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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29029?offset=150</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31375/cocacola-binning-metagenomic-contigs-using-sequence-composition-read-coverage-co-alignment-and-paired-end-read-linkage</guid>
	<pubDate>Tue, 07 Mar 2017 08:50:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31375/cocacola-binning-metagenomic-contigs-using-sequence-composition-read-coverage-co-alignment-and-paired-end-read-linkage</link>
	<title><![CDATA[COCACOLA (binning metagenomic contigs using sequence COmposition, read CoverAge, CO-alignment, and paired-end read LinkAge)]]></title>
	<description><![CDATA[<p>COCACOLA is a general framework that combines different types of information: sequence COmposition, CoverAge across multiple samples, CO-alignment to reference genomes and paired-end reads LinkAge to automatically bin contigs into OTUs. Furthermore, COCACOLA seamlessly embraces customized prior knowledge to facilitate binning accuracy.</p>
<p>News: Python version of COCACOLA is available now!</p><p>Address of the bookmark: <a href="https://github.com/younglululu/COCACOLA" rel="nofollow">https://github.com/younglululu/COCACOLA</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<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/31552/multigenome-assembly</guid>
	<pubDate>Tue, 14 Mar 2017 04:41:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31552/multigenome-assembly</link>
	<title><![CDATA[Multigenome assembly]]></title>
	<description><![CDATA[<p>This project contains scripts and tutorials on how to assemble individual microbial genomes from metagenomes, as described in:</p>
<p>Genome sequences of rare, uncultured bacteria obtained by differential coverage binning of multiple metagenomes</p>
<p>Mads Albertsen, Philip Hugenholtz, Adam Skarshewski, Gene W. Tyson, K&aring;re L. Nielsen and Per .H. Nielsen</p>
<p>Nature Biotechnology 2013, doi:&nbsp;<a href="http://www.nature.com/nbt/journal/vaop/ncurrent/abs/nbt.2579.html">10.1038/nbt.2579</a></p>
<p>See the associated&nbsp;<a href="http://madsalbertsen.github.io/multi-metagenome/">online guide</a>&nbsp;for detailed information.</p>
<p>https://github.com/MadsAlbertsen/multi-metagenome</p><p>Address of the bookmark: <a href="https://github.com/MadsAlbertsen/multi-metagenome" rel="nofollow">https://github.com/MadsAlbertsen/multi-metagenome</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/32719/download-assemblies-from-ncbi</guid>
	<pubDate>Mon, 15 May 2017 06:02:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/32719/download-assemblies-from-ncbi</link>
	<title><![CDATA[Download assemblies from NCBI]]></title>
	<description><![CDATA[<p>A new &ldquo;Download assemblies&rdquo; button is now available in the&nbsp;<a href="https://www.ncbi.nlm.nih.gov/assembly" target="_blank">Assembly</a>&nbsp;database. This makes it easy to download data for multiple genomes without having to write scripts.</p><p>For example, you can run a search in Assembly and use check boxes (see left side of screenshot below) to refine the set of genome assemblies of interest. Then, just open the &ldquo;Download assemblies&rdquo; menu, choose the source database (<a href="https://www.ncbi.nlm.nih.gov/genbank/" target="_blank">GenBank</a>&nbsp;or&nbsp;<a href="https://www.ncbi.nlm.nih.gov/refseq/" target="_blank">RefSeq</a>), choose the file type, and start the download. An archive file will be saved to your computer that can be expanded into a folder containing your selected genome data files.</p><p><img src="https://ncbiinsights.files.wordpress.com/2017/05/download_button.jpg?w=584" alt="image" width="584" height="444" style="border: 0px; border: 0px;"></p><p>&nbsp;</p><p>More at&nbsp;https://ncbiinsights.ncbi.nlm.nih.gov/2017/05/08/genome-data-download-made-easy/</p>]]></description>
	<dc:creator>Bulbul</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32849/car-reconstructing-contiguous-regions-of-an-ancestral-genome</guid>
	<pubDate>Thu, 18 May 2017 05:24:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32849/car-reconstructing-contiguous-regions-of-an-ancestral-genome</link>
	<title><![CDATA[CAR: Reconstructing Contiguous Regions of an Ancestral Genome]]></title>
	<description><![CDATA[<div id="abstract-1">
<p id="p-5">We describe a new method for predicting the ancestral order and orientation of those intervals from their observed adjacencies in modern species. We combine the results from this method with data from chromosome painting experiments to produce a map of an early mammalian genome that accounts for 96.8% of the available human genome sequence data. The precision is further increased by mapping inversions as small as 31 bp. Analysis of the predicted evolutionary breakpoints in the human lineage confirms certain published observations but disagrees with others. Although only a few mammalian genomes are currently sequenced to high precision, our theoretical analyses and computer simulations indicate that our results are reasonably accurate and that they will become highly accurate in the foreseeable future. Our methods were developed as part of a project to reconstruct the genome sequence of the last ancestor of human, dogs, and most other placental mammals;</p>
</div><p>Address of the bookmark: <a href="http://www.bx.psu.edu/miller_lab/car/" rel="nofollow">http://www.bx.psu.edu/miller_lab/car/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34488/scripts-for-the-analysis-of-hgt-in-genome-sequence-data</guid>
