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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44791?offset=10</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41158/carefully-opt-for-human-reference-genome</guid>
	<pubDate>Tue, 18 Feb 2020 07:43:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41158/carefully-opt-for-human-reference-genome</link>
	<title><![CDATA[Carefully opt for human reference genome]]></title>
	<description><![CDATA[<p><a href="http://lh3.github.io/2017/11/13/which-human-reference-genome-to-use" target="_blank">Heng Li posted several issues with the human reference genomes given in these resources</a> and suggests the following compressed FASTA file to be used as hg38/GRCh38 human reference genome.</p>
<p>if you map reads to GRCh38 or hg38, use the following:</p>
<div>
<div>
<pre><code>ftp://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/000/001/405/GCA_000001405.15_GRCh38/seqs_for_alignment_pipelines.ucsc_ids/GCA_000001405.15_GRCh38_no_alt_analysis_set.fna.gz
</code></pre>
</div>
</div>
<p>There are several other versions of GRCh37/GRCh38. What&rsquo;s wrong with them? Here are a collection of potential issues:</p>
<p>More at http://lh3.github.io/2017/11/13/which-human-reference-genome-to-use</p><p>Address of the bookmark: <a href="http://lh3.github.io/2017/11/13/which-human-reference-genome-to-use" rel="nofollow">http://lh3.github.io/2017/11/13/which-human-reference-genome-to-use</a></p>]]></description>
	<dc:creator>biogeek</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41144/seqmule-automated-human-exomegenome-variants-detection</guid>
	<pubDate>Tue, 18 Feb 2020 03:22:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41144/seqmule-automated-human-exomegenome-variants-detection</link>
	<title><![CDATA[SeqMule: Automated human exome/genome variants detection]]></title>
	<description><![CDATA[<p>SeqMule takes single-end or paird-end FASTQ or BAM files, generates a script consisting of more than 10 popular alignment, analysis tools and runs the script line by line. Users can change the pipeline or fine-tune the parameters by modifying its configuration file.</p><p>Address of the bookmark: <a href="https://doc-openbio.readthedocs.io/projects/seqmule/en/latest/" rel="nofollow">https://doc-openbio.readthedocs.io/projects/seqmule/en/latest/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/2518/genome-browsers</guid>
	<pubDate>Fri, 16 Aug 2013 19:04:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/2518/genome-browsers</link>
	<title><![CDATA[Genome Browsers]]></title>
	<description><![CDATA[<p>Genome Browser is the platform/database used for searching and retreiving sequences and annotation of genomes belong to various eukaryotes, prokaryotes, etc.</p><p>Following are the weblink for different available browsers:</p><p><a href="http://www.ensembl.org/index.html">http://www.ensembl.org/index.html</a></p><p><a href="http://ensemblgenomes.org/">http://ensemblgenomes.org/</a></p><p><a href="http://genome.ucsc.edu/">http://genome.ucsc.edu/</a></p><p><a href="http://www.ncbi.nlm.nih.gov/genome">http://www.ncbi.nlm.nih.gov/genome</a></p><p><a href="http://www.ebi.ac.uk/genomes/">http://www.ebi.ac.uk/genomes/</a></p><p><a href="http://flybase.org/">http://flybase.org/</a></p><p><a href="http://cmr.jcvi.org/tigr-scripts/CMR/CmrHomePage.cgi">http://cmr.jcvi.org/tigr-scripts/CMR/CmrHomePage.cgi</a></p><p><a href="http://www.sanger.ac.uk/resources/databases/">http://www.sanger.ac.uk/resources/databases/</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31300/clgenomics</guid>
	<pubDate>Fri, 03 Mar 2017 09:57:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31300/clgenomics</link>
	<title><![CDATA[CLgenomics]]></title>
	<description><![CDATA[<p>CLgenomics is a standalone desktop software specifically designed for bacterial genome analysis. This program has a powerful multi-genome browser, which enables rapid and responsive exploration of bacterial genomes.</p>
<p>To use CLgenomics, individual genome data (genome sequences + annotation details) are compiled and saved in a specially formatted file called CLG (ChunLab Genomics).&nbsp;Each CLG file corresponds with one bacterial genome. If multiple genomes are being considered and compared, multiple CLG files are needed. ChunLab offers &gt;40,000 CLG files of publicly available Bacterial and Archaeal genomes.</p><p>Address of the bookmark: <a href="https://chunlab.wordpress.com/clgenomics-software/" rel="nofollow">https://chunlab.wordpress.com/clgenomics-software/</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38447/kegg-mapper-%E2%80%93-reconstruct-pathway</guid>
	<pubDate>Wed, 12 Dec 2018 09:14:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38447/kegg-mapper-%E2%80%93-reconstruct-pathway</link>
