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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/33960?offset=330</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44902/hite-a-fast-and-accurate-dynamic-boundary-adjustment-approach-for-full-length-transposable-elements-detection-and-annotation-in-genome-assemblies</guid>
	<pubDate>Sat, 20 Sep 2025 09:34:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44902/hite-a-fast-and-accurate-dynamic-boundary-adjustment-approach-for-full-length-transposable-elements-detection-and-annotation-in-genome-assemblies</link>
	<title><![CDATA[HiTE: a fast and accurate dynamic boundary adjustment approach for full-length Transposable Elements detection and annotation in Genome Assemblies]]></title>
	<description><![CDATA[<p dir="auto"><code>HiTE</code>&nbsp;is a Python software that uses a dynamic boundary adjustment approach to detect and annotate full-length Transposable Elements in Genome Assemblies. In comparison to other tools, HiTE demonstrates superior performance in detecting a greater number of full-length TEs.</p>
<div dir="auto">
<h2 dir="auto">panHiTE</h2>
<a href="https://github.com/CSU-KangHu/HiTE#panhite"></a></div>
<p dir="auto">We have developed panHiTE, a comprehensive and accurate pipeline for TE detection in large-scale population genomes. It has been successfully applied to hundreds of plant population genomes, demonstrating its effectiveness and scalability.</p>
<p dir="auto">For detailed instructions, please refer to the&nbsp;<a href="https://github.com/CSU-KangHu/HiTE/wiki/panHiTE-tutorial">panHiTE tutorial</a>.</p><p>Address of the bookmark: <a href="https://github.com/CSU-KangHu/HiTE" rel="nofollow">https://github.com/CSU-KangHu/HiTE</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36111/d3networktools-for-creating-d3-javascript-network-tree-dendrogram-and-sankey-graphs-from-r</guid>
	<pubDate>Fri, 06 Apr 2018 12:10:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36111/d3networktools-for-creating-d3-javascript-network-tree-dendrogram-and-sankey-graphs-from-r</link>
	<title><![CDATA[d3Network:Tools for creating D3 JavaScript network, tree, dendrogram, and Sankey graphs from R.]]></title>
	<description><![CDATA[<p><a href="http://bost.ocks.org/mike/">Mike Bostock</a><span>&rsquo;s&nbsp;</span><a href="http://d3js.org/">D3.js</a><span>&nbsp;is great for creating&nbsp;</span><a href="http://bl.ocks.org/mbostock/4062045">interactive network graphs</a><span>&nbsp;with JavaScript. The&nbsp;</span><a href="https://github.com/christophergandrud/d3Network">d3Network</a><span>&nbsp;package makes it easy to create these network graphs from&nbsp;</span><a href="http://www.r-project.org/">R</a><span>. The main idea is that you should able to take an R data frame with information about the relationships between members of a network and create full network graphs with one command.</span></p><p>Address of the bookmark: <a href="http://christophergandrud.github.io/d3Network/" rel="nofollow">http://christophergandrud.github.io/d3Network/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36720/dupcar-reconstructing-contiguous-ancestral-regions-with-duplications</guid>
	<pubDate>Mon, 21 May 2018 11:09:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36720/dupcar-reconstructing-contiguous-ancestral-regions-with-duplications</link>
	<title><![CDATA[DUPCAR: Reconstructing Contiguous Ancestral Regions with Duplications]]></title>
	<description><![CDATA[we propose a heuristic algorithm, called DUPCAR, for reconstructing ancestral genomic orders with duplications. The method starts from the order of genes in modern genomes and predicts predecessor and successor relationships in the ancestor. Then a greedy algorithm is used to reconstruct the ancestral orders by connecting genes into contiguous regions based on predicted adjacencies. Computer simulation was used to validate the algorithm. We also applied the method to reconstruct the ancestral chromosome X of placental mammals and the ancestral genomes of the ciliate Paramecium tetraurelia.<p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3205822/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3205822/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/26456/the-mills-lab</guid>
  <pubDate>Wed, 24 Feb 2016 16:18:38 -0600</pubDate>
  <link></link>
  <title><![CDATA[The Mills lab]]></title>
  <description><![CDATA[
