<?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/33306?offset=60</link>
	<atom:link href="https://bioinformaticsonline.com/related/33306?offset=60" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34704/nanosim-nanopore-sequence-read-simulator-based-on-statistical-characterization</guid>
	<pubDate>Mon, 18 Dec 2017 04:16:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34704/nanosim-nanopore-sequence-read-simulator-based-on-statistical-characterization</link>
	<title><![CDATA[NanoSim: nanopore sequence read simulator based on statistical characterization.]]></title>
	<description><![CDATA[<p><span>NanoSim, a fast and scalable read simulator that captures the technology-specific features of ONT data and allows for adjustments upon improvement of nanopore sequencing technology. The first step of NanoSim is read characterization, which provides a comprehensive alignment-based analysis and generates a set of read profiles serving as the input to the next step, the simulation stage. The simulation stage uses the model built in the previous step to produce in silico reads for a given reference genome. NanoSim is written in Python and R. The source files and manual are available at the Genome Sciences Centre website: http://www.bcgsc.ca/platform/bioinfo/software/nanosim</span></p>
<p><span>https://github.com/bcgsc/NanoSim</span></p><p>Address of the bookmark: <a href="http://www.bcgsc.ca/platform/bioinfo/software/nanosim" rel="nofollow">http://www.bcgsc.ca/platform/bioinfo/software/nanosim</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37672/seqmonka-tool-to-visualise-and-analyse-high-throughput-mapped-sequence-data</guid>
	<pubDate>Tue, 11 Sep 2018 04:39:38 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37672/seqmonka-tool-to-visualise-and-analyse-high-throughput-mapped-sequence-data</link>
	<title><![CDATA[SeqMonk:A tool to visualise and analyse high throughput mapped sequence data]]></title>
	<description><![CDATA[<p>SeqMonk is a program to enable the visualisation and analysis of mapped sequence data. It was written for use with mapped next generation sequence data but can in theory be used for any dataset which can be expressed as a series of genomic positions. It's main features are:</p>
<ul>
<li>Import of mapped data from mapped data (BAM/SAM/bowtie etc)</li>
<li>Creation of data groups for visualisation and analysis</li>
<li>Visualisation of mapped regions against an annotated genome.</li>
<li>Flexible quantitation of the mapped data to allow comparisons between data sets</li>
<li>Statistical analysis of data to find regions of interest</li>
<li>Creation of reports containing data and genome annotation</li>
</ul><p>Address of the bookmark: <a href="http://www.bioinformatics.babraham.ac.uk/projects/seqmonk/" rel="nofollow">http://www.bioinformatics.babraham.ac.uk/projects/seqmonk/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38441/genome-sequence-based-sub-species-delineation</guid>
	<pubDate>Wed, 12 Dec 2018 08:31:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38441/genome-sequence-based-sub-species-delineation</link>
	<title><![CDATA[Genome sequence-based (sub-)species delineation.]]></title>
	<description><![CDATA[<p>The GGDC web service reports digital DDH for a universal and accurate delineation of prokaryotic (sub-)species without inheriting the pitfalls of classic DDH, and also calculates differences in genomic G+C content.</p>
<p>http://ggdc.dsmz.de/ggdc_background.php#</p>
<p><small>Genome-to-Genome Distance Calculator 2.1</small></p>
<p>http://ggdc.dsmz.de/ggdc.php</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://ggdc.dsmz.de/" rel="nofollow">http://ggdc.dsmz.de/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39856/tritex-sequence-assembly-pipeline-for-triticeae-genomes</guid>
	<pubDate>Tue, 20 Aug 2019 09:47:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39856/tritex-sequence-assembly-pipeline-for-triticeae-genomes</link>
	<title><![CDATA[TRITEX sequence assembly pipeline for Triticeae genomes]]></title>
	<description><![CDATA[<div>
<p>The pipeline is open-source and hosted in a public Bitbucket&nbsp;<a href="https://bitbucket.org/tritexassembly/tritexassembly.bitbucket.io/src/master/">repository</a>.</p>
</div>
<div>
<p>TRITEX has been run on highly inbred genotypes of barley (<em>Hordeum vulgare</em>), tetraploid wheat (<em>Triticum turgidum</em>) and hexaploid wheat (<em>T. aestivum</em>) with reasonable results: super-scaffold N50 values in the range of dozens of Mb and pseudomolecules with better gene space representation than a BAC-by-BAC assembly. It has never been tested and is not expected to work on heterozygous or autopolyploid genomes.</p>