	<title><![CDATA[KEGG Mapper – Reconstruct Pathway]]></title>
	<description><![CDATA[<p><strong>Reconstruct Pathway</strong><span>&nbsp;is a KEGG PATHWAY mapping tool that assists genome and metagenome annotations. The input data is a single gene list (for a single organism) or multiple gene lists (for multiple organisms) annotated with KEGG Orthology (KO) identifiers or K numbers. Each line of the gene list contains the user-defined gene identifier followed by, if any, the assigned K number. The mapping is performed through the K numbers against the KEGG reference pathways.&nbsp;</span></p><p>Address of the bookmark: <a href="https://www.kegg.jp/kegg/tool/map_pathway.html" rel="nofollow">https://www.kegg.jp/kegg/tool/map_pathway.html</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44489/proksee</guid>
	<pubDate>Wed, 27 Mar 2024 11:11:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44489/proksee</link>
	<title><![CDATA[Proksee]]></title>
	<description><![CDATA[<p><span>Proksee is an expert system for genome assembly, annotation and visualization. To begin using Proksee, provide a complete genome sequence, sequencing reads or a CGView/Proksee map JSON file.</span></p>
<fieldset><legend>Please Cite the Following</legend>
<div>Grant JR, Enns E, Marinier E, Mandal A, Herman EK, Chen C, Graham M, Van Domselaar G, and Stothard P</div>
<div><a href="https://pubmed.ncbi.nlm.nih.gov/37140037/">Proksee: in-depth characterization and visualization of bacterial genomes</a></div>
<div>Nucleic Acids Research, 2023, gkad326, https://doi.org/10.1093/nar/gkad326</div>
</fieldset><p>Address of the bookmark: <a href="https://proksee.ca/" rel="nofollow">https://proksee.ca/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45262/gipsy2-detect-hidden-islands-inside-bacteria</guid>
	<pubDate>Mon, 24 Aug 2026 18:15:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45262/gipsy2-detect-hidden-islands-inside-bacteria</link>
	<title><![CDATA[GIPSy2 Detect Hidden Islands Inside Bacteria]]></title>
	<description><![CDATA[<p>Imagine a tiny bacterium living in a crowded environment.</p><p>It looks simple, but inside its microscopic body is a huge library of DNA. Most of this DNA has been passed down from its parents. But sometimes, bacteria can pick up new pieces of DNA from other bacteria.</p><p>These new pieces can give them useful abilities &mdash; such as surviving antibiotics, causing disease, or adapting to a new environment.</p><p>Scientists call some of these special DNA regions genomic islands.</p><p>But there is a problem: How do we find these hidden islands?</p><p>That is where GIPSy2 comes in.</p><p>Researchers developed GIPSy2, a computer tool that acts like a detective. It scans bacterial DNA and looks for unusual patterns that might show where a genomic island is hiding.</p><p>Instead of looking at just one clue, GIPSy2 uses several methods to investigate the DNA. It can also study many bacterial genomes, making it useful when researchers have large amounts of genetic data.</p><p>In their study, the researchers tested GIPSy2 on different bacteria. The tool was able to identify genomic regions connected with important features such as antibiotic resistance, disease-causing abilities, metabolism, and relationships with other organisms.</p><p>Think of it like searching for hidden islands on a huge map. The DNA is the ocean, and genomic islands are the small pieces of land that may contain valuable information.</p><p>GIPSy2 does not give scientists the final answer by itself. Its predictions still need to be carefully checked and, when possible, confirmed through experiments.</p><p>But it gives researchers a faster way to explore bacterial genomes and discover clues about how bacteria change and survive.</p><p>And that is why this small piece of software could help scientists better understand the invisible world of bacteria &mdash; one hidden genomic island at a time.</p><p><span>GIPSy2 is currently available on Zenodo repository at </span><a href="https://zenodo.org/doi/10.5281/zenodo.10222587">https://zenodo.org/doi/10.5281/zenodo.10222587</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/38551/gupta-lab</guid>
  <pubDate>Sat, 29 Dec 2018 13:18:31 -0600</pubDate>
  <link></link>
  <title><![CDATA[Gupta Lab]]></title>
  <description><![CDATA[
<p>Work include (i) understanding the evolutionary relationships among different prokaryotic and eukaryotic organisms; (ii) Understanding the cellular functions of these lineage-specific signature proteins as well as lineage-specific conserved inserts and deletions in important housekeeping proteins by genetic and biochemical studies; (iii) Development of novel diagnostic methods (PCR based and immunological) for identification of different groups of organisms based upon these signature proteins and conserved indels; (iv) The use of these lineage-specific probes with predicitive ability to identify/explore the presence of different groups of organisms in metagenomic sequences from various environments.</p>

