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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37606?offset=50</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44641/heliano-a-fast-and-accurate-tool-for-detection-of-helitron-like-elements</guid>
	<pubDate>Tue, 13 Aug 2024 07:16:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44641/heliano-a-fast-and-accurate-tool-for-detection-of-helitron-like-elements</link>
	<title><![CDATA[HELIANO: A fast and accurate tool for detection of Helitron-like elements]]></title>
	<description><![CDATA[<p><span>Helitron-like elements (HLE1 and HLE2) are DNA transposons. They have been found in diverse species and seem to play significant roles in the evolution of host genomes. Although known for over twenty years, Helitron sequences are still challenging to identify. Here, we propose HELIANO (Helitron-like elements annotator) as an efficient solution for detecting Helitron-like elements.</span></p>
<p>https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkae679/7730539?login=true</p><p>Address of the bookmark: <a href="https://github.com/Zhenlisme/heliano/" rel="nofollow">https://github.com/Zhenlisme/heliano/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33942/mulan-multiple-sequence-local-alignment-and-conservation-visualization-tool</guid>
	<pubDate>Thu, 20 Jul 2017 08:02:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33942/mulan-multiple-sequence-local-alignment-and-conservation-visualization-tool</link>
	<title><![CDATA[Mulan: MUltiple sequence Local AligNment and conservation visualization tool]]></title>
	<description><![CDATA[<p><span>Mulan performs multiple (2 or more) sequence alignments with an efficient and rapid "full local" alignment strategy that ensures a recapitulation of evolutionary sequence rearrangements (such as inversions and reshuffling) in any of the species. It combines&nbsp;</span><a href="http://www.bx.psu.edu/miller_lab/" target="_new"><em>refine</em>&nbsp;and&nbsp;<em>tba</em></a><span>&nbsp;tools to align either "draft" or "finished" quality sequences. Mulan provides a dynamic graphical interface to align and visualize conservation profiles for evolutionarily distant and closely related species.</span><br><span></span></p>
<p><span>Input formats, automated data upload from the&nbsp;</span><a href="http://genome.ucsc.edu/" target="_new">UCSC Genome Browser</a><span>, gene annotation, annotation of repetitive elements, and progress report were previously described in the&nbsp;</span><a href="https://zpicture.dcode.org/zpInstructions.html" target="_zp">zPicture instructions</a><span>&nbsp;and we refer the users to these materials for more details. This introduction is mainly focused on some novel features unique to the Mulan.</span><span><br></span></p><p>Address of the bookmark: <a href="https://mulan.dcode.org/mulanInstructions.php" rel="nofollow">https://mulan.dcode.org/mulanInstructions.php</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44616/basics-of-blast-programs</guid>
	<pubDate>Fri, 26 Jul 2024 06:04:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44616/basics-of-blast-programs</link>
	<title><![CDATA[Basics of BLAST Programs !]]></title>
	<description><![CDATA[<p>The Basic Local Alignment Search Tool (BLAST) is a powerful bioinformatics program used to compare an input sequence (such as DNA, RNA, or protein sequences) against a database of sequences to find regions of similarity. Developed by the National Center for Biotechnology Information (NCBI), BLAST is widely used for identifying species, finding functional and evolutionary relationships between sequences, and predicting the function of novel sequences.</p><p>Key Features of BLAST:<br />1. Sequence Comparison: BLAST searches for local alignments between the query sequence and sequences in a database. It identifies regions of similarity, which can help infer functional and evolutionary relationships.</p><p>2. Speed and Efficiency: BLAST uses heuristic algorithms, making it faster than exhaustive search methods, suitable for large-scale database searches.</p><p>3. Versatility: There are several versions of BLAST for different types of sequence comparisons:<br /> - blastn: Compares a nucleotide query sequence against a nucleotide sequence database.