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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/32379?offset=130</link>
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	<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/bookmarks/view/19636/google-genomics</guid>
	<pubDate>Thu, 18 Dec 2014 11:05:42 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/19636/google-genomics</link>
	<title><![CDATA[Google Genomics]]></title>
	<description><![CDATA[<ul>
<li>
<p><strong>Explore genetic variation interactively.</strong> Compare entire cohorts in seconds with SQL-like queries. Compute transition/transversion ratios, genome-wide association, allelic frequency and more.</p>
</li>
<li>
<p><strong>Process big genomic data easily.</strong> Run batch analyses like principal component analysis and Hardy-Weinberg equilibrium on as many samples as you like, in minutes or hours, with just a little code.</p>
</li>
<li>
<p><strong>Use Google's infrastructure and big data expertise.</strong> Store one genome or a million using Google Genomics and take advantage of the same infrastructure that powers Search, Maps, YouTube, Gmail and Drive.</p>
</li>
<li>
<p><strong>Support emerging global standards.</strong> Google Genomics is implementing the API defined by the Global Alliance for Genomics and Health for visualization, analysis and more. Compliant software can access Google Genomics, local servers, or any other implementation.</p>
</li>
</ul><p>Address of the bookmark: <a href="https://cloud.google.com/genomics/" rel="nofollow">https://cloud.google.com/genomics/</a></p>]]></description>
	<dc:creator>Tenzin Paul</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/23892/bioinformatics-made-easy-search-bioinformatics-tools-and-run-genomic-analysis-in-the-cloud</guid>
	<pubDate>Thu, 20 Aug 2015 02:21:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/23892/bioinformatics-made-easy-search-bioinformatics-tools-and-run-genomic-analysis-in-the-cloud</link>
	<title><![CDATA[Bioinformatics Made Easy Search: Bioinformatics tools and run genomic analysis in the cloud]]></title>
	<description><![CDATA[<p>InsideDNA makes hundreds of bioinformatics tools immediately available to run via an easy-to-use web interface and allows an accurate search across all functions, tools and pipelines.</p>
<p>With InsideDNA, you can upload and store your own genomic/genetic datasets in a limitless cloud space, and instantly analyze it with a powerful compute instance, without any tool installation or set up hassle.</p>
<p>More at https://insidedna.me/</p><p>Address of the bookmark: <a href="https://insidedna.me/" rel="nofollow">https://insidedna.me/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27685/biodbnet</guid>
	<pubDate>Thu, 02 Jun 2016 11:11:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27685/biodbnet</link>
	<title><![CDATA[BioDBnet]]></title>
	<description><![CDATA[<p><span>Database to Database Conversions</span> </p>
<p>db2db allows for conversions of identifiers from one database to other database identifiers or annotations. To use db2db select the input type of your data, changing the input type automatically changes the output options to the ones specific for the input selected. Then select one or more output types and add your identifiers in the ID list box. Set the remove duplicate values to 'No' if you do not want duplicates to be removed. Clicking on submit then returns a table of your inputs matched against all the outputs selected in the exact order as entered. Results can be limited to a particular taxon by entering it's <a href="https://biodbnet-abcc.ncifcrf.gov/tools/orgTaxon.php">Taxon ID</a>. The performance will vary widely depending on the number of outputs and the options selected. Conversions to a single output with the default options should complete in a few seconds</p><p>Address of the bookmark: <a href="https://biodbnet-abcc.ncifcrf.gov/db/db2db.php" rel="nofollow">https://biodbnet-abcc.ncifcrf.gov/db/db2db.php</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26380/hicdat</guid>
	<pubDate>Fri, 12 Feb 2016 05:23:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26380/hicdat</link>
	<title><![CDATA[HiCdat]]></title>
	<description><![CDATA[<p>HiCdat: a fast and easy-to-use Hi-C data analysis tool</p>
<p>HiCdat is easy-to-use and provides solutions starting from aligned reads up to in-depth analyses. Importantly, HiCdat is focussed on the analysis of larger structural features of chromosomes, their correlation to genomic and epigenomic features, and on comparative studies. It uses simple input and output formats and can therefore easily be integrated into existing workflows or combined with alternative tools.</p>
<p>More at http://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0678-x</p><p>Address of the bookmark: <a href="https://github.com/MWSchmid/HiCdat" rel="nofollow">https://github.com/MWSchmid/HiCdat</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28809/kissplice</guid>
	<pubDate>Tue, 16 Aug 2016 08:34:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28809/kissplice</link>
	<title><![CDATA[KisSplice]]></title>
