<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/32379?offset=90</link>
	<atom:link href="https://bioinformaticsonline.com/related/32379?offset=90" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/8798/list-of-gene-ontology-software-and-tools</guid>
	<pubDate>Sun, 09 Mar 2014 14:48:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/8798/list-of-gene-ontology-software-and-tools</link>
	<title><![CDATA[List of gene ontology software and tools]]></title>
	<description><![CDATA[<p>The Gene Ontology (GO) is a set of associations from biological phrases to specific genes that are either chosen by trained curators or generated automatically. GO is designed to rigorously encapsulate the known relationships between biological terms and and all genes that are instances of these terms. These Gene Ontology has become an extremely useful tool for the analysis of genomic data and structuring of biological knowledge. Several excellent software tools for navigating the gene ontology have been developed.</p><p><img src="http://ohnosequences.com/images/GoSlimBlog.svg" alt="image" width="500" height="380" style="border: 0px; border: 0px;"></p><p>The GO provides core biological knowledge representation for modern biologists, whether computationally or experimentally based. GO resources include biomedical ontologies that cover molecular domains of all life forms as well as extensive compilations of gene product annotations to these ontologies that provide largely species-neutral, comprehensive statements about what gene products do. Although extensively used in data analysis workflows, and widely incorporated into numerous data analysis platforms and applications, the general user of GO resources often misses fundamental distinctions about GO structures, GO annotations, and what can and can not be extrapolated from GO resources. Here are ten quick tips for using the Gene Ontology.</p><p>Read "Ten Quick Tips for Using the Gene Ontology" at http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1003343</p><p>Following are the most commonly used old and new GO term enrichment determination tools. These tools are recommended to people working in a wet-lab.</p><p><strong>CLASSIFI (Department of Pathology, UT Southwestern Medical Center)</strong></p><p>CLASSIFI (Cluster Assignment for Biological Inference) is a data-mining tool that can be used to identify significant co-clustering of genes with similar functional properties (e.g. cellular response to DNA damage). Briefly, CLASSIFI uses the Gene OntologyTM (GO) gene annotation scheme to define the functional properties of all genes/probes in a microarray data set, and then applies a cumulative hypergeometric distribution analysis to determine if any statistically significant gene ontology co-clustering has occurred.</p><p><a href="http://pathcuric1.swmed.edu/pathdb/classifi.html">http://pathcuric1.swmed.edu/pathdb/classifi.html</a></p><p><strong>EasyGO (China Agricultural University)</strong></p><p>EasyGO is designed to automate enrichment job for experimental biologists to identify enriched Gene Ontology (GO) terms in a list of microarray probe sets or gene identifiers (with expression information for PAGE analysis). Also EasyGO is also a GO annotation database, especially focus on agronomical species, supporting 30 species. It is user friendly, with advanced result browsing format and in-time update.</p><p><a href="http://bioinformatics.cau.edu.cn/neweasygo/">http://bioinformatics.cau.edu.cn/neweasygo/</a></p><p><a href="http://bioinformatics.cau.edu.cn/easygo/">http://bioinformatics.cau.edu.cn/easygo/</a></p><p><strong>g:GOSt (Institute of Computer Science, University of Tartu)</strong></p><p>g:GOSt retrieves most significant Gene Ontology (GO) terms, KEGG and REACTOME pathways, and TRANSFAC motifs to a user-specified group of genes, proteins or microarray probes. g:GOSt also allows analysis of ranked or ordered lists of genes, visual browsing of GO graph structure, interactive visualisation of retrieved results, and many other features. Multiple testing corrections are applied to extract only statistically important results.</p><p><a href="http://biit.cs.ut.ee/gprofiler/">http://biit.cs.ut.ee/gprofiler/</a></p><p><strong>DAVID</strong> : Gene Functional Classification (Laboratory of Immunopathogenesis and Bioinformatics, NIAID)</p><p>The Functional Classification Tool provides a rapid means to organize large lists of genes into functionally related groups to help unravel the biological content captured by high throughput technologies.