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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/43846?offset=140</link>
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	<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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44791/hibc-human-intestinal-bacteria-collection</guid>
	<pubDate>Wed, 07 May 2025 05:49:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44791/hibc-human-intestinal-bacteria-collection</link>
	<title><![CDATA[HiBC: Human Intestinal Bacteria Collection]]></title>
	<description><![CDATA[<p>The human gut is home to trillions of microorganisms, forming one of the most complex and dynamic microbial ecosystems known to science. The <strong style="font-size: 12.8px;">Human Intestinal Bacteria Collection (HiBC)</strong><span style="font-size: 12.8px; font-weight: normal;"> is a pioneering initiative aimed at cataloging, preserving, and studying the diverse bacterial species that inhabit the human gastrointestinal tract. This curated collection serves as a critical resource for researchers working on microbiome-related health, disease, and therapeutics.</span></p><h2>What is HiBC?</h2><p>The Human Intestinal Bacteria Collection (HiBC) is a comprehensive, high-quality reference repository of bacterial isolates derived from human fecal samples. It focuses on anaerobic and facultative anaerobic bacteria that play pivotal roles in digestion, immune modulation, vitamin synthesis, and pathogen resistance. The collection includes both culturable strains and genomic data from unculturable taxa, bridging the gap between culture-dependent and -independent microbiome studies.</p><h2>Why is HiBC Important?</h2><ol>
<li>
<p><strong>Understanding Microbiome-Host Interactions</strong><br /> HiBC enables deeper insight into the functions of specific bacterial taxa in the gut. With well-characterized isolates, researchers can conduct mechanistic studies to explore how certain bacteria influence metabolism, inflammation, or mental health.</p>
</li>
<li>
<p><strong>Precision Probiotics and Therapeutics</strong><br /> By providing access to native human gut microbes, HiBC supports the development of next-generation probiotics, live biotherapeutic products (LBPs), and fecal microbiota transplantation (FMT) alternatives.</p>
</li>
<li>
<p><strong>Standardization and Reproducibility</strong><br /> With standardized cultivation and genomic protocols, HiBC ensures consistency across microbiome research studies, improving reproducibility and comparability of findings.</p>
</li>
<li>
<p><strong>Antimicrobial Resistance (AMR) Surveillance</strong><br /> HiBC includes metadata on antibiotic resistance genes (ARGs), helping track the spread of AMR in commensal gut bacteria and understanding its implications for human health.</p>
</li>
</ol><h2>Key Features of HiBC</h2><ul>
<li>
<p><strong>Culturable Bacteria Repository:</strong> A living collection of anaerobic and facultative strains isolated from healthy and diseased individuals worldwide.</p>
</li>
<li>
<p><strong>Metadata-rich Entries:</strong> Each isolate is annotated with host details (age, health status, diet), geographical origin, phenotypic traits, and antibiotic susceptibility profiles.</p>
</li>
<li>
<p><strong>Whole Genome Sequencing (WGS):</strong> High-quality genome assemblies for most strains to support functional and comparative genomics.</p>
</li>
<li>
<p><strong>Interactive Database Access:</strong> User-friendly search and filtering options for strain selection based on taxonomy, function, or clinical relevance.</p>
</li>
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<p><strong>Cross-linking with Other Databases:</strong> Integration with NCBI, GOLD, and Human Microbiome Project (HMP) data for broader context and validation.</p>
</li>
</ul><h2>Applications of HiBC</h2><ul>
<li>
<p>Microbiome-based diagnostics and biomarker discovery</p>
</li>
<li>
<p>Host-microbe interaction studies in gnotobiotic mouse models</p>
</li>
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<p>Gut microbiome modulation through diet, drugs, or engineered bacteria</p>
</li>
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<p>Longitudinal studies of gut flora across age, geography, and lifestyle</p>
</li>
<li>
<p>Environmental and evolutionary microbiology of human-associated bacteria</p>
</li>
</ul><h2>Accessing HiBC</h2><p>Researchers and interested parties can explore the HiBC database through its official website: <a href="https://www.hibc.rwth-aachen.de/" target="_new">https://www.hibc.rwth-aachen.de/</a>. The platform offers comprehensive information on bacterial isolates, including taxonomy, cultivation conditions, and genomic data, facilitating advanced research in human gut microbiome studies.</p><h2>Final Thoughts</h2><p>The <strong>HiBC</strong> is a cornerstone resource in the rapidly evolving field of microbiome research. As science moves toward personalized medicine and microbial therapeutics, having a reliable and diverse collection of human gut bacteria is not just useful &mdash; it's essential. Whether you're a microbiologist, clinician, computational biologist, or biotechnologist, HiBC offers tools to accelerate discovery and innovation in gut microbiome science.</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39281/humcfs-a-database-of-fragile-sites-in-human-chromosomes</guid>