	<pubDate>Wed, 29 Nov 2017 16:44:10 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34488/scripts-for-the-analysis-of-hgt-in-genome-sequence-data</link>
	<title><![CDATA[Scripts for the analysis of HGT in genome sequence data.]]></title>
	<description><![CDATA[<p><span>Scripts for the analysis of HGT in genome sequence data</span></p><p>Address of the bookmark: <a href="https://github.com/reubwn/hgt" rel="nofollow">https://github.com/reubwn/hgt</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35131/giggle-a-search-engine-for-large-scale-integrated-genome-analysis</guid>
	<pubDate>Wed, 10 Jan 2018 03:10:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35131/giggle-a-search-engine-for-large-scale-integrated-genome-analysis</link>
	<title><![CDATA[GIGGLE: a search engine for large-scale integrated genome analysis]]></title>
	<description><![CDATA[<p><span>GIGGLE is a genomics search engine that identifies and ranks the significance of genomic loci shared between query features and thousands of genome interval files. GIGGLE (</span><a href="https://github.com/ryanlayer/giggle">https://github.com/ryanlayer/giggle</a><span>) scales to billions of intervals and is over three orders of magnitude faster than existing methods. Its speed extends the accessibility and utility of resources such as ENCODE, Roadmap Epigenomics, and GTEx by facilitating data integration and hypothesis generation.</span></p>
<p>https://www.nature.com/articles/nmeth.4556</p><p>Address of the bookmark: <a href="https://github.com/ryanlayer/giggle" rel="nofollow">https://github.com/ryanlayer/giggle</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39441/snakepipes-a-toolkit-based-on-snakemake-and-python-for-analysis-of-ngs-data</guid>
	<pubDate>Thu, 30 May 2019 04:06:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39441/snakepipes-a-toolkit-based-on-snakemake-and-python-for-analysis-of-ngs-data</link>
	<title><![CDATA[snakepipes: A toolkit based on snakemake and python for analysis of NGS data]]></title>
	<description><![CDATA[<p><span><span>snakePipes are flexible and powerful workflows built using&nbsp;</span><a href="https://github.com/maxplanck-ie/snakepipes/blob/master/snakemake.readthedocs.io">snakemake</a><span>&nbsp;that simplify the analysis of NGS data.</span></span></p>
<ul>
<li>DNA-mapping*</li>
<li>ChIP-seq*</li>
<li>RNA-seq*</li>
<li>ATAC-seq*</li>
<li>scRNA-seq</li>
<li>Hi-C</li>
<li>Whole Genome Bisulfite Seq/WGBS</li>
</ul>
<p><span>(*Also available in "allele-specific" mode)</span></p>
<p><span>snakePipes can be installed via conda : </span></p>
<p><span>'conda install -c mpi-ie -c bioconda -c conda-forge snakePipes'. </span></p>
<p><span>Source code (</span><a href="https://github.com/maxplanck-ie/snakepipes" target="">https://github.com/maxplanck-ie/snakepipes</a><span>) and documentation (</span><a href="https://snakepipes.readthedocs.io/en/latest/" target="">https://snakepipes.readthedocs.io/en/latest/</a><span>) are available online.</span></p><p>Address of the bookmark: <a href="https://github.com/maxplanck-ie/snakepipes" rel="nofollow">https://github.com/maxplanck-ie/snakepipes</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40948/bio7-an-integrated-development-environment-for-ecological-modeling-scientific-image-analysis-and-statistical-analysis</guid>
	<pubDate>Fri, 07 Feb 2020 23:32:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40948/bio7-an-integrated-development-environment-for-ecological-modeling-scientific-image-analysis-and-statistical-analysis</link>
	<title><![CDATA[Bio7: an integrated development environment for ecological modeling, scientific image analysis and statistical analysis]]></title>
	<description><![CDATA[<p><span>The application Bio7 is an integrated development environment for ecological modeling, scientific image analysis and statistical analysis. The application itself is based on an RCP-Eclipse-Environment (Rich-Client-Platform) which offers a huge flexibility in configuration and extensibility because of its plug-in structure and the possibility of customization.</span></p>
<p><a href="https://bio7.org/about/">https://bio7.org/about/</a></p><p>Address of the bookmark: <a href="https://bio7.org/home-2/" rel="nofollow">https://bio7.org/home-2/</a></p>]]></description>
	<dc:creator>Nidhi Rajput</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/40228/bioinformatics-services-cro-services</guid>
	<pubDate>Wed, 06 Nov 2019 00:33:11 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/40228/bioinformatics-services-cro-services</link>
	<title><![CDATA[Bioinformatics Services / CRO Services]]></title>
	<description><![CDATA[<p>RASA is set to provide premium technical and scientific services in a form of solutions, product development and training. .We are also very proficient in providing the high quality Research &amp; Development services in life science informatics field like Next Generation Sequencing (NGS) Data Analysis,Computational Drug Discovery, Bioinformatics, Chemo-informatics and BIO-IT.</p><p>RASA offers faster, better and cost effective cutting edge technology solutions to chemical and life science research and industry. We provide our customers with A seamless model of wide expertise and comprehensive platforms. Our Value is to take our customers</p>]]></description>
	<dc:creator>RASA Life Sciences</dc:creator>
</item>

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