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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44848?offset=80</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31568/pacbio-long-reads-compatible-software-and-tools</guid>
	<pubDate>Wed, 15 Mar 2017 14:19:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31568/pacbio-long-reads-compatible-software-and-tools</link>
	<title><![CDATA[Pacbio Long Reads Compatible Software and Tools]]></title>
	<description><![CDATA[<p>The following software packages are known to be compatible with PacBio&reg; data, in addition to PacBio's own SMRT&reg; Analysis suite. All packages are believed to be open source or freely available for non-commercial use. See the individual project sites for up-to-date license information. A separate page lists&nbsp;<a href="http://pacb.com/community/partner_program/current_partners/">commercial software</a>.</p>
<p>Know of any other open source software for PacBio data?&nbsp;<a href="mailto:devnet@pacificbiosciences.com">Email us</a>.</p>
<p>Software categories:</p>
<ul>
<li><a href="https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software#denovo">De novo assembly</a></li>
<li><a href="https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software#svdetection">Structural Variations Detection</a></li>
<li><a href="https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software#aligners">Reference-based alignment</a></li>
<li><a href="https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software#variants">Consensus and variant calling</a></li>
<li><a href="https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software#RNA">RNA analysis</a></li>
<li><a href="https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software#basemods">Epigenetic base modifications and methylation</a></li>
<li><a href="https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software#barcoding">Barcoding</a></li>
<li><a href="https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software#browsers">Genome Browsers</a></li>
<li><a href="https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software#qc">Run QC</a></li>
<li><a href="https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software#frameworks">Frameworks and APIs</a></li>
</ul><p>Address of the bookmark: <a href="https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software" rel="nofollow">https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software</a></p>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32709/cabog-celera-assembler-with-best-overlap-graph</guid>
	<pubDate>Mon, 15 May 2017 05:04:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32709/cabog-celera-assembler-with-best-overlap-graph</link>
	<title><![CDATA[CABOG: Celera Assembler with Best Overlap Graph]]></title>
	<description><![CDATA[<p>CABOG (Celera Assembler with Best Overlap Graph) is scientific software for&nbsp;<a href="http://bioinformatics.oxfordjournals.org/content/24/24/2818.abstract">DNA research</a>. CABOG has been a critical component of many genome sequencing projects. CABOG operates on small genomes such as bacterial as well as large genomes such as mammalian. CABOG is an extension of the Celera Assembler software that was originally developed at&nbsp;<a href="http://www.celera.com/">Celera</a>&nbsp;for the 2001 publication of the first draft human genome sequence. The software was released to the public domain in 2004. Its open source&nbsp;<a href="http://wgs-assembler.sf.net/">repository</a>&nbsp;on Source Forge is an internet resource for scientists around the world.&nbsp;</p>
<p>CABOG is one of many software programs called genome assemblers. These programs exist to overcome the fundamental limitation of all sequencing machines, namely, that they read out very few DNA letters at a time. These programs reconstruct genomes that are billions of letters long from the hundreds of letters per read that modern sequencers provide. What these programs do is often described as a scaled up version of a family solving a jigsaw puzzle.</p>
<p>The CABOG software was the first to accomplish many scientific goals. It was the first to assemble the genome of a multicellular organism (<em>Drosophila melanogaster</em>, 2000). It was the first to assemble both parental haplotypes of one human genome (J. Craig Venter, 2007). It was the first to assemble environmental sequence from the oceans (Sargasso Sea in 2004 and Global Ocean Sampling in 2007). It was first to combine reads from first-generation Sanger sequencing machines and second-generation pyrosequencing machines (Marine microbes, 2006). Today, CABOG is one of the leading assembly programs for data sets that include paired end data from the Roche 454 line of sequencing machines.</p><p>Address of the bookmark: <a href="http://www.jcvi.org/cms/research/projects/cabog/overview/" rel="nofollow">http://www.jcvi.org/cms/research/projects/cabog/overview/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36597/gappadder-a-sensitive-approach-for-closing-gaps-on-draft-genomes-with-short-sequence-reads</guid>
