi-a-python-pipeline-for-mitochondrial-genome-assembly-from-pacbio-high-fidelity-reads</guid>
	<pubDate>Tue, 05 Sep 2023 07:31:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44373/mitohifi-a-python-pipeline-for-mitochondrial-genome-assembly-from-pacbio-high-fidelity-reads</link>
	<title><![CDATA[MitoHiFi: a python pipeline for mitochondrial genome assembly from PacBio high fidelity reads]]></title>
	<description><![CDATA[<p dir="auto">MitoHiFi v3.2 is a python pipeline distributed under&nbsp;<a href="https://github.com/marcelauliano/MitoHiFi/blob/master/LICENSE">MIT License</a>&nbsp;!</p>
<p dir="auto">MitoHiFi was first developed to assemble the mitogenomes for a wide range of species in the Darwin Tree of Life Project (DToL)</p>
<p dir="auto">https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-023-05385-y&nbsp;</p>
<p dir="auto"><a href="https://github.com/marcelauliano/MitoHiFi/blob/master/docs/dtol-logo-round-300x132.png" target="_blank"><img src="https://github.com/marcelauliano/MitoHiFi/raw/master/docs/dtol-logo-round-300x132.png" alt="" style="border: 0px; border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/marcelauliano/MitoHiFi" rel="nofollow">https://github.com/marcelauliano/MitoHiFi</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44768/tritex-a-computational-pipeline-for-chromosome-scale-assembly-of-plant-genomes</guid>
	<pubDate>Fri, 14 Feb 2025 10:53:48 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44768/tritex-a-computational-pipeline-for-chromosome-scale-assembly-of-plant-genomes</link>
	<title><![CDATA[TRITEX, a computational pipeline for chromosome-scale assembly of plant genomes]]></title>
	<description><![CDATA[<p><span>This is the documentation of TRITEX, a computational pipeline for chromosome-scale assembly of plant genomes. It was developed in the research group Domestication Genomics at the Leibniz Institute of Plant Genetics and Crop Research (IPK) Gatersleben.</span></p><p>Address of the bookmark: <a href="https://tritexassembly.bitbucket.io/" rel="nofollow">https://tritexassembly.bitbucket.io/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30168/gene-synteny-database</guid>
	<pubDate>Fri, 16 Dec 2016 11:09:39 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30168/gene-synteny-database</link>
	<title><![CDATA[Gene Synteny Database]]></title>
	<description><![CDATA[<p>Comparative genomics remains a pivotal strategy to study the evolution of gene organization, and this primacy is reinforced by the growing number of full genome sequences available in public repositories. Despite this growth, bioinformatic tools available to visualize and compare genomes and to infer evolutionary events remain restricted to two or three genomes at a time, thus limiting the breadth and the nature of the question that can be investigated. Here we present Genomicus, a new synteny browser that can represent and compare unlimited numbers of genomes in a broad phylogenetic view. In addition, Genomicus includes reconstructed ancestral gene organization, thus greatly facilitating the interpretation of the data.</p>
<p><strong>Availability:</strong>&nbsp;Genomicus is freely available for online use at&nbsp;<a href="http://www.dyogen.ens.fr/genomicus" target="pmc_ext">http://www.dyogen.ens.fr/genomicus</a>&nbsp;while data can be downloaded at&nbsp;<a href="ftp://ftp.biologie.ens.fr/pub/dyogen/genomicus" target="pmc_ext">ftp://ftp.biologie.ens.fr/pub/dyogen/genomicus</a></p>
<p><strong>Contact:</strong>&nbsp;<a href="mailto:dev@null">rf.sne.eigoloib@crh</a></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2853686/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2853686/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30355/meme-suite</guid>
	<pubDate>Fri, 23 Dec 2016 08:49:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30355/meme-suite</link>
	<title><![CDATA[MEME suite]]></title>
	<description><![CDATA[<p>Motif based sequence analysis suits&nbsp;</p>
<p>The MEME Suite allows the biologist to discover novel motifs in collections of unaligned nucleotide or protein sequences, and to perform a wide variety of other motif-based analyses.</p>
<p>The MEME Suite supports motif-based analysis of DNA, RNA and protein sequences. It provides motif discovery algorithms using both probabilistic (MEME) and discrete models (MEME), which have complementary strengths. It also allows discovery of motifs with arbitrary insertions and deletions (GLAM2). In addition to motif discovery, the MEME Suite provides tools for scanning sequences for matches to motifs (FIMO, MAST and GLAM2Scan), scanning for clusters of motifs (MCAST), comparing motifs to known motifs (Tomtom), finding preferred spacings between motifs (SpaMo), predicting the biological roles of motifs (GOMo), measuring the positional enrichment of sequences for known motifs (CentriMo), and analyzing ChIP-seq and other large datasets (MEME-ChIP).</p>
<p>The MEME Suite is comprised of a collection of tools that work together, as shown below. Not all the tools are available as webservices, so to get the full power of the MEME Suite you will need to&nbsp;<a href="http://meme-suite.org/doc/download.html">download</a>&nbsp;and&nbsp;<a href="http://meme-suite.org/doc/install.html">install</a>&nbsp;a local copy of the software. To see what has changed recently you can peruse the&nbsp;<a href="http://meme-suite.org/doc/release-notes.html">release notes</a>.</p>
