<?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/9639?offset=820</link>
	<atom:link href="https://bioinformaticsonline.com/related/9639?offset=820" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38666/mcat-motif-combining-and-association-tool</guid>
	<pubDate>Sun, 13 Jan 2019 06:27:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38666/mcat-motif-combining-and-association-tool</link>
	<title><![CDATA[MCAT: Motif Combining and Association Tool]]></title>
	<description><![CDATA[<p>This is a pipeline for finding motifs in fasta files.<br>It can be run from the command line as follows:</p>
<p>usage: orange_pipeline_refine.py [-h] [-w W] [--nmotifs NMOTIFS] [--iter ITER] [-c C]<br>[-s S] [-d] [-ff] [-v V]<br>positive_seq negative_seq</p>
<p>positional arguments:<br>positive_seq the fasta file for the positive sequences<br>negative_seq the fasta file for the negative sequences</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/yanshen43/MCAT" rel="nofollow">https://github.com/yanshen43/MCAT</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/1182/installing-perl-gd-module</guid>
	<pubDate>Mon, 22 Jul 2013 14:02:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/1182/installing-perl-gd-module</link>
	<title><![CDATA[Installing Perl GD Module]]></title>
	<description><![CDATA[<div><p>In comparative genome analysis work, we usually compare more than two genomes and looks for syntenic regions amongst them. In my research I used Evolution Highway (RH) <a href="http://eh-demo.ncsa.uiuc.edu/">http://eh-demo.ncsa.uiuc.edu/</a>, which is a collaborative project designed to provide a visual means for simultaneously comparing genomes of multiple amniote species. The tool removes the burden of manually aligning these maps and allows cognitive skills to be used toward something more valuable than preparation and transformation of data. In addition to EH, attractive Circos (<a href="http://circos.ca/">http://circos.ca/</a>) is also very popular for this kind of analysis.</p><p>The EH is available online, and can be easily access and use, whereas Circos installation is not entirely straightforward. One of the most difficult parts of the installation involves installing the GD library. Since there weren't good instructions for installing this library on the internet I decided to post instructions here in case they are useful to anyone else.</p><p><strong>Following are the steps to install GD modules in Mac OS</strong><br /><br />1. Setup<br /><br />Create a folder for the files:<br /><br />$ mkdir -p /SourceCache<br />$ cd /SourceCache<br /><br />Get and unpack the required Jpeg-6b and GD libraries:<br />Download Jpeg-6b (<a href="http://code.google.com/p/google-desktop-for-linux-mirror/downloads/detail?name=jpeg-6b.tar.gz&amp;can=2&amp;q">http://code.google.com/p/google-desktop-for-linux-mirror/downloads/detail?name=jpeg-6b.tar.gz&amp;can=2&amp;q</a>)<br />Download GD (<a href="http://search.cpan.org/%7Elds/GD-2.46/">http://search.cpan.org/~lds/GD-2.46/</a>)<br /><br />Place the "tar.gz" files in "/SourceCache" and double click to unpack.<br /><br />2. Install libjpeg<br /><br />Copy the "config.sub" and "config.guess" files to "/SourceCache". Note that your "config.sub" and ""config.guess" files may be in a slightly different location. The commands below show where they were on my machine:<br /><br />$ cd /SourceCache/jpeg-6b/src<br />$ cp /usr/share/libtool/config/config.sub .<br />$ cp /usr/share/libtool/config/config.guess .<br /><br />Configure libjpeg as follows. Note that this was installed on a 64 bit machine. However, this method may configure it in a 32 bit format. This may not be the best way to configure the installation but it works.<br /><br />$ .configure --enable-shared<br />$ make<br /><br />Check to see if the following directories exist on your machine. Create the missing directories in the following manner:<br /><br />$ mkdir -p /usr/local/include<br />$ mkdir -p /usr/local/bin<br />$ mkdir -p /usr/local/lib<br />$ mkdir -p /usr/local/man/man1<br /><br />Finish making and installing libjpeg:<br /><br />$ make install<br /><br />3. Install GD<br /><br />$ cd /SourceCache/GD-2.46/GD/<br />$ perl Makefile.PL<br />$ make<br />$ make test (optional)<br />$ make html (optional)<br />$ make install</p><p><strong>Other way for Mac OS</strong><br />The easiest way to get a lot of these is with a program called Fink, which is similar in nature to the CPAN installer, but installs common GNU utilities. Fink is available from &lt;<a href="http://sourceforge.net/projects/fink/%3E">http://sourceforge.net/projects/fink/&gt;</a>.