<?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/40208?offset=330</link>
	<atom:link href="https://bioinformaticsonline.com/related/40208?offset=330" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36950/salsa-a-tool-to-scaffold-long-read-assemblies-with-hi-c</guid>
	<pubDate>Fri, 15 Jun 2018 04:01:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36950/salsa-a-tool-to-scaffold-long-read-assemblies-with-hi-c</link>
	<title><![CDATA[SALSA: A tool to scaffold long read assemblies with Hi-C]]></title>
	<description><![CDATA[This code is used to scaffold your assemblies using Hi-C data. This version implements some improvements in the original SALSA algorithm. If you want to use the old version, it can be found in the old_salsa branch.

To use the latest version, first run the following commands:

  cd SALSA
  make
To run the code, you will need Python 2.7, BOOST libraries and Networkx(version lower than 1.2).

If you consider using this tool, please cite our publication which describes the methods used for scaffolding.

Ghurye, J., Pop, M., Koren, S., Bickhart, D., &amp; Chin, C. S. (2017). Scaffolding of long read assemblies using long range contact information. BMC genomics, 18(1), 527. Link

Ghurye, J., Rhie, A., Walenz, B.P., Schmitt, A., Selvaraj, S., Pop, M., Phillippy, A.M. and Koren, S., 2018. Integrating Hi-C links with assembly graphs for chromosome-scale assembly. bioRxiv, p.261149 Link

For any queries, please either ask on github issue page or send an email to Jay Ghurye (jayg@cs.umd.edu).<p>Address of the bookmark: <a href="https://github.com/machinegun/SALSA" rel="nofollow">https://github.com/machinegun/SALSA</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/news/view/39217/caulobacter-ethensis-20-computer-generated-genome-of-a-living-organism</guid>
	<pubDate>Wed, 03 Apr 2019 08:45:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/39217/caulobacter-ethensis-20-computer-generated-genome-of-a-living-organism</link>
	<title><![CDATA[Caulobacter ethensis - 2.0 : Computer-generated Genome of a Living Organism]]></title>
	<description><![CDATA[<div><span>All the genome sequences of organisms known throughout the world are stored in a database belonging to the National Center for Biotechnology Information in the United States. As of today, the database has an additional entry:&nbsp;<em><strong><span>Caulobacter ethensis</span></strong></em><span><strong><span>-2.0</span></strong>.&nbsp;</span></span></div><div><span><span>&nbsp;</span></span></div><div><span><span>It is the&nbsp;<strong>world's first fully computer-generated genome of a living organism</strong>, developed by scientists at ETH Zurich.&nbsp;</span></span></div><div><span><span>&nbsp;</span></span></div><div><span><span>However, it must be emphasised that although the genome for&nbsp;</span><em>C. ethensis</em>-2.0 was physically produced in the form of a very large DNA molecule, a corresponding organism does not yet exist.</span></div><div><span>&nbsp;</span></div><div><span><strong>Source</strong>:&nbsp;<a href="https://www.sciencedaily.com/releases/2019/04/190401171343.htm?utm_source=feedburner&amp;utm_medium=email&amp;utm_campaign=Feed%3A+sciencedaily%2Fmost_popular+%28Most+Popular+News+--+ScienceDaily%29">https://www.sciencedaily.com/releases/2019/04/190401171343.htm</a></span></div>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40549/mgse-mapping-based-genome-size-estimation</guid>
	<pubDate>Fri, 17 Jan 2020 02:11:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40549/mgse-mapping-based-genome-size-estimation</link>
	<title><![CDATA[MGSE: Mapping-based Genome Size Estimation]]></title>