<br /> - blastp: Compares a protein query sequence against a protein sequence database.<br /> - blastx: Compares a nucleotide query sequence translated in all reading frames against a protein sequence database.<br /> - tblastn: Compares a protein query sequence against a nucleotide sequence database translated in all reading frames.<br /> - tblastx: Compares the six-frame translations of a nucleotide query sequence against the six-frame translations of a nucleotide sequence database.</p><p>4. Scoring and E-value: BLAST results are scored based on the quality and length of the alignments. The E-value (expect value) indicates the number of alignments one can expect to find by chance, with lower E-values representing more significant matches.</p><p>5. Output Formats: BLAST provides results in various formats, including plain text, HTML, XML, and JSON, making it adaptable for different types of analyses and integrations with other tools.</p><p>Applications of BLAST:<br />- Genomic Research: Identifying genes, understanding genetic diversity, and mapping genome sequences.<br />- Protein Function Prediction: Inferring the function of unknown proteins by comparing them to known protein sequences.<br />- Evolutionary Studies: Exploring evolutionary relationships between organisms by comparing their genetic material.<br />- Medical Research: Identifying pathogens, understanding disease mechanisms, and developing treatments by comparing sequences of interest.</p><p>Overall, BLAST is an essential tool in bioinformatics, offering a reliable and efficient way to analyze and interpret biological sequence data.</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38755/svaba-genome-wide-detection-of-structural-variants-and-indels-by-local-assembly</guid>
	<pubDate>Mon, 21 Jan 2019 17:58:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38755/svaba-genome-wide-detection-of-structural-variants-and-indels-by-local-assembly</link>
	<title><![CDATA[SvABA: Genome-wide detection of structural variants and indels by local assembly]]></title>
	<description><![CDATA[<p><span>SvABA is a method for detecting structural variants in sequencing data using genome-wide local assembly. Under the hood, SvABA uses a custom implementation of&nbsp;</span><a href="https://github.com/jts/sga">SGA</a><span>&nbsp;(String Graph Assembler) by Jared Simpson, and&nbsp;</span><a href="https://github.com/lh3/bwa">BWA-MEM</a><span>&nbsp;by Heng Li. Contigs are assembled for every 25kb window (with some small overlap) for every region in the genome. The default is to use only clipped, discordant, unmapped and indel reads, although this can be customized to any set of reads at the command line using&nbsp;</span><a href="https://github.com/walaj/VariantBam">VariantBam</a><span>&nbsp;rules. These contigs are then immediately aligned to the reference with BWA-MEM and parsed to identify variants. Sequencing reads are then realigned to the contigs with BWA-MEM, and variants are scored by their read support.</span></p><p>Address of the bookmark: <a href="https://github.com/walaj/svaba" rel="nofollow">https://github.com/walaj/svaba</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39250/darwin-wga-a-co-processor-provides-increased-sensitivity-in-whole-genome-alignments-with-high-speedup</guid>
	<pubDate>Sat, 13 Apr 2019 08:55:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39250/darwin-wga-a-co-processor-provides-increased-sensitivity-in-whole-genome-alignments-with-high-speedup</link>
	<title><![CDATA[Darwin-WGA: A Co-processor Provides Increased Sensitivity in Whole Genome Alignments with High Speedup]]></title>
	<description><![CDATA[<p>Darwin-WGA, is the first hardware accelerator for whole genome alignment and accelerates the gapped filtering stage. Darwin-WGA also employs GACT-X, a novel algorithm used in the extension stage to align arbitrarily long genome sequences using a small on-chip memory, that provides better quality alignments at 2&times; improvement in memory and speed over the previously published GACT algorithm. Implemented on an FPGA, Darwin-WGA provides up to 24&times; improvement (performance/$) in WGA over iso-sensitive software.</p>