<br /><br />Follow the instructions for setting up Fink. Once it's installed, you'll want to run the following as root: fink install gd<br /><br />It will prompt you for a number of dependencies, type 'y' and hit enter to install all of the dependencies. Then watch it work.<br /><br />To prevent creating conflicts with the software that Apple installs by default, Fink creates its own directory tree at /sw where it installs most of the software that it installs. This means your libraries and headers for libgd will be at /sw/lib and /sw/include instead of /usr/lib and /usr/local/include. Because of these changed locations for the libraries, the Perl GD module will not install directly via CPAN, because it looks for the specific paths instead of getting them from your environment. But there's a way around that :-)<br /><br />Instead of typing "install GD" at the cpan&gt; prompt, type look GD. This should go through the motions of downloading the latest version of the GD module, then it will open a shell and drop you into the build directory. Apply below patch to the Makefile.PL file (save the patch into a file and use the command patch &lt; patchfile.)<br /><br />Then, run these commands to finish the installation of the GD module:<br /><br />perl Makefile.PL<br />make<br />make test<br />make install<br />And don't forget to run exit to get back to CPAN.</p><p>&nbsp;</p><p><strong>Install on MS Window, using PPM</strong></p><p>C:\Documents and Settings\Owner&gt;ppm<br />PPM interactive shell (2.2.0) - type 'help' for available commands.<br />PPM&gt; install GD<br />Install package 'GD?' (y/N): y<br />Installing package 'GD'...<br />Downloading <a href="http://ppm.ActiveState.com/PPMPackages/5.6plus/MSW">http://ppm.ActiveState.com/PPMPackages/5.6plus/MSW</a>. ...<br />Installing C:\Perl\site\lib\auto\GD\GD.bs<br />Installing C:\Perl\site\lib\auto\GD\GD.dll<br />Installing C:\Perl\site\lib\auto\GD\GD.exp<br />Installing C:\Perl\site\lib\auto\GD\GD.lib<br />Installing C:\Perl\html\site\lib\GD.html<br />Installing C:\Perl\site\lib\GD.pm<br />Installing C:\Perl\site\lib\qd.pl<br />Installing C:\Perl\site\lib\auto\GD\autosplit.ix<br />PPM&gt;<br /><br /><br />If you can't install it from ppm. You can download it:<br /><a href="http://ppm.ActiveState.com/PPMPackages/5.6plus/MSW">http://ppm.ActiveState.com/PPMPackages/5.6plus/MSW</a>.<br /><br /><br />BTW,All Perl 5.6.1 Modules are located at:<br /><br /><a href="http://ppm.ActiveState.com/PPMPackages/5.6plus/MSW">http://ppm.ActiveState.com/PPMPackages/5.6plus/MSW</a>.</p><p>&nbsp;</p><p><strong>Install the Perl GD Module on Linux</strong><br /><br />$ sudo perl -MCPAN -e shell<br /><br />Since it was the first time I had run this command on this particular machine I had to answer a lot of questions but simply selected the defaults for everything as this usually works for me. Once in the CPAN shell I entered<br /><br />$ install Bundle::CPAN<br /><br />and selected all of the defaults again. Once the CPAN bundle had finished installing I tried to install GD::Graph by typing<br /><br />$ install GD::Graph<br /><br />but it failed with hundreds of errors &ndash; the first of which was<br /><br />GD.xs:7:16: error: gd.h: No such file or directory<br /><br />This was fixed with the following apt-get command (in the bash shell)<br /><br />$ sudo apt-get install libgd2-xpm-dev<br /><br />back in the CPAN shell I still couldn&rsquo;t get GD::Graph to build and I guessed this was because of some left over files from the failed build. I don&rsquo;t know the command to clean things up inside the CPAN shell and am too lazy to read the docs so I simply went into the .cpan/build directory in my home directory and deleted anything that started with GD &ndash; eg<br /><br />$ rm -rf GD-2.35-HC_vkB<br /><br />$ rm -rf GDGraph-1.44-Evfibe<br /><br />and so on. Those strings at the end (VkB and so on) look random so they might be different on your machine. Then I went back into the CPAN shell and ran<br /><br />$ install GD::Graph<br /><br />There were a few dependencies which the script fetched and installed for me but everything worked smoothly.</p><p>Manual and other Perl Module instalation are mentioned in my previous blog @ <a href="http://bioinformaticsonline.com/blog/view/710/how-to-install-perl-modules-manually-using-cpan-command-and-other-quick-ways">http://bioinformaticsonline.com/blog/view/710/how-to-install-perl-modules-manually-using-cpan-command-and-other-quick-ways</a></p></div>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36502/creating-conda-environment-for-python27</guid>