	<description><![CDATA[<p>MGSE can harness the power of files generated in genome sequencing projects to predict the genome size. Required are the FASTA file containing a high continuity assembly and a BAM file with all available reads mapped to this assembly. The script construct_cov_file.py (https://doi.org/10.1186/s12864-018-5360-z) allows the generation of a COV file based on the (sorted) BAM file (also possible via MGSE directly). Next, this COV file can be used by MGSE to calculate the coverage in provided reference regions and to calculate the total number of mapped bases. Both values are subjected to the genome size estimation. Providing accurate reference regions is crucial for this genome size estimation.</p><p>Address of the bookmark: <a href="https://github.com/bpucker/MGSE" rel="nofollow">https://github.com/bpucker/MGSE</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41604/synteny-and-rearrangement-identifier-syri</guid>
	<pubDate>Tue, 05 May 2020 10:37:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41604/synteny-and-rearrangement-identifier-syri</link>
	<title><![CDATA[Synteny and Rearrangement Identifier (SyRI)]]></title>
	<description><![CDATA[<p>SyRI is a comprehensive tool for predicting genomic differences between related genomes using whole-genome assemblies (WGA). The assemblies are aligned using whole-genome alignment tools, and these alignments are then used as input to SyRI. SyRI identifies syntenic path (longest set of co-linear regions), structural rearrangements (inversions, translocations, and duplications), local variations (SNPs, indels, CNVs etc) within syntenic and structural rearrangements, and un-aligned regions.</p><p>Address of the bookmark: <a href="https://schneebergerlab.github.io/syri/" rel="nofollow">https://schneebergerlab.github.io/syri/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43376/hisat2-index-files-download</guid>
	<pubDate>Wed, 15 Sep 2021 22:17:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43376/hisat2-index-files-download</link>
	<title><![CDATA[HISAT2 Index Files Download !]]></title>
	<description><![CDATA[<p>Resource for downloading all the HISAT2 related files&nbsp;</p>
<p>Please cite:</p>
<blockquote>
<p>Kim, D., Paggi, J.M., Park, C.&nbsp;<em>et al.</em>&nbsp;Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype.&nbsp;<em>Nat Biotechnol</em>&nbsp;<strong>37</strong>, 907&ndash;915 (2019).&nbsp;<a href="https://doi.org/10.1038/s41587-019-0201-4" target="_blank">https://doi.org/10.1038/s41587-019-0201-4</a></p>
</blockquote><p>Address of the bookmark: <a href="http://daehwankimlab.github.io/hisat2/download/#h-sapiens" rel="nofollow">http://daehwankimlab.github.io/hisat2/download/#h-sapiens</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43670/useful-bioinformatics-analysis-tools</guid>
	<pubDate>Thu, 23 Dec 2021 23:10:02 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43670/useful-bioinformatics-analysis-tools</link>
	<title><![CDATA[Useful Bioinformatics Analysis Tools !]]></title>
	<description><![CDATA[<h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=cometa&amp;subpage=about">CoMeta</a></h3><p><strong>Classificier of reads from metagenomic sequencing experiments.</strong></p><p><span>&bull;&nbsp;&nbsp;Kawulok, J., Deorowicz, S.,&nbsp;</span><em>CoMeta: Classification of Metagenomes Using k-mers</em><span>,&nbsp;</span><a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0121453">PLOS ONE,&nbsp;</a><span>2015; 10(4):1&ndash;23,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=CoMSA&amp;subpage=about">CoMSA</a></h3><p><strong>Compressor of multiple sequence alignments of proteins.</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S., Walczyszyn, J., Debudaj-Grabysz, A.,&nbsp;</span><em>CoMSA: compression of protein multiple sequence alignment files</em><span>,&nbsp;</span><a href="https://doi.org/10.1093/bioinformatics/bty619">Bioinformatics,&nbsp;</a><span>2019; 35(2):22&ndash;234,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=dsrc&amp;subpage=about">DSRC</a></h3><p><strong>Compressor of sequencing reads.