<p>The laboratory is focused on the discovery and analysis of structural variation (SVs) from genomic sequence data. As part of the 1000 Genomes Project and other endeavors, we have helped produce initial fine-scale maps using a variety of SV discovery approaches including: (i) paired-end mapping (or read pair analysis) based on abnormally mapped pairs of clone ends; (ii) read-depth analysis, which detects deletions and duplications through analysis of the read depth-of-coverage; (iii) split read analysis, which detects SVs by evaluating gapped sequence alignments; and (iv) sequence assembly, which enables the discovery of novel (non-reference) sequence insertions.</p>

<p>http://millslab.org/research.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44219/chromosome-breakpoint-a-breakup-to-remember</guid>
	<pubDate>Tue, 07 Mar 2023 13:31:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44219/chromosome-breakpoint-a-breakup-to-remember</link>
	<title><![CDATA[Chromosome breakpoint - a breakup to remember]]></title>
	<description><![CDATA[<div><div><div><div><div><div><div><div><div><div><p>Chromosome breakpoint refers to the physical location where a chromosome is broken and rearranged. Chromosome breakage can occur spontaneously or be induced by environmental factors such as radiation, chemicals, or viruses. The rearrangement of genetic material resulting from a chromosome breakpoint can have important consequences, including the development of genetic diseases, chromosomal abnormalities, or cancer.</p><p>Chromosome breakpoints can occur in two ways: interstitial or terminal. Interstitial breakpoints occur within the chromosome, while terminal breakpoints occur at the end of the chromosome. Terminal breakpoints can lead to the loss of genetic material, whereas interstitial breakpoints can result in the duplication or deletion of genetic material.</p><p>Chromosome breakpoints can be detected using a variety of techniques, including cytogenetic analysis, fluorescence in situ hybridization (FISH), and molecular methods such as polymerase chain reaction (PCR) and next-generation sequencing (NGS). These techniques can also help identify the exact location of the breakpoint and the nature of the rearrangement, such as translocations, inversions, deletions, or duplications.</p><p>Translocations are one of the most common types of chromosome rearrangements caused by breakpoints. In a translocation, genetic material is exchanged between two different chromosomes, resulting in a balanced or unbalanced distribution of genetic material. Unbalanced translocations can cause genetic diseases or developmental abnormalities, while balanced translocations can be inherited without any apparent phenotypic effects.</p><p>Inversions occur when a chromosome segment is inverted, resulting in a change in the order of genetic material. Inversions can be pericentric, involving the centromere, or paracentric, not involving the centromere. Inversions can cause genetic diseases or phenotypic effects if they disrupt the function of essential genes or regulatory elements.</p><p>Deletions and duplications are caused by interstitial breakpoints that result in the loss or gain of genetic material. Deletions can cause genetic diseases or developmental abnormalities if they involve essential genes or regulatory elements. Duplications can also have phenotypic effects, depending on the location and size of the duplicated segment.</p><p>Chromosome breakpoints can also be involved in the formation of complex chromosomal rearrangements, such as ring chromosomes or dicentric chromosomes. These complex rearrangements can have important clinical implications, as they can cause genetic diseases or cancer.</p><p>In conclusion, chromosome breakpoints are important genetic events that can lead to the rearrangement of genetic material and have important clinical implications. The detection and characterization of chromosome breakpoints using cytogenetic, molecular, and genomic methods are essential for the diagnosis, prognosis, and treatment of genetic diseases and cancer. Further research is needed to understand the molecular mechanisms underlying chromosome breakage and to develop new therapies targeting these events.</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/33976/goldgenomes-online-database</guid>
	<pubDate>Wed, 26 Jul 2017 07:49:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33976/goldgenomes-online-database</link>
	<title><![CDATA[GOLD:Genomes Online Database]]></title>
	<description><![CDATA[<p><span>GOLD</span><span>:Genomes Online Database, is a World Wide Web resource for comprehensive access to information regarding genome and metagenome sequencing projects, and their associated metadata, around the world.</span></p>