	<pubDate>Mon, 07 May 2018 08:56:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36502/creating-conda-environment-for-python27</link>
	<title><![CDATA[Creating conda environment for python2.7]]></title>
	<description><![CDATA[<p>TIP: By default, environments are installed into the&nbsp;<code><span>envs</span></code>&nbsp;directory in your conda directory. Run&nbsp;<code><span>conda</span>&nbsp;<span>create</span>&nbsp;<span>--help</span></code>&nbsp;for information on specifying a different path.</p><p>Use the Terminal or an Anaconda Prompt for the following steps.</p><ol>
<li>
<p>To create an environment:</p>
<div>
<div>
<pre><span></span><span>conda</span> <span>create</span> <span>--</span><span>name</span> <span>myenv</span>
</pre>
</div>
</div>
<p>NOTE: Replace&nbsp;<code><span>myenv</span></code>&nbsp;with the environment name.</p>
</li>
<li>
<p>When conda asks you to proceed, type&nbsp;<code><span>y</span></code>:</p>
<div>
<div>
<pre><span></span>proceed ([y]/n)?
</pre>
</div>
</div>
</li>
</ol><p>This creates the myenv environment in&nbsp;<code><span>/envs/</span></code>. This environment uses the same version of Python that you are currently using, because you did not specify a version.</p><p>To create an environment with a specific version of Python:</p><div><div><pre><span></span>conda create -n myenv <span>python</span><span>=</span><span>3</span>.4
</pre></div></div><p>To create an environment with a specific package:</p><div><div><pre><span></span>conda create -n myenv scipy
</pre></div></div><p>OR:</p><div><div><pre><span></span>conda create -n myenv python
conda install -n myenv scipy
</pre></div></div><p>To create an environment with a specific version of a package:</p><div><div><pre><span></span>conda create -n myenv <span>scipy</span><span>=</span><span>0</span>.15.0
</pre></div></div><p>OR:</p><div><div><pre><span></span>conda create -n myenv python
conda install -n myenv <span>scipy</span><span>=</span><span>0</span>.15.0
</pre></div></div><p>To create an environment with a specific version of Python and multiple packages:</p><div><div><pre><span></span>conda create -n myenv <span>python</span><span>=</span><span>3</span>.4 <span>scipy</span><span>=</span><span>0</span>.15.0 astroid babel
</pre></div></div><p>TIP: Install all the programs that you want in this environment at the same time. Installing 1 program at a time can lead to dependency conflicts.</p><p>To automatically install pip or another program every time a new environment is created, add the default programs to the&nbsp;<a href="https://conda.io/docs/user-guide/configuration/use-condarc.html#config-add-default-pkgs">create_default_packages</a>&nbsp;section of your&nbsp;<code><span>.condarc</span></code>&nbsp;configuration file. The default packages are installed every time you create a new environment. If you do not want the default packages installed in a particular environment, use the&nbsp;<code><span>--no-default-packages</span></code>&nbsp;flag:</p><div><div><pre><span></span>conda create --no-default-packages -n myenv python
</pre></div></div><p>TIP: You can add much more to the&nbsp;<code><span>conda</span>&nbsp;<span>create</span></code>&nbsp;command. For details, run&nbsp;<code><span>conda</span>&nbsp;<span>create</span>&nbsp;<span>--help</span></code>.</p><p>➜ redundans git:(master) ✗ conda create --name py27 python=2.7<br />Solving environment: done</p><p><br />==&gt; WARNING: A newer version of conda exists. &lt;==<br /> current version: 4.5.0<br /> latest version: 4.5.2</p><p>Please update conda by running</p><p>$ conda update -n base conda</p><p>&nbsp;</p><p>## Package Plan ##</p><p>environment location: /home/urbe/anaconda3/envs/py27</p><p>added / updated specs: <br /> - python=2.7</p><p><br />The following packages will be downloaded:</p><p>package | build<br /> ---------------------------|-----------------<br /> wheel-0.31.0 | py27_0 61 KB<br /> python-2.7.15 | h1571d57_0 12.1 MB<br /> certifi-2018.4.16 | py27_0 142 KB<br /> sqlite-3.23.1 | he433501_0 1.5 MB<br /> setuptools-39.1.0 | py27_0 582 KB<br /> openssl-1.0.2o | h20670df_0 3.4 MB<br /> pip-10.0.1 | py27_0 1.7 MB<br /> ca-certificates-2018.03.07 | 0 124 KB<br /> ------------------------------------------------------------<br /> Total: 19.6 MB</p><p>The following NEW packages will be INSTALLED:</p><p>ca-certificates: 2018.03.07-0 <br /> certifi: 2018.4.16-py27_0 <br /> libedit: 3.1-heed3624_0 <br /> libffi: 3.2.1-hd88cf55_4 <br /> libgcc-ng: 7.2.0-hdf63c60_3 <br /> libstdcxx-ng: 7.2.0-hdf63c60_3 <br /> ncurses: 6.0-h9df7e31_2 <br /> openssl: 1.0.2o-h20670df_0<br /> pip: 10.0.1-py27_0 <br /> python: 2.7.15-h1571d57_0<br /> readline: 7.0-ha6073c6_4 <br /> setuptools: 39.1.0-py27_0 <br /> sqlite: 3.23.1-he433501_0<br /> tk: 8.6.7-hc745277_3 <br /> wheel: 0.31.0-py27_0 <br /> zlib: 1.2.11-ha838bed_2</p><p>Proceed ([y]/n)? y</p><p><br />Downloading and Extracting Packages<br />wheel 0.31.0: #################################################################################################################################################################################################### | 100% <br />python 2.7.15: ################################################################################################################################################################################################### | 100% <br />certifi 2018.4.16: ############################################################################################################################################################################################### | 100% <br />sqlite 3.23.1: ################################################################################################################################################################################################### | 100% <br />setuptools 39.1.0: ############################################################################################################################################################################################### | 100% <br />openssl 1.0.2o: ################################################################################################################################################################################################## | 100% <br />pip 10.0.1: ###################################################################################################################################################################################################### | 100% <br />ca-certificates 2018.03.07: ###################################################################################################################################################################################### | 100% <br />Preparing transaction: done<br />Verifying transaction: done<br />Executing transaction: done<br />#<br /># To activate this environment, use:<br /># &gt; source activate py27<br />#<br /># To deactivate an active environment, use:<br /># &gt; source deactivate<br />#</p><p>➜ redundans git:(master) ✗ source activate py27</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/14091/subprocess-pkg</guid>
	<pubDate>Sun, 17 Aug 2014 07:59:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/14091/subprocess-pkg</link>
	<title><![CDATA[Subprocess pkg]]></title>
	<description><![CDATA[<p>Subprocess is one of simplest way of running linux command from within python code</p><p>Example:</p><p>if you want to run fastqc for QC of fastq file:</p><p>from subprocess import Popen,PIPE,call</p><p>p=Popen(["fastqc","-f","fastq","-o", "/home/name/result/","/dev/stdin"],stdin=fopen("read.fastq","r") ,stdout=PIPE,stderr=PIPE)</p><p>print p.stderr</p><p>p.stdout.close()</p><p>More:</p><p>http://pymotw.com/2/subprocess/</p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43120/ventoy-an-open-source-tool-to-create-bootable-usb-drive</guid>
	<pubDate>Tue, 29 Jun 2021 10:16:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43120/ventoy-an-open-source-tool-to-create-bootable-usb-drive</link>
	<title><![CDATA[Ventoy: an open source tool to create bootable USB drive]]></title>
	<description><![CDATA[<p>Ventoy is an open source tool to create bootable USB drive for ISO/WIM/IMG/VHD(x)/EFI files. With ventoy, you don't need to format the disk over and over, you just need to copy the image files to the USB drive and boot it. You can copy many image files at a time and ventoy will give you a boot menu to select them. x86 Legacy BIOS, IA32 UEFI, x86_64 UEFI, ARM64 UEFI and MIPS64EL UEFI are supported in the same way. Both MBR and GPT partition style are supported in the same way. Most type of OS supported(Windows/WinPE/Linux/Unix/Vmware/Xen...) 700+ ISO files are tested.&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/ventoy/Ventoy" rel="nofollow">https://github.com/ventoy/Ventoy</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/2791/ncbi-psi-blast-tutorial</guid>