</p><p><a href="http://david.abcc.ncifcrf.gov/gene2gene.jsp">http://david.abcc.ncifcrf.gov/gene2gene.jsp</a></p><p><a href="http://david.abcc.ncifcrf.gov/">http://david.abcc.ncifcrf.gov/</a></p><p>API <a href="https://github.com/chrisamiller/davidapi">https://github.com/chrisamiller/davidapi</a></p><p><strong>GOEAST</strong> (Institute of Genetics and Developmental Biology, Chinese Academy of Sciences)</p><p>GOEAST is web based software toolkit providing easy to use, visualizable, comprehensive and unbiased Gene Ontology (GO) analysis for high-throughput experimental results, especially for results from microarray hybridization experiments. The main function of GOEAST is to identify significantly enriched GO terms among give lists of genes using accurate statistical methods.</p><p><a href="http://omicslab.genetics.ac.cn/GOEAST/">http://omicslab.genetics.ac.cn/GOEAST/</a></p><p><strong>GOstat</strong> (Walter and Eliza Hall Institute of Medical Research)</p><p>Find statistically overrepresented GO terms within a group of genes</p><p><a href="http://gostat.wehi.edu.au/">http://gostat.wehi.edu.au/</a></p><p><strong>GOrilla</strong> (Technion - Laboratory of Computational Biology , Israel Institute of Technology)</p><p>GOrilla is a tool for identifying and visualizing enriched GO terms in ranked lists of genes.<br /> It uses two approaches, first by searching for enriched GO terms that appear densely at the top of a ranked list of genes&nbsp; or by searching for enriched GO terms in a target list of genes compared to a background list of genes.</p><p><a href="http://cbl-gorilla.cs.technion.ac.il/">GOrilla</a> makes nice pictures !!!!</p><p><a href="http://cbl-gorilla.cs.technion.ac.il/">http://cbl-gorilla.cs.technion.ac.il/</a></p><p><strong>Gene Ontology for Functional Analysis (GOFFA)</strong></p><p>GOFFA is a tool developed for ArrayTrack&trade; that takes a list of genes and identifies terms in Gene Ontology (GO) disclaimer icon associated with those genes.</p><p>It provides several tools to view/access the GO term hierarchy, full listing of GO terms annotated with the genes associated with a given term with statically useful report.</p><p><a href="http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm233315.htm">http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm233315.htm</a></p><p><strong>GOAT</strong> (The University of Manchester)</p><p>The aim of the GOAT project is to create an application that will guide users, especially biomedical researchers, in the annotation of gene products with terms from the <a href="http://www.geneontology.org">Gene Ontology</a>.</p><p><a href="http://goat.man.ac.uk/">http://goat.man.ac.uk/</a></p><p>Script <a href="https://github.com/tanghaibao/goatools/">https://github.com/tanghaibao/goatools/</a></p><p><strong>REVIGO</strong> ( Rudjer Boskovic Institute, Croatia)</p><p>REViGO is a web server that can take long lists of Gene Ontology terms and summarize them by removing redundant GO terms. The remaining terms can be visualized in semantic similarity-based scatterplots, interactive graphs, or tag clouds.</p><p><a href="http://revigo.irb.hr/">http://revigo.irb.hr/</a></p><p><strong>QuickGo</strong> (EMBL-EBI Institute)</p><p>It uses extensive computational filters to allow the generation of specific subsets of GO annotations, mapped to sequence identifiers of your choice. Then GO slims are used which is collective list of GO full set of terms available from the Gene Ontology project.</p><p><a href="http://www.ebi.ac.uk/QuickGO/">http://www.ebi.ac.uk/QuickGO/</a></p><p><strong>GOLEM</strong></p><p>An interactive graph-based gene-ontology navigation and analysis tool. GOLEM is a userful tool which allows the viewer to navigate and explore a local portion of the <a href="http://www.geneontology.org/">Gene Ontology</a> (GO) hierarchy.