	<description><![CDATA[<p>KisSplice is a software that enables to analyse RNA-seq data with or without a reference genome. It is an exact local transcriptome assembler that allows to identify SNPs, indels and alternative splicing events. It can deal with an arbitrary number of biological conditions, and will quantify each variant in each condition. It has been tested on Illumina datasets of up to 1G reads. Its memory consumption is around 5Gb for 100M reads.</p>
<p>KisSplice is not a full-length transcriptome assembler. This means that it will output the variable regions of the transcripts, not reconstruct them entirely.</p>
<p>KisSplice comes as a workflow, with several possible post-treatments meant to facilitate the analysis of the results. The choice of the post-treatment depends on the availability of a reference genome/transcriptome and on the need to perform a differential analysis, as summarised in the following table.</p><p>Address of the bookmark: <a href="http://kissplice.prabi.fr/" rel="nofollow">http://kissplice.prabi.fr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28200/machine-learning</guid>
	<pubDate>Fri, 01 Jul 2016 12:57:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28200/machine-learning</link>
	<title><![CDATA[Machine Learning !!!]]></title>
	<description><![CDATA[<p>In machine learning, computers apply&nbsp;<strong>statistical learning</strong>&nbsp;techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions.</p>
<p><em>Keep scrolling.</em>&nbsp;Using a data set about homes, we will create a machine learning model to distinguish homes in New York from homes in San Francisco.</p><p>Address of the bookmark: <a href="http://www.r2d3.us/visual-intro-to-machine-learning-part-1/" rel="nofollow">http://www.r2d3.us/visual-intro-to-machine-learning-part-1/</a></p>]]></description>
	<dc:creator>Gudiya Pal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28417/wisescaffolder</guid>
	<pubDate>Wed, 13 Jul 2016 08:08:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28417/wisescaffolder</link>
	<title><![CDATA[WiseScaffolder]]></title>
	<description><![CDATA[<p>Function</p>
<p>WiseScaffolder is a stand-alone semi-automatic application for genome scaffolding of pre-assembled contigs using mate-pair data. It also produces editable scaffold maps, allowing either to build gapped scaffolds or usable as a common thread for the manual improvement of scaffolds.</p>
<p>Description&nbsp;</p>
<p>WiseScaffolder includes 4 subcommands: dumpconfig generates a configuration file that notably specifies the average insert size of the mate-pair library preprocess allows the detection and correction of chimerae, the estimation of contigs copy number and produces valuable outputs for the manual improvement of scaffolds scaffold constitutes the central scaffold-builder and comprises two modules:</p>
<p>i) the interative_scaffold_extender, which works with big, unambiguous contigs, or when they run out, single copy contigs, and</p>
<p>ii) the small_contig_inserter, which inserts the small contigs within scaffolds buildfasta converts the scaffold(s) map(s) into Fasta sequences.</p><p>Address of the bookmark: <a href="http://abims.sb-roscoff.fr/wisescaffolder" rel="nofollow">http://abims.sb-roscoff.fr/wisescaffolder</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29018/crossmap</guid>
	<pubDate>Mon, 05 Sep 2016 04:07:38 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29018/crossmap</link>
	<title><![CDATA[CrossMap]]></title>
	<description><![CDATA[<ul>
<li>CrossMap is a program for convenient conversion of genome coordinates (or annotation files) between&nbsp;<em>different assemblies</em>&nbsp;(such as Human&nbsp;<a href="http://www.ncbi.nlm.nih.gov/assembly/2928/">hg18 (NCBI36)</a>&nbsp;&lt;&gt;&nbsp;<a href="http://www.ncbi.nlm.nih.gov/assembly/2758/">hg19 (GRCh37)</a>, Mouse&nbsp;<a href="http://www.ncbi.nlm.nih.gov/assembly/165668/">mm9 (MGSCv37)</a>&nbsp;&lt;&gt;&nbsp;<a href="http://www.ncbi.nlm.nih.gov/assembly/327618/">mm10 (GRCm38)</a>).</li>
<li>It supports most commonly used file formats including SAM/BAM, Wiggle/BigWig, BED, GFF/GTF, VCF.</li>
<li>CrossMap is designed to liftover genome coordinates between assemblies. It&rsquo;s&nbsp;<em>not</em>&nbsp;a program for aligning sequences to reference genome.</li>
<li>We&nbsp;<em>do not</em>&nbsp;recommend using CrossMap to convert genome coordinates between species.</li>
</ul><p>Address of the bookmark: <a href="http://crossmap.sourceforge.net/" rel="nofollow">http://crossmap.sourceforge.net/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28844/teannot</guid>
	<pubDate>Thu, 18 Aug 2016 10:02:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28844/teannot</link>
	<title><![CDATA[TEannot]]></title>
	<description><![CDATA[<p>We advise to run first the TEdenovo pipeline but it is not compulsory. We suppose you begin by running the TEannot pipeline on the example provided in the directory "db/" rather than directly on your own genomic sequences. Thus, from now on, the project name is "DmelChr4".</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://urgi.versailles.inra.fr/Tools/REPET/TEannot-tuto" rel="nofollow">https://urgi.versailles.inra.fr/Tools/REPET/TEannot-tuto</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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