<p><a href="https://stanford.edu/~yatisht/pubs/darwin-wga.pdf">https://stanford.edu/~yatisht/pubs/darwin-wga.pdf</a></p><p>Address of the bookmark: <a href="https://github.com/gsneha26/Darwin-WGA" rel="nofollow">https://github.com/gsneha26/Darwin-WGA</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/35429/list-of-visualization-tools-for-genome-alignments</guid>
	<pubDate>Fri, 02 Feb 2018 13:25:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/35429/list-of-visualization-tools-for-genome-alignments</link>
	<title><![CDATA[List of visualization tools for genome alignments]]></title>
	<description><![CDATA[<p><span>Genome</span><span>&nbsp;browsers are useful not only for showing final results but also for improving analysis protocols, testing data quality, and generating result drafts. Its integration in analysis pipelines allows the optimization of parameters, which leads to better results. But sometime, we need publication ready figure of genomes. Following are the list of genome alignment visualization tools, which could be useful for analysis and&nbsp;interpretation of results:</span></p><p>ABySS Explorer</p><p>Interactive Java application that uses a novel graph-based representation to display a sequence assembly and associated metadata</p><p>http://www.bcgsc.ca/platform/bioinfo/software/abyss-explorer</p><p>BamView</p><p>Genome browser and annotation tool that allows visualization of sequence features, next-generation sequencing (NGS) data and the results of analyses within the context of the sequence, and also its six-frame translation</p><p>http://www.sanger.ac.uk/resources/software/artemis/</p><p>DNannotator&nbsp;</p><p>Annotation web toolkit for regional genomic sequences</p><p>http://bioapp.psych.uic.edu/DNannotator.htm</p><p>JVM&nbsp;</p><p>Java Visual Mapping tool for NGS reads</p><p>http://www.springer.com/cda/content/document/cda_downloaddocument/9789401792448-c2.pdf?SGWID=0-0-45-1487072-p176815501</p><p>LookSeq&nbsp;</p><p>Web-based visualization of sequences derived from multiple sequencing technologies. Low- or high-depth read pileups and easy visualization of putative single nucleotide and structural variation</p><p>http://lookseq.sourceforge.net</p><p>MagicViewer&nbsp;</p><p>Visualization of short read alignment, identification of genetic variation and association with annotation information of a reference genome</p><p>http://bioinformatics.zj.cn/magicviewer/</p><p>MapView&nbsp;</p><p>Alignments of huge-scale single-end and pair-end short reads</p><p>http://omictools.com/mapview-s1367.html</p><p>MultiPipMaker</p><p>Computes alignments of similar regions in two DNA sequences. The resulting alignments are summarized with a &lsquo;percent identity plot&rsquo; (pip)</p><p>http://pipmaker.bx.psu.edu/pipmaker/</p><p>PileLineGUI&nbsp;</p><p>Handling genome position files in NGS studies</p><p>http://sing.ei.uvigo.es/pileline/pilelinegui.html</p><p>SAMtools tview&nbsp;</p><p>Simple and fast text alignment viewer; NGS compatible</p><p>http://www.htslib.org/</p><p>SEWAL</p><p>Uses a locality-sensitive hashing algorithm to enumerate all unique sequences in an entire Illumina sequencing run</p><p>http://www.sourceforge.net/projects/sewal</p><p>STAR&nbsp;</p><p>A web-based integrated solution to management and visualization of sequencing data</p><p>http://wanglab.ucsd.edu/star/browser</p><p>SVA&nbsp;</p><p>Software for annotating and visualizing sequenced human genomes</p><p>http://www.svaproject.org</p><p>Viewer (IGV)&nbsp;</p><p>Visualization of large heterogeneous datasets, providing a smooth and intuitive user experience at all levels of genome resolution</p><p>https://www.broadinstitute.org/igv/</p><p>ZOOM Lite&nbsp;</p><p>NGS data mapping and visualization software</p><p>http://bioinfor.com/zoom/lite/</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38172/bamview-a-free-interactive-display-of-read-alignments-in-bam-data-files</guid>
	<pubDate>Fri, 09 Nov 2018 13:43:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38172/bamview-a-free-interactive-display-of-read-alignments-in-bam-data-files</link>
	<title><![CDATA[BamView: a free interactive display of read alignments in BAM data files]]></title>