</p><p><a href="http://reducio.princeton.edu/GOLEM/">http://reducio.princeton.edu/GOLEM/</a></p><p><strong>BGI Web Gene Ontology (WEGO)</strong> Annotation Plot (Beijing Genomics Institute)</p><p>WEGO () is a useful tool for plotting GO annotation results. It has been widely used in many important biological research projects, such as the rice genome project [<a href="http://wego.genomics.org.cn/pubs/rice_indica.pdf">Yu, J. et al. Science 296, 79-92 (2002);</a> <a href="http://wego.genomics.org.cn/pubs/rice_finish.pdf">Yu, J. et al. PLoS Biol 3, e38 (2005)</a>] and the silkworm genome project [<a href="http://wego.genomics.org.cn/pubs/combine_silkworm.pdf">Xia, Q. et al. Science 306, 1937-40 (2004)</a>]. It has become one of the daily tools for downstream gene annotation analysis, especially when performing comparative genomics tasks. WEGO along with two other tools, namely <a href="http://wego.genomics.org.cn/cgi-bin/wego/External2GO.pl">External to GO Query</a> and <a href="http://wego.genomics.org.cn/cgi-bin/wego/GOArchive.pl">GO Archive Query</a>, are freely available for all users. Any suggestions are welcome at <a href="mailto:%20wego@genomics.org.cn">wego@genomics.org.cn</a>. Here is a sample output generated by WEGO</p><p><a href="http://wego.genomics.org.cn/cgi-bin/wego/index.pl">http://wego.genomics.org.cn/cgi-bin/wego/index.pl</a></p><p><strong>GeneGO MetaCore</strong> (MIT)</p><p>GeneGo is a leading provider of data mining &amp; analysis solutions in systems biology. MetaCore, GeneGo's flapship product, is an integrated software suite for functional analysis of experimental data. MetaCore is based on a curated database of human protein-protein, protein-DNA interactions, transcription factors, signaling and metabolic pathways, disease and toxicity, and the effects of bioactive molecules.</p><p><a href="https://portal.genego.com/">https://portal.genego.com/</a></p><p><strong>GOEx</strong> (Stony Brook University)</p><p>GOEx facilitates organism-specific studies by leveraging GO and providing a rich graphical user interface. It is a simple to use tool, specialized for biologists who wish to analyze spectral counting data from shotgun proteomics.</p><p><a href="http://pcarvalho.com/patternlab">http://pcarvalho.com/patternlab</a></p><p><strong>GOssTo</strong></p><p>GOssTo and GOssToWeb are tools to calculate the <a href="https://en.wikipedia.org/wiki/Semantic_similarity#Biomedical_Informatics">semantic similarity</a> between genes or terms in the <a href="http://www.geneontology.org/">Gene Ontology</a>.</p><p><a href="http://www.paccanarolab.org/gosstoweb/">http://www.paccanarolab.org/gosstoweb/</a></p><p><strong>GO Workbench</strong></p><p>The Gene Ontology Analysis Viewer allows direct browsing of the Gene Ontology, and also the visualization of GO Term analysis results.</p><p><a href="http://wiki.c2b2.columbia.edu/workbench/index.php/Gene_Ontology_Viewer">http://wiki.c2b2.columbia.edu/workbench/index.php/Gene_Ontology_Viewer</a></p><p>Some other useful list of GO software and tools is available at <a href="http://www.geneontology.org/GO.tools.shtml#browser">http://www.geneontology.org/GO.tools.shtml#browser</a></p><p>Yet another useful webpage with list of GO tools at <a href="http://neurolex.org/wiki/Category:Resource:Gene_Ontology_Tools">http://neurolex.org/wiki/Category:Resource:Gene_Ontology_Tools</a></p><p>&nbsp;</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41863/ppai-a-web-server-for-predicting-protein-aptamer-interactions</guid>
	<pubDate>Fri, 12 Jun 2020 07:26:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41863/ppai-a-web-server-for-predicting-protein-aptamer-interactions</link>
	<title><![CDATA[PPAI: a web server for predicting protein-aptamer interactions]]></title>
	<description><![CDATA[<p><span>PPAI can query aptamers and proteins, predict aptamers and predict protein-aptamer interactions in batch mode precisely and efficiently, which would be a novel bioinformatics tool for the research of protein-aptamer interactions. PPAI web-server is freely available at&nbsp;</span><a href="http://39.96.85.9/PPAI">http://39.96.85.9/PPAI</a></p><p>Address of the bookmark: <a href="http://39.96.85.9/PPAI/" rel="nofollow">http://39.96.85.9/PPAI/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/10409/check-linux-server-configuration</guid>
	<pubDate>Tue, 06 May 2014 01:10:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/10409/check-linux-server-configuration</link>
	<title><![CDATA[Check Linux server configuration !!]]></title>