	<pubDate>Sun, 21 Apr 2019 20:17:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39281/humcfs-a-database-of-fragile-sites-in-human-chromosomes</link>
	<title><![CDATA[HumCFS: a database of fragile sites in human chromosomes]]></title>
	<description><![CDATA[<p>Fragile sites are specific chromosomal region that exhibit an increased frequency of chromosdomal breakge when cells are exposed to replicative stress. Since from the discovery of chromosomal fragile sites/regions (CFS), several line of evidence suggests their involvement in human pathologies and they have been recognized as a preferential site for integration of exogenous oncogenic DNA viruses and hotspots for chromosomal re-arrangement. There is large gap in our knowledge of human CFS region as knowledge about CFS are unequally distributed in literature, which impose a problem in studying these region. In order to address these issues, we develop this platform HumCFS, which provides comprehensive information about experimentally identified CFS at a single source.</p>
<p>https://link.springer.com/epdf/10.1186/s12864-018-5330-5?author_access_token=ICASEpyMAQaxLlKw--fyCG_BpE1tBhCbnbw3BuzI2RMA57KLmXk5bZabRUiDQzRFHXd6hjm4kWSiLV3mU5XVMitqXUwFMSo4x5vbfty0EDQ9PW1sd1h923_TYXkvJ5niSwAyZ7BklJ0ujFAFhcKtjw%3D%3D</p><p>Address of the bookmark: <a href="https://webs.iiitd.edu.in/raghava/humcfs/" rel="nofollow">https://webs.iiitd.edu.in/raghava/humcfs/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27331/andi</guid>
	<pubDate>Fri, 13 May 2016 05:16:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27331/andi</link>
	<title><![CDATA[Andi]]></title>
	<description><![CDATA[<p>This is the <code>andi</code> program for estimating the evolutionary distance between closely related genomes. These distances can be used to rapidly infer phylogenies for big sets of genomes. Because <code>andi</code> does not compute full alignments, it is so efficient that it scales even up to thousands of bacterial genomes.</p>
<p>This readme covers all necessary instructions for the impatient to get <code>andi</code> up and running. For extensive instructions please consult the <a href="https://github.com/EvolBioInf/andi/blob/master/andi-manual.pdf">manual</a>.</p>
<p>More at https://github.com/evolbioinf/andi/</p><p>Address of the bookmark: <a href="http://bioinformatics.oxfordjournals.org/content/early/2015/01/13/bioinformatics.btu815.full" rel="nofollow">http://bioinformatics.oxfordjournals.org/content/early/2015/01/13/bioinformatics.btu815.full</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28119/kraken-ultrafast-metagenomic-sequence-classification-using-exact-alignments</guid>
	<pubDate>Mon, 27 Jun 2016 11:01:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28119/kraken-ultrafast-metagenomic-sequence-classification-using-exact-alignments</link>
	<title><![CDATA[Kraken: ultrafast metagenomic sequence classification using exact alignments]]></title>
	<description><![CDATA[<p>Kraken is an ultrafast and highly accurate program for assigning taxonomic labels to metagenomic DNA sequences. Previous programs designed for this task have been relatively slow and computationally expensive, forcing researchers to use faster abundance estimation programs, which only classify small subsets of metagenomic data. Using exact alignment of <em>k</em>-mers, Kraken achieves classification accuracy comparable to the fastest BLAST program. In its fastest mode, Kraken classifies 100 base pair reads at a rate of over 4.1 million reads per minute, 909 times faster than Megablast and 11 times faster than the abundance estimation program MetaPhlAn. Kraken is available at <a href="http://ccb.jhu.edu/software/kraken/" target="pmc_ext">http://ccb.jhu.edu/software/kraken/</a>.</p>
<p>Krona</p>
<p>https://sourceforge.net/p/krona/home/krona/</p><p>Address of the bookmark: <a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4053813/" rel="nofollow">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4053813/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33789/i-pv-interactive-protein-sequence-visualization</guid>
	<pubDate>Mon, 03 Jul 2017 07:52:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33789/i-pv-interactive-protein-sequence-visualization</link>
	<title><![CDATA[I-PV: Interactive Protein Sequence Visualization]]></title>
	<description><![CDATA[<p><span>I-PV is a interactive data visualization software designed for inspection of protein sequences and mutation information. It is mainly used for Genetics and Bioinformatics. So what exactly makes it standout?</span></p>
<p><span>http://i-pv.org/ipv_rec</span></p><p>Address of the bookmark: <a href="http://i-pv.org/" rel="nofollow">http://i-pv.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37993/platypus-a-haplotype-based-variant-caller-for-next-generation-sequence-data</guid>
	<pubDate>Thu, 25 Oct 2018 06:14:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37993/platypus-a-haplotype-based-variant-caller-for-next-generation-sequence-data</link>
	<title><![CDATA[Platypus: A Haplotype-Based Variant Caller For Next Generation Sequence Data]]></title>