</div>
<div>
<p>A protocol for generating chromosome-conformation capture sequencing (Hi-C) data suitable for use with the pipeline is described in&nbsp;<a href="https://bio-protocol.org/e2955">Himmelbach et al. 2018</a>. Refer to the&nbsp;<a href="https://www.10xgenomics.com/resources/technical-notes/">technical notes</a>&nbsp;of 10X Genomics on how to generate Chromium data.</p>
</div><p>Address of the bookmark: <a href="https://tritexassembly.bitbucket.io/" rel="nofollow">https://tritexassembly.bitbucket.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40217/shouji-a-fast-and-efficient-pre-alignment-filter-for-sequence-alignment</guid>
	<pubDate>Mon, 04 Nov 2019 07:09:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40217/shouji-a-fast-and-efficient-pre-alignment-filter-for-sequence-alignment</link>
	<title><![CDATA[Shouji: a fast and efficient pre-alignment filter for sequence alignment]]></title>
	<description><![CDATA[<p>The ability to generate massive amounts of sequencing data continues to overwhelm the processing capacity of existing algorithms and compute infrastructures. In this work, we explore the use of hardware/software co-design and hardware acceleration to significantly reduce the execution time of short sequence alignment, a crucial step in analyzing sequenced genomes.</p>
<p>&nbsp;<img src="https://github.com/BilkentCompGen/Shoji/raw/master/Figure1-GitHub.png" alt="image" style="border: 0px;"></p>
<p>We introduce Shouji, a highly parallel and accurate pre-alignment filter that remarkably reduces the need for computationally-costly dynamic programming algorithms. The first key idea of our proposed pre-alignment filter is to provide high filtering accuracy by correctly detecting all common subsequences shared between two given sequences. The second key idea is to design a hardware accelerator design that adopts modern FPGA (field-programmable gate array) architectures to further boost the performance of our algorithm.</p>
<p>More at <a href="https://github.com/CMU-SAFARI/Shouji">https://github.com/CMU-SAFARI/Shouji</a></p><p>Address of the bookmark: <a href="https://github.com/CMU-SAFARI/Shouji" rel="nofollow">https://github.com/CMU-SAFARI/Shouji</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40814/accesssyri-finding-genomic-rearrangements-and-local-sequence-differences-from-whole-genome-assemblies</guid>
	<pubDate>Sat, 01 Feb 2020 13:38:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40814/accesssyri-finding-genomic-rearrangements-and-local-sequence-differences-from-whole-genome-assemblies</link>
	<title><![CDATA[AccessSyRI: finding genomic rearrangements and local sequence differences from whole-genome assemblies]]></title>
	<description><![CDATA[<p><span>Access</span><span>SyRI: finding genomic rearrangements and</span><span>local sequence differences from whole-</span><span>genome assemblies</span><span><br></span></p>
<p><span><span>SyRI, a pairwise whole-genome comparison tool for chromosome-level assemblies. SyRI starts by finding rearranged regions and then searches for differences in the sequences, which are distinguished for residing in syntenic or rearranged regions. This distinction is important as rearranged regions are inherited differently compared to syntenic regions.</span></span></p>
<p><span><a href="https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1911-0">https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1911-0</a></span></p><p>Address of the bookmark: <a href="https://github.com/schneebergerlab/syri" rel="nofollow">https://github.com/schneebergerlab/syri</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/41562/submit-your-sars-cov-2-sequence-data-to-genbank</guid>
	<pubDate>Thu, 09 Apr 2020 18:28:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/41562/submit-your-sars-cov-2-sequence-data-to-genbank</link>
	<title><![CDATA[Submit your SARS-CoV-2 sequence data to GenBank]]></title>