	<description><![CDATA[<p>Bioinformatician uses servers for computational analysis. Sometime we need to check the server details before running our programs or tools. Here I am showing some basic commands using them you can gather the system/server information.<br /><br />To check what version of Operating System is installed on the server you can use the following commands:-<br />&nbsp;=================================================================<br />1.cat /etc/issue<br />[root@localhost ~]# cat /etc/issue<br />Red Hat Enterprise Linux Server release 5.5 (Tikanga)<br />Kernel \r on an \m<br /><br />2.cat /etc/redhat-release<br />[root@localhost ~]# cat /etc/redhat-release<br />Red Hat Enterprise Linux Server release 5.5 (Tikanga)<br /><br /><br />3.lsb_release -a<br />[root@localhost ~]# lsb_release -a<br />LSB Version:&nbsp;&nbsp;&nbsp; :core-3.1-ia32:core-3.1-noarch:graphics-3.1-ia32:graphics-3.1-noarch<br />Distributor ID: RedHatEnterpriseServer<br />Description:&nbsp;&nbsp;&nbsp; Red Hat Enterprise Linux Server release 5.5 (Tikanga)<br />Release:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 5.5<br />Codename:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Tikanga<br /><br /><br /><br />To check whether the operating system is 32 or 64bit:-<br />================================<br /># uname -i<br />[root@localhost ~]# uname -i<br />i386<br />(i386 represents that server is having 32bit operating system)<br /><br />[root@localhost ~]# uname -i<br />x86_64<br />(x86_64 represents that server is having 64bit operating system)<br /><br />To see the processor/CPU information:-<br />=============================<br /># cat /proc/cpuinfo<br />[root@localhost ~] cat /proc/cpuinfo<br />processor&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 0<br />vendor_id&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : GenuineIntel<br />cpu family&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 6<br />model&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 15<br />model name&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : Intel(R) Xeon(R) CPU&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 5130&nbsp; @ 2.00GHz<br />stepping&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 6<br />cpu MHz&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 1995.087<br />cache size&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 4096 KB<br />physical id&nbsp;&nbsp;&nbsp;&nbsp; : 0<br />siblings&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 2<br />core id&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 0<br />cpu cores&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 2<br />apicid&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 0<br />fdiv_bug&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : no<br />hlt_bug&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : no<br />f00f_bug&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : no<br />coma_bug&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : no<br />fpu&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : yes<br />fpu_exception&nbsp;&nbsp; : yes<br />cpuid level&nbsp;&nbsp;&nbsp;&nbsp; : 10<br />wp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : yes<br />flags&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe nx lm constant_tsc pni monitor ds_cpl vmx tm2 ssse3 cx16 xtpr lahf_lm<br />bogomips&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 3990.17<br />(Here processor number 0 indicates that the system is having one process(processor number starts with zero))<br /><br /><br /><br /><br />To check memory information:-<br />===========================<br /># free -m<br />[root@localhost ~]# free -m<br />&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; total&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; used&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; free&nbsp;&nbsp;&nbsp;&nbsp; shared&nbsp;&nbsp;&nbsp; buffers&nbsp;&nbsp;&nbsp;&nbsp; cached<br />Mem:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 5066&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 3513&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 1552&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 612&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 2319<br />-/+ buffers/cache:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 582&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 4484<br />Swap:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 1983&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 1983<br /><br /><br /><br /># cat /proc/meminfo<br />[root@localhost ~]# cat /proc/meminfo<br />MemTotal:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 5187752 kB<br />MemFree:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 1639300 kB<br />Buffers:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 627024 kB<br />Cached:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 