<p>https://fhs.mcmaster.ca/gupta-lab/index.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/5388/biggest-human-brain-project-hbp-launched</guid>
	<pubDate>Mon, 07 Oct 2013 19:50:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/5388/biggest-human-brain-project-hbp-launched</link>
	<title><![CDATA[Biggest Human Brain Project (HBP) launched!!!]]></title>
	<description><![CDATA[<p><img src="http://s1.ibtimes.com/sites/www.ibtimes.com/files/styles/v2_article_large/public/2013/10/07/human-brain-project.jpg" width="500" height="500" alt="image" style="border: 0px;"></p><p>"In neuroscience, the project will use neuroinformatics and brain simulation to collect and integrate experimental data, identifying and filling gaps in our knowledge, and prioritising future experiments.</p><p>In medicine, the HBP will use medical informatics to identify biological signatures of brain disease, allowing diagnosis at an early stage, before the disease has done irreversible damage, and enabling personalized treatment, adapted to the needs of individual patients. Better diagnosis, combined with disease and drug simulation, will accelerate the discovery of new treatments, drastically lowering the cost of drug discovery.<br /><br />In computing, new techniques of interactive supercomputing, driven by the needs of brain simulation, will impact a vast range of industries. Devices and systems, modelled after the brain, will overcome fundamental limits on the energy-efficiency, reliability and programmability of current technologies, clearing the road for systems with brain-like intelligence."</p><p>Source:&nbsp;<a href="http://www.forbes.com/sites/jenniferhicks/2013/10/07/the-human-brain-project-begins/">http://www.forbes.com/sites/jenniferhicks/2013/10/07/the-human-brain-project-begins/</a>&nbsp;</p><p>(<a href="https://www.facebook.com/humanbrainproj/info">https://www.facebook.com/humanbrainproj/info</a>)</p><p>Home Page:</p><p><a href="https://www.humanbrainproject.eu/">https://www.humanbrainproject.eu/</a></p><p>Jobs:</p><p><a href="https://www.humanbrainproject.eu/participate/jobs">https://www.humanbrainproject.eu/participate/jobs</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41869/hs3d-homo-sapiens-splice-sites-dataset</guid>
	<pubDate>Fri, 12 Jun 2020 12:33:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41869/hs3d-homo-sapiens-splice-sites-dataset</link>
	<title><![CDATA[HS3D: Homo Sapiens Splice Sites Dataset]]></title>
	<description><![CDATA[<p>HS3D (Homo Sapiens Splice Sites Dataset) is a data set of Homo Sapiens Exon, Intron and Splice regions extracted from GenBank Rel.123. The aim of this data set is to give standardized material to train and to assess the prediction accuracy of computational approaches for gene identification and characterization. From the complete GenBank (Primate Sequences Division) Rel.123 (162,557 entries), entries of Human Nuclear DNA including Complete CDS and more than one Exon have been selected, and 4523 exons and 3802 introns have been extracted from these entries. Details about extracted exons and introns are reported (Locus, number, Start and End position in the entry, sequence, length, G+C content, presence of not AGCT data (nucleotide scan check)). Statistics are also reported (overall nucleotides, average G+C content, nucleotide scan check results, number of not GT starting / AG ending introns, minimum /&nbsp; &nbsp;maximum / average length, length standard deviation) . 3799+3799 donor and acceptor sites, as windows of 140 nucleotides around&nbsp; each splice site have been extracted. After discarding sequences not including canonical GT&ndash;AG junctions (65+74),&nbsp; including insufficient data (not enough material for a 140 nucleotide window) (686+589),&nbsp; including not AGCT bases (29+30), and redundant (218+226) there are 2796+ 2880 windows.&nbsp;</p>
<p>1. P.Pollastro, S.Rampone (2002). HS3D, a Dataset of Homo Sapiens Splice Regions, and its Extraction Procedure from a Major Public Database , International Journal of Modern Physics C, 13(8), 1105-1117. (please cite this paper)</p>
<p>2. P.Pollastro, S.Rampone (2003). HS3D: Homo Sapiens Splice Site Data Set , Nucleic Acids Research, 2003 Annual Database Issue.</p><p>Address of the bookmark: <a href="http://www.sci.unisannio.it/docenti/rampone/" rel="nofollow">http://www.sci.unisannio.it/docenti/rampone/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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