</strong></p><p><span>&bull;&nbsp;&nbsp;Roguski, L., Deorowicz, S.,&nbsp;</span><em>DSRC 2: Industry-oriented compression of FASTQ files</em><span>,&nbsp;</span><a href="http://bioinformatics.oxfordjournals.org/content/30/15/2213">Bioinformatics,&nbsp;</a><span>2014; 30(15):2213&ndash;2215,</span><br /><span>&bull;&nbsp;&nbsp;Deorowicz, S., Grabowski, Sz.,&nbsp;</span><em>Compression of DNA sequences in FASTQ format</em><span>,&nbsp;</span><a href="http://bioinformatics.oxfordjournals.org/">Bioinformatics,&nbsp;</a><span>2011; 27(6):860&ndash;862,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=famsa&amp;subpage=about">FAMSA</a></h3><p><strong>Multiple sequence alignment designed for huge families of proteins (even containing hundreds of thousands of sequences).</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S., Debudaj-Grabysz, A., Gudys, A.,&nbsp;</span><em>FAMSA: Fast and accurate multiple sequence alignment of huge protein families</em><span>,&nbsp;</span><a href="http://www.nature.com/articles/srep33964">Scientific Reports,&nbsp;</a><span>2016; 6(33964):</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=fastore&amp;subpage=about">FaStore</a></h3><p><strong>Compressor of FASTQ files.</strong></p><p><span>&bull;&nbsp;&nbsp;Roguski, L., Ochoa, I., Hernaez, M., Deorowicz, S.,&nbsp;</span><em>FaStore - a space-saving solution for raw sequencing data</em><span>,&nbsp;</span><a href="https://doi.org/10.1093/bioinformatics/bty205">Bioinformatics,&nbsp;</a><span>2018; 34(16):2748&ndash;2756,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=fqsqueezer&amp;subpage=about">FQSqueezer</a></h3><p><strong>Experimental high-end compressor of FASTQ files.</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S.,&nbsp;</span><em>FQSqueezer: k-mer-based compression of sequencing data</em><span>,&nbsp;</span><a href="https://www.nature.com/articles/s41598-020-57452-6">Scientific Reports,&nbsp;</a><span>2020; 10(578):</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=gdc&amp;subpage=about">GDC</a></h3><p><strong>Compressor of collections of genome sequences.</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S., Danek, A., Niemiec, M.,&nbsp;</span><em>GDC 2: Compression of large collections of genomes</em><span>,&nbsp;</span><a href="http://www.nature.com/srep/2015/150625/srep11565/full/srep11565.html">Scientific Reports,&nbsp;</a><span>2015; 5(11565):1&ndash;12,</span><br /><span>&bull;&nbsp;&nbsp;Deorowicz, S., Grabowski, Sz.,&nbsp;</span><em>Robust relative compression of genomes with random access</em><span>,&nbsp;</span><a href="http://sun.aei.polsl.pl/REFRESH/bioinformatics.oxfordjournals.org/content/27/21/2979.abstract">Bioinformatics,&nbsp;</a><span>2011; 27(21):2979&ndash;2986,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=gtc&amp;subpage=about">GTC</a></h3><p><strong>Genotype databases compressor with support for fast queries.</strong></p><p><span>&bull;&nbsp;&nbsp;Danek, A., Deorowicz, S.,&nbsp;</span><em>GTC: how to maintain huge genotype collections in a compressed form</em><span>,&nbsp;</span><a href="https://doi.org/10.1093/bioinformatics/bty023">Bioinformatics,&nbsp;</a><span>2018; 34(11):1834&ndash;1840,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=gtshark&amp;subpage=about">GTShark</a></h3><p><strong>Genotypes compressor.</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S., Danek, A.,&nbsp;</span><em>GTShark: Genotype compression in large projects</em><span>,&nbsp;</span><a href="https://doi.org/10.1093/bioinformatics/btz508">Bioinformatics,&nbsp;</a><span>2019; 35(22):4791&ndash;4793,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=kmc&amp;subpage=about">KMC</a></h3><p><strong>Memory frugal&nbsp;<em>k</em>-mer counter.