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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/39372?offset=80</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38489/biotite-a-general-framework-for-computational-biology</guid>
	<pubDate>Mon, 17 Dec 2018 18:52:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38489/biotite-a-general-framework-for-computational-biology</link>
	<title><![CDATA[Biotite: A general framework for computational biology]]></title>
	<description><![CDATA[<p><span>The package is open source and freely available at GitHub (</span><span><a href="https://github.com/biotite-dev/biotite" target="_blank">https://github.com/biotite-dev/biotite</a></span><span>). This package is simple to use especially for the beginners in programming and computationally efficient because of the implementation of Numpy and Cython.&nbsp;Biotite consists of four sub packages: sequence, structure, databases, and application. The&nbsp;</span><em>sequence</em><span>&nbsp;and&nbsp;</span><em>structure</em><span>&nbsp;modules serve for the analysis of sequence and structural data analysis respectively,&nbsp;</span><em>database</em><span>&nbsp;downloads files from the other databases such as RCSB PDB, and&nbsp;</span><em>application</em><span>&nbsp;provides interface for external software.&nbsp;</span></p>
<p><span><span>The&nbsp;</span><em>Biotite</em><span>&nbsp;package bundles popular tasks in computational biology into an unifying framework, which is easy to use on the one hand side, but is also computationally efficient due to intensive usage of&nbsp;</span><em>NumPy</em><span>&nbsp;and&nbsp;</span><em>Cython</em><span>. This package focuses on working with sequence and structure data and supports various file formats and analysis and manipulation functions.</span></span></p><p>Address of the bookmark: <a href="https://github.com/biotite-dev/biotite" rel="nofollow">https://github.com/biotite-dev/biotite</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42201/rosettaantibodydesign-rabd-a-general-framework-for-computational-antibody-design</guid>
	<pubDate>Sun, 20 Sep 2020 06:03:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42201/rosettaantibodydesign-rabd-a-general-framework-for-computational-antibody-design</link>
	<title><![CDATA[RosettaAntibodyDesign (RAbD): A general framework for computational antibody design]]></title>
	<description><![CDATA[<p><strong>RosettaAntibodyDesign (RAbD)</strong>&nbsp;is a generalized framework for the design of antibodies, in which a user can easily tailor the run to their project needs.&nbsp;<strong>The algorithm is meant to sample the diverse sequence, structure, and binding space of an antibody-antigen complex.</strong>&nbsp;It can be used for a multitude of project types, from denovo design to redesigns that improve binding affinity, optimize stability, or manipulate function.</p>
<p>The framework is based on rigorous bioinformatic analysis and rooted very much on our&nbsp;<a href="https://www.ncbi.nlm.nih.gov/pubmed/21035459">recent clustering</a>&nbsp;of antibody CDR regions. It uses the&nbsp;<strong>North/Dunbrack CDR definition</strong>&nbsp;as outlined in the North/Dunbrack clustering paper.</p>
<p>More at</p>
<p>https://www.rosettacommons.org/docs/latest/application_documentation/antibody/RosettaAntibodyDesign</p>
<p>https://bio-jade.readthedocs.io/en/latest/installation.html</p><p>Address of the bookmark: <a href="https://www.rosettacommons.org/docs/latest/application_documentation/antibody/RosettaAntibodyDesign" rel="nofollow">https://www.rosettacommons.org/docs/latest/application_documentation/antibody/RosettaAntibodyDesign</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/2631/what-junk-dna-it%E2%80%99s-an-operating-system</guid>
	<pubDate>Mon, 19 Aug 2013 15:24:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/2631/what-junk-dna-it%E2%80%99s-an-operating-system</link>
	<title><![CDATA[What Junk DNA? It’s an Operating System]]></title>
	<description><![CDATA[<p>The report adds to growing experimental support for the idea that all that extra stuff in the human genes, once referred to as &ldquo;junk DNA,&rdquo; is more than functionless, space-filling material that happens to make up nearly 98% of the genome. The paper adds to a growing body of knowledge establishing a considerable role for this material in the regulation of gene expression and its potential role in human disease.</p><p>Address of the bookmark: <a href="http://www.genengnews.com/keywordsandtools/print/3/32115/" rel="nofollow">http://www.genengnews.com/keywordsandtools/print/3/32115/</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/6720/rna-sequencing-helps-identify-functional-variants-from-gwas</guid>
	<pubDate>Fri, 22 Nov 2013 21:33:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/6720/rna-sequencing-helps-identify-functional-variants-from-gwas</link>