	<description><![CDATA[<div dir="auto">Submit your SARS-CoV-2 sequence data to GenBank and SRA with our new submission landing page. Submission is simple and streamlined *and* there&rsquo;s a rapid turnaround. <span><a href="https://l.facebook.com/l.php?u=https%3A%2F%2Fsubmit.ncbi.nlm.nih.gov%2Fsarscov2%2F%3Ffbclid%3DIwAR3p-OzZPe2yx4CZMoZxiWMF3kUQjXyVVduNQhBdehWmFTJ3cPBstsOLypI&amp;h=AT2d-umit7ciXRW-nrRYVL3gJSLKY4Hte8W8cXw8Wl94n6PGmoHmVqvvhgQj-mTo6A5lpMP9JDV_lRSq9RRLT5KeVVAAfcuRgJOeA6QhApIB2B9nFxUfDCD3sio4HYidpRwpmng&amp;__tn__=-UK-R&amp;c[0]=AT2zWGa1K5EvV4UcnB0b7HHvkBtX-wAyh7AF8_fZ9uI2y-02nOHQHT_Um3xgnto5KEZ26wRG0xNgUWTA1W-7HF0E25E23XtIL5XGOhloBXaDIcHw30AVjTCkQi7aFk4dN7aBCmVJeSbH37urtbM2kmMfyTCbdTvMU8FGlnX-DNVuCaZr4XfXnf_jvPNdxe9sBH84oXJ-uJz5kbqlHGAHDoqK" target="_blank">https://submit.ncbi.nlm.nih.gov/sarscov2/</a></span></div><div dir="auto">&nbsp;</div><div dir="auto"><span><span>Quickly and easily add your SARS-CoV-2 sequence data to the growing public archive with new, special features and support from NCBI. </span><a href="https://submit.ncbi.nlm.nih.gov/sarscov2/">new SARS-CoV-2 sequence submission landing page</a><span>&nbsp;will help you get started. GenBank submissions are accessioned and released in approximately 1-2 working days, and&nbsp;</span><a href="https://www.ncbi.nlm.nih.gov/sra" target="_blank">Sequence Read Archive</a><span>&nbsp;(SRA) submissions typically processed and released within hours. Submission is simple!</span></span></div><div><div dir="auto">&nbsp;</div><div dir="auto">More information is available on NCBI Insights. <span><a href="https://l.facebook.com/l.php?u=https%3A%2F%2Fncbiinsights.ncbi.nlm.nih.gov%2F2020%2F04%2F09%2Fsars-cov2-data-streamlined-submission-rapid-turnaround%2F%3Ffbclid%3DIwAR1OuLu3oDjz3VX4fDq5Jg316td9foTOUGNqnoN1eI2nFXTf4EBv28JiXD4&amp;h=AT0ah_epxwAc-nM6QiPBYvKSQ-kWmiPgHKO1w7SnxnnRiTI4etJJfNAWyzcR7snIdtxtcErAFRdHPBH2j0EY77gUPDdnBVnAsxnVbSgZnrrOPfnni331A37Xvytgnye0ArnUuWk&amp;__tn__=-UK-R&amp;c[0]=AT2zWGa1K5EvV4UcnB0b7HHvkBtX-wAyh7AF8_fZ9uI2y-02nOHQHT_Um3xgnto5KEZ26wRG0xNgUWTA1W-7HF0E25E23XtIL5XGOhloBXaDIcHw30AVjTCkQi7aFk4dN7aBCmVJeSbH37urtbM2kmMfyTCbdTvMU8FGlnX-DNVuCaZr4XfXnf_jvPNdxe9sBH84oXJ-uJz5kbqlHGAHDoqK" target="_blank">https://ncbiinsights.ncbi.nlm.nih.gov/2020/04/09/sars-cov2-data-streamlined-submission-rapid-turnaround/</a></span></div></div>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42645/mmseqs2-ultra-fast-and-sensitive-sequence-search-and-clustering-suite</guid>
	<pubDate>Mon, 18 Jan 2021 10:47:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42645/mmseqs2-ultra-fast-and-sensitive-sequence-search-and-clustering-suite</link>
	<title><![CDATA[MMseqs2: ultra fast and sensitive sequence search and clustering suite]]></title>
	<description><![CDATA[<p><span>MMseqs2 (Many-against-Many sequence searching) is a software suite to search and cluster huge protein and nucleotide sequence sets. MMseqs2 is open source GPL-licensed software implemented in C++ for Linux, MacOS, and (as beta version, via cygwin) Windows. The software is designed to run on multiple cores and servers and exhibits very good scalability. MMseqs2 can run 10000 times faster than BLAST. At 100 times its speed it achieves almost the same sensitivity. It can perform profile searches with the same sensitivity as PSI-BLAST at over 400 times its speed.</span></p><p>Address of the bookmark: <a href="https://github.com/soedinglab/MMseqs2" rel="nofollow">https://github.com/soedinglab/MMseqs2</a></p>]]></description>
	<dc:creator>Manisha Mishra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43846/the-complete-sequence-of-a-human-genome</guid>
	<pubDate>Thu, 31 Mar 2022 23:58:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43846/the-complete-sequence-of-a-human-genome</link>
	<title><![CDATA[The complete sequence of a human genome]]></title>
	<description><![CDATA[<p><span>The completed regions include all centromeric satellite arrays, recent segmental duplications, and the short arms of all five acrocentric chromosomes, unlocking these complex regions of the genome to variational and functional studies.</span></p><p>Address of the bookmark: <a href="https://www.science.org/doi/10.1126/science.abj6987" rel="nofollow">https://www.science.org/doi/10.1126/science.abj6987</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44904/termal-a-fast-and-interactive-terminal-based-viewer-for-multiple-sequence-alignments</guid>
	<pubDate>Mon, 22 Sep 2025 23:51:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44904/termal-a-fast-and-interactive-terminal-based-viewer-for-multiple-sequence-alignments</link>
	<title><![CDATA[Termal: a fast and interactive terminal-based viewer for multiple sequence alignments]]></title>
	<description><![CDATA[<p>termal, a fast, interactive, terminal-based viewer for multiple sequence alignments (MSAs), designed for use on remote systems such as high-performance computing (HPC) clusters.</p>
<p>https://academic.oup.com/bioinformaticsadvances/advance-article/doi/10.1093/bioadv/vbaf208/8257678?login=true</p><p>Address of the bookmark: <a href="https://github.com/sib-swiss/termal" rel="nofollow">https://github.com/sib-swiss/termal</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

</channel>
</rss>