	<description><![CDATA[<p><strong>Platypus</strong><span>&nbsp;is a tool designed for efficient and accurate variant-detection in high-throughput sequencing data. By using local realignment of reads and local assembly it achieves both high sensitivity and high specificity. Platypus can detect SNPs, MNPs, short indels, replacements and (using the assembly option) deletions up to several kb. It has been extensively tested on&nbsp;</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/?term=24463883">whole-genome</a><span>,&nbsp;</span><a href="http://www.nature.com/ng/journal/v45/n1/abs/ng.2492.html">exon-capture</a><span>, and&nbsp;</span><a href="http://www.nature.com/nature/journal/v493/n7432/abs/nature11725.html">targeted capture</a><span>&nbsp;data, it has been run on very large datasets as part of the&nbsp;</span><a href="http://www.1000genomes.org/">Thousand Genomes</a><span>&nbsp;and WGS500 projects, and is being used in clinical sequencing trials in the&nbsp;</span><a href="http://www.mcgprogramme.com/">Mainstreaming Cancer Genetics</a><span>&nbsp;programme.&nbsp;</span></p>
<p><span>Tutorial&nbsp;https://github.com/andyrimmer/Platypus/blob/master/misc/README.txt</span></p><p>Address of the bookmark: <a href="http://www.well.ox.ac.uk/platypus" rel="nofollow">http://www.well.ox.ac.uk/platypus</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42359/dnasp-dna-sequence-polymorphism-is-a-software-package-for-the-analysis-of-dna-polymorphisms</guid>
	<pubDate>Wed, 25 Nov 2020 19:51:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42359/dnasp-dna-sequence-polymorphism-is-a-software-package-for-the-analysis-of-dna-polymorphisms</link>
	<title><![CDATA[DnaSP: DNA Sequence Polymorphism, is a software package for the analysis of DNA polymorphisms]]></title>
	<description><![CDATA[<p><span>DnaSP, DNA Sequence Polymorphism, is a software package for the analysis of DNA polymorphisms using data from a single locus (a multiple sequence aligned -MSA data), or from several loci (a Multiple-MSA data, such as formats generated by some assembler RAD-seq software). DnaSP can estimate several measures of DNA sequence variation within and between populations in noncoding, synonymous or nonsynonymous sites, or in various sorts of codon positions), as well as linkage disequilibrium, recombination, gene flow and gene conversion parameters.</span></p><p>Address of the bookmark: <a href="http://www.ub.edu/dnasp/" rel="nofollow">http://www.ub.edu/dnasp/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44555/ultra-ultra-locates-tandemly-repetitive-areas-effective-labeling-of-repetitive-genomic-sequence</guid>
	<pubDate>Sat, 08 Jun 2024 16:03:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44555/ultra-ultra-locates-tandemly-repetitive-areas-effective-labeling-of-repetitive-genomic-sequence</link>
	<title><![CDATA[ULTRA (ULTRA Locates Tandemly Repetitive Areas) : Effective Labeling of Repetitive Genomic Sequence]]></title>
	<description><![CDATA[<p dir="auto">ULTRA is a tool to find and annotate tandem repeats inside genomic sequence. It is able to find repeats of any length and of any period (up to a maximum period of 4000). It can find highly decayed repeats missed by other software, and it will also be able to find very large repeats in highly repetitive sequence, regardless of the size of sequence or length of repeats. ULTRA offers meaningful annotation scores and can produce annotation P-values at user request.</p>
<p dir="auto">More at&nbsp;https://www.biorxiv.org/content/10.1101/2024.06.03.597269v1</p><p>Address of the bookmark: <a href="https://github.com/TravisWheelerLab/ULTRA" rel="nofollow">https://github.com/TravisWheelerLab/ULTRA</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34391/taxoblast-taxoblast-is-a-pipeline-to-identify-contamination-in-genomic-sequence</guid>
	<pubDate>Thu, 23 Nov 2017 08:37:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34391/taxoblast-taxoblast-is-a-pipeline-to-identify-contamination-in-genomic-sequence</link>
	<title><![CDATA[Taxoblast : Taxoblast is a pipeline to identify contamination in genomic sequence]]></title>
	<description><![CDATA[<p><span>Modern genome sequencing strategies are highly sensitive to contamination making the detection of foreign DNA sequences an important part of analysis pipelines. Here we use Taxoblast, a simple pipeline with a graphical user interface, for the post-assembly detection of contaminating sequences in the published genome of the kelp&nbsp;</span><em>Saccharina japonica</em><span>. Analyses were based on multiple blastn searches with short sequence fragments. They revealed a number of probable bacterial contaminations as well as hybrid scaffolds that contain both bacterial and algal sequences. This or similar types of analysis, in combination with manual curation, may thus constitute a useful complement to standard bioinformatics analyses prior to submission of genomic data to public repositories. Our analysis pipeline is open-source and freely available at&nbsp;</span><a href="http://sdittami.altervista.org/taxoblast" title="">http://sdittami.altervista.org/taxoblast</a><span>&nbsp;and via SourceForge (</span><a href="https://sourceforge.net/projects/taxoblast" title="">https://sourceforge.net/projects/taxoblast</a><span>).</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/taxoblast/files/" rel="nofollow">https://sourceforge.net/projects/taxoblast/files/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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