	<title><![CDATA[RNA Sequencing Helps Identify Functional Variants from GWAS]]></title>
	<description><![CDATA[<p><span>For Alzheimer&rsquo;s and other complex disorders, mining the genome for disease-associated variants is no longer the obstacle. The challenge nowadays is figuring out how the identified loci relate to disease. As reported last month in Nature and its associated journals, advances in high-throughput RNA sequencing are providing new tools for understanding how disease loci influence gene expression&mdash;a starting point for understanding their connection to pathogenesis.</span></p><p>Address of the bookmark: <a href="http://schizophreniaforum.org/new/detail.asp?id=1953" rel="nofollow">http://schizophreniaforum.org/new/detail.asp?id=1953</a></p>]]></description>
	<dc:creator>Andaleeb</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/17843/pathway-analysis</guid>
	<pubDate>Fri, 03 Oct 2014 08:51:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/17843/pathway-analysis</link>
	<title><![CDATA[Pathway Analysis]]></title>
	<description><![CDATA[<p>Pathway Analysis is usually performed with aim to enrich the genes with their functional information and reveal the underlying biological mechanisms pursue by genes. Pathway Analysis is not only limited to what biological pathways a particular set of expressed genes follow but also to disclose the relationships between these genes. With availability of more genomics, transcriptomics and proteomics data, interactions between genes involve in multiple pathways become more clear and also relationships between the genes, their transcripts, and their gene products. However, existing tools and dbs mainly based on knowledge driven approach in which pathways will be identified by finding the correlation between the&nbsp;<span>information in one of the pathway knowledge databases (KEGG,Reactome,Panther,BioCarta, Panther,GO,NCI,WikiPathways,etc) and gene expression result for a specific conditions for instance tumor, obesity , cold resistant crops/plants, etc.</span></p><p><span><strong>Introductory Articles/ppt/sources</strong>:</span></p><p><a href="http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002375"><span>http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002375</span></a></p><p><a href="http://bioinformatics.mdanderson.org/MicroarrayCourse/Lectures09/Pathway%20Analysis.pdf"><span>http://bioinformatics.mdanderson.org/MicroarrayCourse/Lectures09/Pathway%20Analysis.pdf</span></a></p><p><a href="http://gettinggeneticsdone.blogspot.de/2012/03/pathway-analysis-for-high-throughput.html"><span>http://gettinggeneticsdone.blogspot.de/2012/03/pathway-analysis-for-high-throughput.html</span></a></p><p><a href="http://davetang.org/muse/tag/pathway/"><span>http://davetang.org/muse/tag/pathway/</span></a></p><p><a href="https://www.biostars.org/p/42219/"><span>https://www.biostars.org/p/42219/</span></a></p><p><a href="http://bioinformatics.ca//files/public/Pathways_2014_Module4_v2.pdf"><span>http://bioinformatics.ca//files/public/Pathways_2014_Module4_v2.pdf</span></a></p><p><a href="http://bioinformatics.ca//files/public/Pathways_2014_Module2.pdf"><span>http://bioinformatics.ca//files/public/Pathways_2014_Module2.pdf</span></a></p><p><span><strong>Impotant Database and Tools</strong>:</span></p><p>GeneMANIA, Cytoscape,&nbsp;<a href="http://www.ingenuity.com/products/ipa">IPA</a>&nbsp;and <a href="http://thomsonreuters.com/metacore/">Metacore</a> (Commerical ),&nbsp;<span>Pathway Commons, Reactome ,Panther, BioCyc, WikiPathways, Pathvisio, KEGG, NCI, Stringdb, Amigo,&nbsp;<span>WebGestalt ,<span>ConsensusPathDB ,GSEA,Blast2go</span></span></span></p><p><span><strong>Popular R based tools</strong>:</span></p><p><span>Reactome.db, ReactomePA, ClusterProfiler, Gage, SPIA, topGO, Pathview,DOSE,GOStat</span></p><p><span><strong>More</strong>:</span></p><p><a href="http://www.bioconductor.org/help/search/index.html?q=Enrichment+analysis+"><span>http://www.bioconductor.org/help/search/index.html?q=Enrichment+analysis+</span></a></p><p>&nbsp;</p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/25993/hoffman-lab</guid>
  <pubDate>Tue, 12 Jan 2016 02:47:41 -0600</pubDate>
  <link></link>
  <title><![CDATA[Hoffman Lab]]></title>
  <description><![CDATA[
<p>They develop machine learning techniques to better understand chromatin biology. These models and algorithms transform high-dimensional functional genomics data into interpretable patterns and lead to new biological insight.</p>

<p>https://www.pmgenomics.ca/hoffmanlab/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32631/barrnap-bacterial-ribosomal-rna-predictor</guid>
	<pubDate>Fri, 12 May 2017 09:24:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32631/barrnap-bacterial-ribosomal-rna-predictor</link>
	<title><![CDATA[Barrnap: Bacterial ribosomal RNA predictor]]></title>
	<description><![CDATA[<p>Barrnap predicts the location of ribosomal RNA genes in genomes. It supports bacteria (5S,23S,16S), archaea (5S,5.8S,23S,16S), mitochondria (12S,16S) and eukaryotes (5S,5.8S,28S,18S).</p>