</strong></p><p><span>&bull;&nbsp;&nbsp;Kokot, M., Długosz, M., Deorowicz, S.,&nbsp;</span><em>KMC 3: counting and manipulating k -mer statistics</em><span>,&nbsp;</span><a href="https://doi.org/10.1093/bioinformatics/btx304">Bioinformatics,&nbsp;</a><span>2017; 33(17):2759&ndash;2761,</span><br /><span>&bull;&nbsp;&nbsp;Deorowicz, S., Kokot, M., Grabowski, Sz., Debudaj-Grabysz, A.,&nbsp;</span><em>KMC 2: Fast and resource-frugal k-mer counting</em><span>,&nbsp;</span><a href="https://doi.org/10.1093/bioinformatics/btv022">Bioinformatics,&nbsp;</a><span>2015; 31(10):1569&ndash;1576,</span><br /><span>&bull;&nbsp;&nbsp;Deorowicz, S., Debudaj-Grabysz, A., Grabowski, Sz.,&nbsp;</span><em>Disk-based k-mer counting on a PC</em><span>,&nbsp;</span><a href="http://www.biomedcentral.com/1471-2105/14/160">BMC Bioinformatics,&nbsp;</a><span>2013; 14():Article no. 160,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=kmer-db&amp;subpage=about">Kmer-db</a></h3><p><strong>Tool for estimation of evolutionary distances in a collection of genomes.</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S., Gudys, A., Dlugosz, M., Kokot, M., Danek, A.,&nbsp;</span><em>Kmer-db: instant evolutionary distance estimation</em><span>,&nbsp;</span><a href="https://doi.org/10.1093/bioinformatics/bty610">Bioinformatics,&nbsp;</a><span>2019; 35(1):133&ndash;136,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=mugi&amp;subpage=about">MuGI</a></h3><p><strong>Index allowing queries for a collection of multiple genome sequences.</strong></p><p><span>&bull;&nbsp;&nbsp;Danek, A., Deorowicz, S., Grabowski, Sz.,&nbsp;</span><em>Indexes of Large Genome Collections on a PC</em><span>,&nbsp;</span><a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0109384">PLOS ONE,&nbsp;</a><span>2014; 9(10):e109384,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=orcom&amp;subpage=about">ORCOM</a></h3><p><strong>Experimental compressor of sequencing reads.</strong></p><p><span>&bull;&nbsp;&nbsp;Grabowski, Sz., Deorowicz, S., Roguski, L.,&nbsp;</span><em>Disk-based compression of data from genome sequencing</em><span>,&nbsp;</span><a href="http://bioinformatics.oxfordjournals.org/content/early/2014/12/22/bioinformatics.btu844.abstract">Bioinformatics,&nbsp;</a><span>2014; 31(9):1389&ndash;1395,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=pgsa&amp;subpage=about">PgSA</a></h3><p><strong>Index allowing queries for a collection of sequencing reads.</strong></p><p><span>&bull;&nbsp;&nbsp;Kowalski, T., Grabowski, Sz., Deorowicz, S.,&nbsp;</span><em>Indexing arbitrary-length k-mers in sequencing reads</em><span>,&nbsp;</span><a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0133198">PLOS ONE,&nbsp;</a><span>2015; 10(7):1&ndash;16,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=quickprobs&amp;subpage=about">QuickProbs</a></h3><p><strong>Multiple sequence alignment designed especially for GPU.</strong></p><p><span>&bull;&nbsp;&nbsp;Gudys, A., Deorowicz, S.,&nbsp;</span><em>QuickProbs 2: towards rapid construction of high-quality alignments of large protein families</em><span>,&nbsp;</span><a href="http://www.nature.com/articles/srep41553">Scientific Reports,&nbsp;</a><span>2017; 7(41553):</span><br /><span>&bull;&nbsp;&nbsp;Gudys, A., Deorowicz, S.,&nbsp;</span><em>QuickProbs &ndash; A Fast Multiple Sequence Alignment Algorithm Designed for Graphics Processors</em><span>,&nbsp;</span><a href="http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0088901">PLOS ONE,&nbsp;</a><span>2014; 9(2):e88901,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=reckoner&amp;subpage=about">RECKONER</a></h3><p><strong>Read error corrector.</strong></p><p><span>&bull;&nbsp;&nbsp;Maciej Długosz, M., Deorowicz, S.,&nbsp;</span><em>RECKONER: read error corrector based on KMC</em><span>,&nbsp;</span><a href="https://academic.oup.com/bioinformatics/article-abstract/33/7/1086/2843893/RECKONER-read-error-corrector-based-on-KMC">Bioinformatics,&nbsp;</a><span>2017; 33(7):1086&ndash;1089,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=tgc&amp;subpage=about">TGC</a></h3><p><strong>Compressor of collections of genomes given in Variant Call Format (VCF) files.