	<pubDate>Fri, 23 Aug 2013 02:25:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/2791/ncbi-psi-blast-tutorial</link>
	<title><![CDATA[NCBI PSI-BLAST Tutorial]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/T3kHEieyylk" frameborder="0" allowfullscreen></iframe>http:--www.biotechnology.jhu.edu-
Tutorial for PSI-BLAST, an extension of BLAST that uses matrix algebra. BLAST is a cornerstone bioinformatics tool at NCBI. BLAST is the
Basic Local Alignment Search tool and will protein and DNA sequences that
are related to a sequence that the user provides.]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44559/metagraph-ultra-scalable-framework-for-dna-search-alignment-assembly</guid>
	<pubDate>Sat, 08 Jun 2024 16:15:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44559/metagraph-ultra-scalable-framework-for-dna-search-alignment-assembly</link>
	<title><![CDATA[MetaGraph: Ultra Scalable Framework for DNA Search, Alignment, Assembly]]></title>
	<description><![CDATA[<p><span>The MetaGraph framework</span><span>&nbsp;is designed to work with a wide range of input data sets, indexing from a few samples up to the contents of entire archives with hundreds of thousands of records. The indexing workflow always follows the same principle, transforming single input samples into error-removed, refined sample graphs, which are then merged into a joint metagraph index. Each input sample is annotated in the joint index as a subgraph. This graph index enriched with metadata can then be used for downstream applications such as&nbsp;</span><a href="https://metagraph.ethz.ch/#query">sequence search</a><span>&nbsp;or&nbsp;</span><a href="https://metagraph.ethz.ch/#assembly">differential assembly</a><span>.</span></p>
<p><span>Searcg link&nbsp;https://metagraph.ethz.ch/search&nbsp;</span></p>
<p><span>Pre-print&nbsp;https://www.biorxiv.org/content/10.1101/2020.10.01.322164v4&nbsp;</span></p><p>Address of the bookmark: <a href="https://metagraph.ethz.ch/" rel="nofollow">https://metagraph.ethz.ch/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36026/mmseqs20-ultra-fast-and-sensitive-protein-search-and-clustering-suite</guid>
	<pubDate>Thu, 22 Mar 2018 10:40:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36026/mmseqs20-ultra-fast-and-sensitive-protein-search-and-clustering-suite</link>
	<title><![CDATA[MMseqs2.0: ultra fast and sensitive protein search and clustering suite]]></title>
	<description><![CDATA[<p>MMseqs2 (Many-against-Many sequence searching) is a software suite to search and cluster huge protein sequence sets. MMseqs2 is open source GPL-licensed software implemented in C++ for Linux, MacOS, and (as beta version, via cygwin) Windows. The software is designed to run on multiple cores and servers and exhibits very good scalability. MMseqs2 can run 10000 times faster than BLAST. At 100 times its speed it achieves almost the same sensitivity. It can perform profile searches with the same sensitivity as PSI-BLAST at over 400 times its speed.</p>
<p>The MMseqs2 user guide is available as&nbsp;<a href="https://github.com/soedinglab/mmseqs2/wiki">Github Wiki</a>&nbsp;or as&nbsp;<a href="https://mmseqs.com/latest/userguide.pdf">PDF file</a>&nbsp;(Thanks to&nbsp;<a href="https://github.com/jgm/pandoc">pandoc</a>!)</p>
<p>Please cite:&nbsp;<a href="https://www.nature.com/nbt/journal/vaop/ncurrent/full/nbt.3988.html">Steinegger M and Soeding J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nature Biotechnology, doi: 10.1038/nbt.3988 (2017)</a>.</p><p>Address of the bookmark: <a href="https://github.com/soedinglab/MMseqs2" rel="nofollow">https://github.com/soedinglab/MMseqs2</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43439/mmseqs2-ultra-fast-and-sensitive-sequence-search-and-clustering-suite</guid>
	<pubDate>Wed, 06 Oct 2021 07:01:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43439/mmseqs2-ultra-fast-and-sensitive-sequence-search-and-clustering-suite</link>
	<title><![CDATA[MMseqs2: ultra fast and sensitive sequence search and clustering suite]]></title>