<p>It takes FASTA DNA sequence as input, and write GFF3 as output. It uses the new NHMMER tool that comes with HMMER 3.1 for HMM searching in RNA:DNA style. NHMMER binaries for 64-bit Linux and Mac OS X are included and will be auto-detected. Multithreading is supported and one can expect roughly linear speed-ups with more CPUs.&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/tseemann/barrnap" rel="nofollow">https://github.com/tseemann/barrnap</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37650/p-rna-scaffolder-a-fast-and-accurate-genome-scaffolder-using-paired-end-rna-sequencing-reads</guid>
	<pubDate>Fri, 07 Sep 2018 05:19:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37650/p-rna-scaffolder-a-fast-and-accurate-genome-scaffolder-using-paired-end-rna-sequencing-reads</link>
	<title><![CDATA[P_RNA_scaffolder: a fast and accurate genome scaffolder using paired-end RNA-sequencing reads]]></title>
	<description><![CDATA[<p><span>P_RNA_scaffolder is a novel scaffolding tool using Pair-end RNA-seq to scaffold genome fragments. The method is suitable for most genomes. The program could utilize Illumina Paired-end RNA-sequencing reads from target speciesies. Our method provides another practical alternative to existing mate-pair_based approaches or other Protein-based approaches (for instance,&nbsp;</span><a href="http://www.fishbrowser.org/software/PEP_scaffolder/">PEP_scaffolder&nbsp;</a><span>) for scaffolding genome sequences. The most important feature of this method is to improve the completeness of gene regions and long-coding gene regions (for instance,&nbsp;</span><a href="http://circrna.org/">circRNA</a><span>).</span></p><p>Address of the bookmark: <a href="http://www.fishbrowser.org/software/P_RNA_scaffolder/#" rel="nofollow">http://www.fishbrowser.org/software/P_RNA_scaffolder/#</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41825/hnadock-a-nucleic-acid-docking-server-for-modeling-rnadna%E2%80%93rnadna-3d-complex-structures</guid>
	<pubDate>Thu, 04 Jun 2020 23:19:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41825/hnadock-a-nucleic-acid-docking-server-for-modeling-rnadna%E2%80%93rnadna-3d-complex-structures</link>
	<title><![CDATA[HNADOCK: a nucleic acid docking server for modeling RNA/DNA–RNA/DNA 3D complex structures]]></title>
	<description><![CDATA[<p><span>The HNADOCK server is to predict the binding complex structure between two nucleic acid molecules through a hierarchical docking algorihtm of an FFT-based global search strategy and an intrinsic scoring function for nucleic acid interactions. Users are required to provide the three-dimensional (3D) structures of the two molecules to be docked.&nbsp;</span></p><p>Address of the bookmark: <a href="http://huanglab.phys.hust.edu.cn/hnadock/" rel="nofollow">http://huanglab.phys.hust.edu.cn/hnadock/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43997/tools-for-rna-classification</guid>
	<pubDate>Tue, 08 Nov 2022 03:39:11 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43997/tools-for-rna-classification</link>
	<title><![CDATA[Tools for RNA classification]]></title>
	<description><![CDATA[<p><span>barrnap</span>&nbsp;-&nbsp;<a href="https://github.com/tseemann/barrnap" target="_blank">https://github.com/tseemann/barrnap</a></p><p><span>CPAT</span>&nbsp;-&nbsp;<a href="https://github.com/liguowang/cpat" target="_blank">https://github.com/liguowang/cpat</a>,&nbsp;<a href="http://lilab.research.bcm.edu/" target="_blank">http://lilab.research.bcm.edu/</a>&nbsp;(web server)</p><p><span>CPC2</span>&nbsp;-&nbsp;<a href="https://github.com/gao-lab/CPC2_standalone" target="_blank">https://github.com/gao-lab/CPC2_standalone</a>,&nbsp;<a href="http://cpc2.gao-lab.org/" target="_blank">http://cpc2.gao-lab.org/</a>&nbsp;(web server)</p><p><span>Infernal</span>&nbsp;-&nbsp;<a href="http://eddylab.org/infernal/" target="_blank">http://eddylab.org/infernal/</a>,&nbsp;<a href="https://github.com/EddyRivasLab/infernal" target="_blank">https://github.com/EddyRivasLab/infernal</a></p><p><span>NCBI RefSeq</span>&nbsp;-&nbsp;<a href="https://www.ncbi.nlm.nih.gov/refseq/" target="_blank">https://www.ncbi.nlm.nih.gov/refseq/</a></p><p><span>Rfam</span>&nbsp;-&nbsp;<a href="http://rfam.xfam.org/" target="_blank">http://rfam.xfam.org/</a>,&nbsp;<a href="https://docs.rfam.org/en/latest/index.html" target="_blank">https://docs.rfam.org/en/latest/index.html</a></p><p><span>SILVA</span>&nbsp;-&nbsp;<a href="https://www.arb-silva.de/" target="_blank">https://www.arb-silva.de/</a></p><p><span>RNAmmer</span>&nbsp;-&nbsp;<a href="http://www.cbs.dtu.dk/services/RNAmmer/" target="_blank">http://www.cbs.dtu.dk/services/RNAmmer/</a>&nbsp;(web server, standalone download link)</p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>

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