<p>http://meme-suite.org/</p><p>Address of the bookmark: <a href="http://meme-suite.org/" rel="nofollow">http://meme-suite.org/</a></p>]]></description>
	<dc:creator>Bulbul</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/30744/binc-2017</guid>
	<pubDate>Wed, 01 Feb 2017 09:36:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/30744/binc-2017</link>
	<title><![CDATA[BINC 2017]]></title>
	<description><![CDATA[<p><span>Pondicherry University,Puducherry,on behalf of Department of Biotechnology, Government of India, conducted the BINC examination in&nbsp;</span><span style="color: blue;">2015 and 2016.&nbsp;</span><span>The objective of this examination is to certify bioinformatics professionals, trained formally as well as self-trained.</span><span style="color: blue;">Registration for BINC 2017 examination will open from January 29,2017 to February 28,2017.</span><span>&nbsp;</span></p><p><span>Pondicherry University, Puducherry has been identified as a nodal agency by the Department of Biotechnology, Govt. of India to coordinate this examination along with nine centres namely, </span></p><p><span>Pune University, Pune; </span></p><p><span>Anna University, Chennai; </span></p><p><span>Bose Institute, Kolkata; </span></p><p><span>Institute of Bioinformatics &amp; Applied Biotechnology, Bangalore; </span></p><p><span>North-Eastern Hill University, Shillong, University of Hyderabad, Hyderabad; </span></p><p><span>University of Kerala, Thiruvananthapuram; </span></p><p><span>Jawaharlal Nehru University, New Delhi and </span></p><p><span>Assam Agricultural University, Guwahati.</span><span style="color: blue;"><strong>&nbsp;</strong></span></p><p><span style="color: blue;"><strong>In the BINC 2015 and 2016 examination, 23 candidates and five candidates were certified respectively.</strong></span><span>&nbsp;DBT has agreed to fund Research fellowships for all the BINC qualified Indian nationals to pursue Ph.D. in Indian Institutes/Universities. </span></p><p><span>Note that the candidate must possess a postgraduate degree(or equivalent) &amp; meet the criteria of the institutes/universities in order to avail research fellowship. </span></p><p><span>In addition, cash prize of Rs. 10,000/- will be awarded to the top 10 BINC qualifiers.</span></p><p><span>More at&nbsp;http://www.pondiuni.edu.in/exams/binc/</span></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30831/fsa-fast-statistical-alignment</guid>
	<pubDate>Mon, 06 Feb 2017 04:26:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30831/fsa-fast-statistical-alignment</link>
	<title><![CDATA[FSA: Fast Statistical Alignment]]></title>
	<description><![CDATA[<p><span>FSA is a probabilistic multiple sequence alignment algorithm which uses a "distance-based" approach to aligning homologous protein, RNA or DNA sequences. Much as distance-based phylogenetic reconstruction methods like Neighbor-Joining build a phylogeny using only pairwise divergence estimates, FSA builds a multiple alignment using only pairwise estimations of homology. This is made possible by the sequence annealing technique for constructing a multiple alignment from pairwise comparisons, developed by Ariel Schwartz in&nbsp;</span><a href="http://www.eecs.berkeley.edu/Pubs/TechRpts/2007/EECS-2007-39.html">"Posterior Decoding Methods for Optimization and Control of Multiple Alignments</a><span>."</span></p>
<p>FSA brings the high accuracies previously available only for small-scale analyses of proteins or RNAs to large-scale problems such as aligning thousands of sequences or megabase-long sequences. FSA introduces several novel methods for constructing better alignments:</p>
<ul>
<li>FSA uses machine-learning techniques to estimate gap and substitution parameters on the fly for each set of input sequences. This "query-specific learning" alignment method makes FSA very robust: it can produce superior alignments of sets of homologous sequences which are subject to very different evolutionary constraints.</li>
<li>FSA is capable of aligning hundreds or even thousands of sequences using a randomized inference algorithm to reduce the computational cost of multiple alignment. This randomized inference can be over ten times faster than a direct approach with little loss of accuracy.</li>
<li>FSA can quickly align very long sequences using the "anchor annealing" technique for resolving anchors and projecting them with transitive anchoring. It then stitches together the alignment between the anchors using the methods described above.</li>
<li>The included GUI, MAD (Multiple Alignment Display), can display the intermediate alignments produced by FSA, where each character is colored according to the probability that it is correctly aligned (see the picture and&nbsp;<a href="http://fsa.sourceforge.net/images/Suchard_SIV.fsa.mov">movie</a>&nbsp;at the top of the page).</li>
</ul>
<p><span>You can see more information on the&nbsp;</span><a href="http://fsa.sourceforge.net/FAQ.html">FAQ</a><span>.&nbsp;</span></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://fsa.sourceforge.net/" rel="nofollow">http://fsa.sourceforge.net/</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>
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	<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>
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