	<pubDate>Mon, 14 May 2018 05:25:48 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36597/gappadder-a-sensitive-approach-for-closing-gaps-on-draft-genomes-with-short-sequence-reads</link>
	<title><![CDATA[GAPPadder: A Sensitive Approach for Closing Gaps on Draft Genomes with Short Sequence Reads]]></title>
	<description><![CDATA[<p><span>This software is provided ``as is&rdquo; without warranty of any kind. In no event shall the author be held responsible for any damage resulting from the use of this software. The program package, including source codes, executables, and this documentation, is distributed free of charge. If you use this program in a publication, please cite the following reference:</span><br><span>Chong Chu, Xin Li, and Yufeng Wu. "GAPPadder: A Sensitive Approach for Closing Gaps on Draft Genomes with Short Sequence Reads." bioRxiv (2017): 125534.</span></p><p>Address of the bookmark: <a href="https://github.com/Reedwarbler/GAPPadder" rel="nofollow">https://github.com/Reedwarbler/GAPPadder</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40940/consed-a-finishing-package-bam-file-viewer-assembly-editor-autofinish-autoreport-autoedit-and-align-reads-to-reference-sequence</guid>
	<pubDate>Fri, 07 Feb 2020 07:16:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40940/consed-a-finishing-package-bam-file-viewer-assembly-editor-autofinish-autoreport-autoedit-and-align-reads-to-reference-sequence</link>
	<title><![CDATA[Consed--A Finishing Package (BAM File Viewer, Assembly Editor, Autofinish, Autoreport, Autoedit, and Align Reads To Reference Sequence)]]></title>
	<description><![CDATA[<ul>
<li>Supports Illumina, 454, other Next-Gen and Sanger Reads and allows mixtures of these read types</li>
<li>Consed includes BamScape which can view bam files with unlimited numbers of reads. BamScape can bring up consed to edit reads and the reference sequence in targeted regions.</li>
<li>Consed is compatible with Newbler, Cross_match, Phrap, MIRA, Velvet and PCAP output.</li>
<li>Quickly takes the user to each variant site for viewing (also available as an automated report)</li>
<li>Overview of assembly can help detect and fix misassemblies</li>
<li>Editing time reduced by the program's ability to pin-point problem areas</li>
<li>Editing is guided by error probabilities</li>
</ul><p>Address of the bookmark: <a href="http://www.phrap.org/consed/consed.html" rel="nofollow">http://www.phrap.org/consed/consed.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44593/bear-better-emulation-for-artificial-reads</guid>
	<pubDate>Sat, 06 Jul 2024 04:27:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44593/bear-better-emulation-for-artificial-reads</link>
	<title><![CDATA[BEAR: Better Emulation for Artificial Reads]]></title>
	<description><![CDATA[<p dir="auto">Created by Stephen Johnson, Brett Trost, Dr. Jeffrey R. Long, Dr. Anthony Kusalik University of Saskatchewan, Department of Computer Science</p>
<p dir="auto">BEAR is intended to be an easy-to-use collection of scripts for generating simulated WGS metagenomic reads with read lengths, quality scores, error profiles, and species abundances derived from real user-supplied WGS data.</p><p>Address of the bookmark: <a href="https://github.com/sej917/BEAR" rel="nofollow">https://github.com/sej917/BEAR</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43856/puffaligner-a-fast-efficient-and-accurate-aligner-based-on-the-pufferfish-index</guid>
	<pubDate>Thu, 21 Apr 2022 05:41:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43856/puffaligner-a-fast-efficient-and-accurate-aligner-based-on-the-pufferfish-index</link>
	<title><![CDATA[PuffAligner: a fast, efficient and accurate aligner based on the Pufferfish index]]></title>
	<description><![CDATA[<p><span>PuffAligner, a fast, accurate and versatile aligner built on top of the Pufferfish index. PuffAligner is able to produce highly sensitive alignments, similar to those of Bowtie2, but much more quickly. While exhibiting similar speed to the ultrafast STAR aligner, PuffAligner requires considerably less memory to construct its index and align reads. PuffAligner strikes a desirable balance with respect to the time, space and accuracy tradeoffs made by different alignment tools and provides a promising foundation on which to test new alignment ideas over large collections of sequences.</span></p><p>Address of the bookmark: <a href="https://github.com/COMBINE-lab/pufferfish/tree/cigar-strings" rel="nofollow">https://github.com/COMBINE-lab/pufferfish/tree/cigar-strings</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/14801/the-home-microbiome-project</guid>
	<pubDate>Tue, 02 Sep 2014 15:21:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/14801/the-home-microbiome-project</link>
	<title><![CDATA[The Home Microbiome Project]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/dQCBpmUZlF4" frameborder="0" allowfullscreen></iframe>The Home Microbiome Project is an initiative aimed at uncovering the dynamic co-associations between people's bacteria and the bacteria found in their homes.The hope is that the data and project will show that routine monitoring of the microbial diversity of your body and of the environment in which you live is possible.