2374944 kB<br />SwapCached:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0 kB<br />Active:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 2458788 kB<br />Inactive:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 920964 kB<br />HighTotal:&nbsp;&nbsp;&nbsp;&nbsp; 4325164 kB<br />HighFree:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 1561936 kB<br />LowTotal:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 862588 kB<br />LowFree:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 77364 kB<br />SwapTotal:&nbsp;&nbsp;&nbsp;&nbsp; 2031608 kB<br />SwapFree:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 2031608 kB<br />Dirty:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 704 kB<br />Writeback:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0 kB<br />AnonPages:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 377892 kB<br />Mapped:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 35328 kB<br />Slab:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 153036 kB<br />PageTables:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 6316 kB<br />NFS_Unstable:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0 kB<br />Bounce:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0 kB<br />CommitLimit:&nbsp;&nbsp; 4625484 kB<br />Committed_AS:&nbsp;&nbsp; 977132 kB<br />VmallocTotal:&nbsp;&nbsp; 116728 kB<br />VmallocUsed:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 4492 kB<br />VmallocChunk:&nbsp;&nbsp; 112124 kB<br />HugePages_Total:&nbsp;&nbsp;&nbsp;&nbsp; 0<br />HugePages_Free:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0<br />HugePages_Rsvd:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0<br />Hugepagesize:&nbsp;&nbsp;&nbsp;&nbsp; 2048 kB<br /><br /><br />To check the model and serial name of the server:-<br />=======================================<br />[root@localhost ~]#&nbsp; dmidecode | egrep -i "product name|Serial number"<br />Product Name: PowerEdge R710<br />Serial Number: AB8CDE1<br />&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp;<br /><br />To check the host name:-<br />=====================<br />[root@localhost ~]# uname -n<br />localhost<br /><br />[root@localhost ~]# hostname<br />localhost<br /><br />To check the kernel version:-<br />========================<br />[root@localhost ~]# uname -r<br />2.6.18-238.9.1.el5PAE</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/26827/kamaleshwar-singh-lab</guid>
  <pubDate>Fri, 25 Mar 2016 10:46:49 -0500</pubDate>
  <link></link>
  <title><![CDATA[Kamaleshwar Singh Lab]]></title>
  <description><![CDATA[
<p>The focus of Dr. Singh’s research and teaching is on the molecular mechanistic basis for environmental carcinogen-induced genetic (DNA damage) and epigenetic changes, and susceptibility to human cancer development</p>

<p>More at http://www.tiehh.ttu.edu/dr.-kamaleshwar-singh.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27427/rcircos-an-r-package-for-circos-2d-track-plots</guid>
	<pubDate>Fri, 20 May 2016 11:01:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27427/rcircos-an-r-package-for-circos-2d-track-plots</link>
	<title><![CDATA[RCircos: an R package for Circos 2D track plots]]></title>
	<description><![CDATA[<p>RCircos package provides a simple and flexible way to make Circos 2D track plots with R and could be easily integrated into other R data processing and graphic manipulation pipelines for presenting large-scale multi-sample genomic research data. It can also serve as a base tool to generate complex Circos images.</p>
<p>More at https://bitbucket.org/henryhzhang/rcircos/src</p><p>Address of the bookmark: <a href="https://bitbucket.org/henryhzhang/rcircos/src" rel="nofollow">https://bitbucket.org/henryhzhang/rcircos/src</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27463/bpipe-a-tool-for-running-and-managing-bioinformatics-pipelines</guid>
	<pubDate>Sat, 21 May 2016 22:42:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27463/bpipe-a-tool-for-running-and-managing-bioinformatics-pipelines</link>
	<title><![CDATA[Bpipe - a tool for running and managing bioinformatics pipelines]]></title>
	<description><![CDATA[<p>Bpipe provides a platform for running big bioinformatics jobs that consist of a series of processing stages - known as 'pipelines'.</p>
<ul>
<li>January 20th, 2016 - New! Bpipe 0.9.9 released!</li>
<li>Download <a href="http://download.bpipe.org/versions/bpipe-0.9.9.tar.gz">latest</a>, <a href="http://download.bpipe.org">all</a></li>