<p>https://gold.jgi.doe.gov/</p><p>Address of the bookmark: <a href="https://gold.jgi.doe.gov/" rel="nofollow">https://gold.jgi.doe.gov/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34413/coursera-genome-assembly-tutorial</guid>
	<pubDate>Sat, 25 Nov 2017 08:57:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34413/coursera-genome-assembly-tutorial</link>
	<title><![CDATA[coursera genome assembly tutorial]]></title>
	<description><![CDATA[<p><span>Solutions to Coursera Genome Sequencing (Bioinformatics II)</span></p><p>Address of the bookmark: <a href="https://github.com/iansealy/coursera-assembly" rel="nofollow">https://github.com/iansealy/coursera-assembly</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34519/bandage-interactive-visualization-of-de-novo-genome-assemblies</guid>
	<pubDate>Mon, 04 Dec 2017 10:09:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34519/bandage-interactive-visualization-of-de-novo-genome-assemblies</link>
	<title><![CDATA[Bandage: interactive visualization of de novo genome assemblies]]></title>
	<description><![CDATA[<p>Bandage (a Bioinformatics Application for Navigating&nbsp;<em>De&nbsp;novo</em>&nbsp;Assembly Graphs Easily) is a tool for visualizing assembly graphs with connections. Users can zoom in to specific areas of the graph and interact with it by moving nodes, adding labels, changing colors and extracting sequences. BLAST searches can be performed within the Bandage graphical user interface and the hits are displayed as highlights in the graph. By displaying connections between contigs, Bandage presents new possibilities for analyzing&nbsp;<em>de novo</em>&nbsp;assemblies that are not possible through investigation of contigs alone.</p>
<p><strong>Availability and implementation:</strong>&nbsp;Source code and binaries are freely available at&nbsp;<a href="https://github.com/rrwick/Bandage" target="pmc_ext">https://github.com/rrwick/Bandage</a>. Bandage is implemented in C++ and supported on Linux, OS X and Windows. A full feature list and screenshots are available at&nbsp;<a href="http://rrwick.github.io/Bandage" target="pmc_ext">http://rrwick.github.io/Bandage</a>.</p><p>Address of the bookmark: <a href="http://rrwick.github.io/Bandage/" rel="nofollow">http://rrwick.github.io/Bandage/</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34571/mugsy-multiple-whole-genome-alignment-tool</guid>
	<pubDate>Fri, 08 Dec 2017 17:41:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34571/mugsy-multiple-whole-genome-alignment-tool</link>
	<title><![CDATA[Mugsy: multiple whole genome alignment tool]]></title>
	<description><![CDATA[<p><span>Mugsy is a multiple whole genome aligner. Mugsy uses Nucmer for pairwise alignment, a custom graph based segmentation procedure for identifying collinear regions, and the segment-based progressive multiple alignment strategy from Seqan::TCoffee. Mugsy accepts draft genomes in the form of multi-FASTA files and does not require a reference genome.</span></p>
<p>To cite Mugsy, use:</p>
<p>Angiuoli SV and Salzberg SL.&nbsp;<a href="http://bioinformatics.oxfordjournals.org/content/27/3/334">Mugsy: Fast multiple alignment of closely related whole genomes.</a><em>Bioinformatics</em>&nbsp;2011 27(3):334-4</p><p>Address of the bookmark: <a href="http://mugsy.sourceforge.net/" rel="nofollow">http://mugsy.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34715/delta-a-new-web-based-3d-genome-visualization-and-analysis-platform</guid>
	<pubDate>Wed, 20 Dec 2017 08:49:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34715/delta-a-new-web-based-3d-genome-visualization-and-analysis-platform</link>
	<title><![CDATA[Delta: a new Web-based 3D genome visualization and analysis platform]]></title>
	<description><![CDATA[<p><em>Delta</em><span>&nbsp;is an integrative visualization and analysis platform to facilitate visually annotating and exploring the 3D physical architecture of genomes.&nbsp;</span><em>Delta</em><span>&nbsp;takes Hi-C or ChIA-PET contact matrix as input and predicts the topologically associating domains and chromatin loops in the genome. It then generates a physical 3D model which represents the plausible consensus 3D structure of the genome.&nbsp;</span><em>Delta</em><span>features a highly interactive visualization tool which enhances the integration of genome topology/physical structure with extensive genome annotation by juxtaposing the 3D model with diverse genomic assay outputs.</span></p>
<p>https://github.com/zhangzhwlab/delta</p><p>Address of the bookmark: <a href="https://github.com/zhangzhwlab/delta" rel="nofollow">https://github.com/zhangzhwlab/delta</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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