Computer animation courtesy the Biology & Built Environment (BioBE) Center, University of Oregon and Cameron Slayden at Cosmocyte. http://vimeo.com/90059732

BioBE on Vimeo: http://vimeo.com/user22991553]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35823/regen-ancestral-genome-reconstruction-for-bacteria</guid>
	<pubDate>Tue, 06 Mar 2018 05:02:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35823/regen-ancestral-genome-reconstruction-for-bacteria</link>
	<title><![CDATA[REGEN: Ancestral Genome Reconstruction for Bacteria]]></title>
	<description><![CDATA[<p><span>REGEN infers evolutionary events, including gene creation and deletion and replicon fission and fusion. The reconstruction can be performed by either a maximum parsimony or a maximum likelihood method. Gene content reconstruction is based on the concept of neighboring gene pairs. REGEN was designed to be used with any set of genomes that are sufficiently related, which will usually be the case for bacteria within the same taxonomic order.&nbsp;</span></p><p>Address of the bookmark: <a href="http://www.mdpi.com/2073-4425/3/3/423" rel="nofollow">http://www.mdpi.com/2073-4425/3/3/423</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38452/silix-implements-an-ultra-efficient-algorithm-for-the-clustering-of-homologous-sequences</guid>
	<pubDate>Wed, 12 Dec 2018 09:22:41 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38452/silix-implements-an-ultra-efficient-algorithm-for-the-clustering-of-homologous-sequences</link>
	<title><![CDATA[SiLiX: implements an ultra-efficient algorithm for the clustering of homologous sequences]]></title>
	<description><![CDATA[<p>The software package SiLiX implements<strong>&nbsp;an ultra-efficient algorithm for the clustering of homologous sequences</strong>, based on single transitive links (<em>single linkage</em>) with alignment coverage constraints.</p>
<p>SiLiX adopts a graph-theoretical framework to interpret similarity pairs as edges of a network. A very efficient algorithm, based on the&nbsp;<em>Disjoint Sets Data Structure</em>, allows the computation of sequence families with&nbsp;<strong>low time and space requirements</strong>.</p>
<p><strong>A parallel version</strong>&nbsp;of SiLiX, based on MPI, is also available in this package and has been proved to be scalable, so that its allows the study of&nbsp;<strong>very large datasets</strong>.</p>
<p>SiLiX is already included in the analysis pipeline for&nbsp;<a href="http://pbil.univ-lyon1.fr/databases/hogenom/acceuil.php">HOGENOM</a>.</p><p>Address of the bookmark: <a href="http://lbbe.univ-lyon1.fr/SiLiX?lang=fr" rel="nofollow">http://lbbe.univ-lyon1.fr/SiLiX?lang=fr</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<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>
<li>
<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>
<li>
<p>Gut microbiome modulation through diet, drugs, or engineered bacteria</p>
</li>
<li>
<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>
</item>

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