</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S., Danek, A., Grabowski, Sz.,&nbsp;</span><em>Genome compression: a novel approach for large collections</em><span>,&nbsp;</span><a href="http://bioinformatics.oxfordjournals.org/content/early/2013/08/29/bioinformatics.btt460">Bioinformatics,&nbsp;</a><span>2013; 29(20):2572&ndash;2578,</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=vcfshark&amp;subpage=about">VCFShark</a></h3><p><strong>Compressor of VCF files.</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S., Danek, A.,&nbsp;</span><em>GTShark: Genotype compression in large projects</em><span>,&nbsp;</span><a href="https://www.biorxiv.org/content/10.1101/2020.12.18.423437v1">biorxiv.org,&nbsp;</a><span>2020; ():</span></p><h3><a href="http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&amp;project=whisper&amp;subpage=about">Whisper</a></h3><p><strong>Experimental mapper of whole genome sequencing data.</strong></p><p><span>&bull;&nbsp;&nbsp;Deorowicz, S., Gudys, A.,&nbsp;</span><em>Whisper 2: indel-sensitive short read mapping</em><span>,&nbsp;</span><a href="https://doi.org/10.1101/2019.12.18.881292">bioRxiv.org,&nbsp;</a><span>2019; :</span><br /><span>&bull;&nbsp;&nbsp;Deorowicz, S., Debudaj-Grabysz, A., Gudys, A., Grabowski, Sz.,&nbsp;</span><em>Whisper: read sorting allows robust robust mapping of DNA sequencing data</em><span>,&nbsp;</span><a href="https://doi.org/10.1093/bioinformatics/bty927">Bioinformatics,&nbsp;</a><span>2019; 35(12):2043&ndash;2050,</span><br /><span>&bull;&nbsp;&nbsp;Deorowicz, S., Debudaj-Grabysz, A., Gudys, A., Grabowski, Sz.,&nbsp;</span><em>Robust mapping of whole genome sequencing data</em><span>,&nbsp;</span><a href="https://meetings.cshl.edu/abstracts.aspx?meet=GENOME&amp;year=17">Poster at The Biology of Genomes Conference,&nbsp;</a><span>2017;</span></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/44537/the-atcc-genome-portal</guid>
	<pubDate>Wed, 15 May 2024 14:24:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44537/the-atcc-genome-portal</link>
	<title><![CDATA[The ATCC Genome Portal]]></title>
	<description><![CDATA[<p><span>The ATCC Genome Portal (AGP,&nbsp;</span><a href="https://genomes.atcc.org/">https://genomes.atcc.org/</a><span>) is a database of authenticated genomes for bacteria, fungi, protists, and viruses held in ATCC&rsquo;s biorepository. It now includes 3,938 assemblies (253% increase) produced under ISO 9000 by ATCC. Here, we present new features and content added to the AGP for the research community.</span></p><p>Address of the bookmark: <a href="https://genomes.atcc.org/" rel="nofollow">https://genomes.atcc.org/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44503/entire-human-genome-sequencing</guid>
	<pubDate>Tue, 02 Apr 2024 01:19:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44503/entire-human-genome-sequencing</link>
	<title><![CDATA[Entire Human Genome Sequencing !]]></title>
	<description><![CDATA[<p>Cost-effective whole human genome sequencing has revolutionized the landscape of genetic research and personalized medicine by making comprehensive genetic analysis accessible to a wider population. Through advancements in sequencing technologies, such as next-generation sequencing (NGS), costs have significantly decreased, enabling researchers and healthcare providers to analyze an individual's complete genetic makeup with greater efficiency and affordability. This has profound implications for disease diagnosis, prognosis, and treatment, as it allows for the identification of genetic predispositions and the customization of healthcare interventions based on an individual's unique genetic profile. Moreover, as the cost continues to decline, the potential for population-scale genomic studies and large-scale screening programs becomes increasingly feasible, promising to further enhance our understanding of human genetics and improve healthcare outcomes on a global scale.</p><p>Here are few companies:</p><p>https://mynucleus.com/</p><p>https://myome.com/</p><p>https://nebula.org/whole-genome-sequencing-dna-test/</p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

</channel>
</rss>