<li><a href="http://docs.bpipe.org">Documentation</a></li>
<li><a href="https://groups.google.com/forum/#%21forum/bpipe-discuss">Mailing List</a> (Google Group)</li>
</ul>
<p>Bpipe has been published in <a href="http://bioinformatics.oxfordjournals.org/content/early/2012/04/11/bioinformatics.bts167.abstract">Bioinformatics</a>! If you use Bpipe, please cite:</p>
<p><em>Sadedin S, Pope B &amp; Oshlack A, Bpipe: A Tool for Running and Managing Bioinformatics Pipelines, Bioinformatics</em></p><p>Address of the bookmark: <a href="http://docs.bpipe.org/" rel="nofollow">http://docs.bpipe.org/</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27479/biogps</guid>
	<pubDate>Mon, 23 May 2016 03:15:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27479/biogps</link>
	<title><![CDATA[BioGPS]]></title>
	<description><![CDATA[<p>A free&nbsp;<em>extensible</em>&nbsp;and&nbsp;<em>customizable</em>&nbsp;<strong>gene annotation portal</strong>, a complete resource for learning about&nbsp;<strong>gene and protein function</strong>.</p>
<p>http://biogps.org/#goto=welcome</p><p>Address of the bookmark: <a href="http://biogps.org/#goto=welcome" rel="nofollow">http://biogps.org/#goto=welcome</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27679/cluego</guid>
	<pubDate>Thu, 02 Jun 2016 09:51:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27679/cluego</link>
	<title><![CDATA[ClueGO]]></title>
	<description><![CDATA[<p>ClueGO is a Cytoscape plug-in that visualizes the non-redundant biological terms for large clusters of genes in a functionally grouped network and it can be used in combination with GOlorize.</p><p>Address of the bookmark: <a href="http://www.ici.upmc.fr/cluego/" rel="nofollow">http://www.ici.upmc.fr/cluego/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31278/metapred2cs</guid>
	<pubDate>Fri, 03 Mar 2017 05:15:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31278/metapred2cs</link>
	<title><![CDATA[MetaPred2CS]]></title>
	<description><![CDATA[<p style="text-align: justify;"><strong>MetaPred2CS Web server&nbsp;</strong>is a meta-predictor based on&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/17160063">Support Vector Machine (SVM)</a>&nbsp;that combines 6 individual sequence based protein-protein interaction prediction methods to predict&nbsp;<strong>prokaryotic two-component system&nbsp;</strong>protein-protein interactions (PPIs). The methods implemented in MetaPred2CS are 2 co-evolutionary methods:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/11933068">in-silico two hybrid (i2h)</a>&nbsp;and&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/11707606">mirror tree (MT)</a>&nbsp;methods and 4 genomics context based methods:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/15947018">phylogenetic profiling (PP)</a>,&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/10573422">gene fusion (GF)</a>,&nbsp;<a href="http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.0030043">gene neighbourhood (GN)</a>&nbsp;and and&nbsp;<a href="http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.0030043">gene operon methods (GO)</a>.</p>
<p>&nbsp;http://metapred2cs.ibers.aber.ac.uk/</p><p>Address of the bookmark: <a href="https://github.com/martinjvickers/MetaPred2CS" rel="nofollow">https://github.com/martinjvickers/MetaPred2CS</a></p>]]></description>
	<dc:creator>Manisha Mishra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27847/anvio</guid>
	<pubDate>Thu, 16 Jun 2016 18:15:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27847/anvio</link>
	<title><![CDATA[Anvio]]></title>
	<description><![CDATA[<p>In a nutshell</p>
<p>Anvi&rsquo;o is an analysis and visualization platform for &lsquo;omics data.</p>
<p>Please find the methods paper here: https://peerj.com/articles/1319/</p>
<p>Anvi&rsquo;o would not have been possible without the help of many people who directly or indirectly contributed to its development. Here is the acknowledgements section of our methods paper</p>
<p><span>An analysis and visualization platform for 'omics data</span><span>&nbsp;</span><span><a href="http://merenlab.org/projects/anvio">http://merenlab.org/projects/anvio</a></span></p>
<p><span>Paper&nbsp;https://peerj.com/articles/1839/</span></p><p>Address of the bookmark: <a href="https://github.com/meren/anvio" rel="nofollow">https://github.com/meren/anvio</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>

</channel>
</rss>