	<description><![CDATA[<p>To run the application on UNIX from the downloaded jar file run the UNIX:</p>
<p><tt>java -mx512m -jar BamView.jar</tt></p>
<p>and extra command line options are given when '-h' is used:</p>
<p><tt>java -jar BamView.jar -h</tt></p>
<p>BAM files can be specified on the command line with the '-a' option:</p>
<p><tt>java -mx512m -jar BamView.jar -a pathToFile/sorted.bam</tt></p>
<p>If a BAM filename is not given on the command line BamView will prompt for a file to be entered. The BAM index file should have the same name as the BAM file but with a '.bai' suffix. Multiple BAM files can be loaded and overlaid in the viewer. To make this easier BamView will read in files that contain a list of filenames.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://bamview.sourceforge.net/" rel="nofollow">http://bamview.sourceforge.net/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44663/svbyeye-r-package-to-visualize-alignments-between-two-or-multiple-dna-sequences</guid>
	<pubDate>Tue, 17 Sep 2024 02:34:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44663/svbyeye-r-package-to-visualize-alignments-between-two-or-multiple-dna-sequences</link>
	<title><![CDATA[SVbyEye: R Package to visualize alignments between two or multiple DNA sequences]]></title>
	<description><![CDATA[<p dir="auto">R Package to visualize alignments between two or multiple DNA sequences including<br>a number of functionalities to facilitate processing of alignments in PAF format.</p>
<p dir="auto"><span>SVbyEye, an open-source R package to visualize and annotate sequence-to-sequence alignments along with various functionalities to process alignments in PAF format. The tool facilitates the characterization of complex SVs in the context of sequence homology helping resolve the mechanisms underlying their formation. Availability and implementation SVbyEye is available at https://github.com/daewoooo/SVbyEye.</span></p>
<p dir="auto">Author: David Porubsky</p><p>Address of the bookmark: <a href="https://github.com/daewoooo/SVbyEye" rel="nofollow">https://github.com/daewoooo/SVbyEye</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34565/fogsaa-fast-optimal-global-sequence-alignment-algorithm</guid>
	<pubDate>Fri, 08 Dec 2017 14:41:08 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34565/fogsaa-fast-optimal-global-sequence-alignment-algorithm</link>
	<title><![CDATA[FOGSAA: Fast Optimal Global Sequence Alignment Algorithm]]></title>
	<description><![CDATA[<p>Sequence alignment algorithms are widely used to infer similarirty and the point of differences between pair of sequences. FOGSAA is a fast Global alignment algorithm. It is basically a branch and bound approach which starts branch expansion in a greedy way taking the symbols from the given pair of sequences (protein or nucleotide) and results in an optimal alignment faster than conventional dymanic programming techniques. It is also better than the heuristic methods with respect to alignment quality.</p><p>Address of the bookmark: <a href="http://www.isical.ac.in/~bioinfo_miu/FOGSAA.htm" rel="nofollow">http://www.isical.ac.in/~bioinfo_miu/FOGSAA.htm</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39671/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads</guid>
	<pubDate>Sat, 06 Jul 2019 03:48:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39671/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads</link>
	<title><![CDATA[Flye: Fast and accurate de novo assembler for single molecule sequencing reads]]></title>
	<description><![CDATA[<p><span>Flye is a de novo assembler for single molecule sequencing reads, such as those produced by PacBio and Oxford Nanopore Technologies. It is designed for a wide range of datasets, from small bacterial projects to large mammalian-scale assemblies. The package represents a complete pipeline: it takes raw PB / ONT reads as input and outputs polished contigs. Flye also includes a special mode for metagenome assembly.</span></p><p>Address of the bookmark: <a href="https://github.com/fenderglass/Flye" rel="nofollow">https://github.com/fenderglass/Flye</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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