	<description><![CDATA[<p><span>MMseqs2 (Many-against-Many sequence searching) is a software suite to search and cluster huge protein and nucleotide sequence sets. MMseqs2 is open source GPL-licensed software implemented in C++ for Linux, MacOS, and (as beta version, via cygwin) Windows. The software is designed to run on multiple cores and servers and exhibits very good scalability. MMseqs2 can run 10000 times faster than BLAST. At 100 times its speed it achieves almost the same sensitivity. It can perform profile searches with the same sensitivity as PSI-BLAST at over 400 times its speed.</span></p><p>Address of the bookmark: <a href="https://github.com/soedinglab/MMseqs2" rel="nofollow">https://github.com/soedinglab/MMseqs2</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/12883/breaking-chromosomes-to-study-cancer</guid>
	<pubDate>Fri, 18 Jul 2014 05:42:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/12883/breaking-chromosomes-to-study-cancer</link>
	<title><![CDATA[Breaking chromosomes to study cancer !!!]]></title>
	<description><![CDATA[<p>Chromosomes are present in every cell of our body and they contain the information the body needs to develop and function properly. This information is carried in genes that are arranged along the chromosomes. There are usually 46 chromosomes in every cell. These chromosomes come in pairs, one from our mother and one from our father. The chromosomes can be sorted into 23 pairs by looking at them down a microscope.</p><p>Most people who have a balanced translocation have the right amount of chromosome material but it has been rearranged in some way. This may happen if two chromosomes swap pieces (a reciprocal translocation). In other cases two whole chromosomes may become stuck together (a Robertsonian translocation). This page describes what happens when someone has a reciprocal translocation. <br /><br />Reciprocal chromosomal translocations occur following double-strand breaks (DSBs) in DNA when a section of one chromosome is exchanged with that of another, non-homologous chromosome. These exchanges may produce a dysfunctional fusion gene that disrupts cell growth and survival pathways, such as the translocations seen in leukemia and childhood sarcomas. <br /><br />Chromosomal translocations have been well studied in cancer cell lines which are associated with two types of cancer, acute myeloid leukemia and Ewing's sarcoma, but determining how they contribute to cancer development is complicated by additional mutations and altered gene expression profiles in these cultured cells. Now, Juan Carlos Ramirez, head of the Viral Vector Facility at the Fundacion Centro Nacional de Investigaciones Cardiovasculares (CNIC) and his colleagues Raul Torres at CNIC and Sandra Rodriguez-Peralez at the Spanish National Cancer Center (CNIO) in Madrid, Spain have used a new genome editing tool, CRISPR-Cas9, to induce chromosomal translocations for the first time in a human cell line and in primary cells. The study's authors conclude by stating that the use of this technology will allow for the clarification of how and why chromosomal translocation occurs, which without doubt will allow new anti-cancer therapeutic strategies to be tackled.</p><p>Using RNA-Guided Endonuclease (RGEN) technology or CRISPR/Cas9 genome engineering technology, CNIO and CNIC researchers have shown that it is possible to obtain such chromosomal translocations. The CRISPR-Cas9 system is extremely simple to introduce a cut at the desired locus, easier to design, and cheaper than many other systems. Using the CRISPR-Cas9 system, Ramirez and his colleagues reproduced the translocations observed in Ewing&rsquo;s Sarcoma (ES) and Acute Myeloid Leukemia (AML) patient cell lines in HEK293 cells and also generated the ES translocation in human mesenchymal stem cells and the AML translocation in umbilical cord blood cells.</p><p>By focusing on chromosomal translocation without the confounding characteristics of established cell lines, these new cells lines should help answer the fundamental question of what causes a cell to become cancerous. Ramirez and his team now look forward to modeling other chromosome translocations in a variety of cell types.</p><p>Reference:</p><p>http://en.wikipedia.org/wiki/Chromosomal_translocation</p><p>http://www.nature.com/ncomms/2014/140603/ncomms4964/abs/ncomms4964.html<br /><br /></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

</channel>
</rss>