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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/42405?offset=70</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/37677/installing-blat-on-linux</guid>
	<pubDate>Tue, 11 Sep 2018 08:17:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/37677/installing-blat-on-linux</link>
	<title><![CDATA[Installing BLAT on Linux !]]></title>
	<description><![CDATA[<p><span>It's been a while since I last installed BLAT and when I went to the download directory at UCSC:&nbsp;</span><a href="http://users.soe.ucsc.edu/~kent/src/">http://users.soe.ucsc.edu/~kent/src/</a><span>&nbsp;I found that the latest blast is now version 35 and that the code to download was:&nbsp;</span><a href="http://users.soe.ucsc.edu/~kent/src/blatSrc35.zip">blatSrc35.zip</a><span>. However, you can also get pre-compiled binaries at:&nbsp;</span><a href="http://hgdownload.cse.ucsc.edu/admin/exe/">http://hgdownload.cse.ucsc.edu/admin/exe/</a><span>&nbsp;and that there was a linux x86_64 executable for my architecture available at:&nbsp;</span><a href="http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/blat/">http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/blat/</a><span>. Though YYMV, BLAT can be a little bit of a tricky beast to get going, so I decided to download the source code and compile that.</span><br /><br /><span>I will be compiling this code as 'root' as a system tool in&nbsp;</span><code>/usr/local/src</code><span>, so do not scream at me for that.</span><br /><br /><span>First I created an /usr/local/src/blat directory and I copied the blatSrc35.zip file into that.</span><br /><br /><span>Next I used</span></p><pre><code>unzip blatSrc35.zip</code></pre><p><span>to unpack the archive. This gives a directory blatSrc now move into that directory.</span></p><pre><code>#cd blatSrc</code></pre><p><span>before you begin read the README file that comes with the source code.</span><br /><br /><span>One thing about building blat is that you need to set the MACHTYPE variable so that the BLAT sources know what type of machine you are compiling the software on.</span><br /><br /><span>on most *nix machines, typing</span></p><pre><code>echo $MACHTYPE</code></pre><p><span>will return the machine architecture type.</span><br /><br /><span>On my CentOS 6 based system this gave:</span></p><pre><code>x86_64-redhat-linux-gnu</code></pre><p><span>However, what BLAT requires is the 'short value' (ie the first part of the MACHTYPE). To correct this, in the bash shell type (change this to the correct MACHTYPE for your system)</span></p><pre><code>MACHTYPE=x86_64
export MACHTYPE</code></pre><p><span>now running the command:</span></p><pre><code>echo $MACHTYPE</code></pre><p><span>should give the correct short form of the MACHTYPE:</span></p><pre><code>x86_64</code></pre><p><span>now create the directory lib/$MACHTYPE in the source tree. ie:</span></p><pre><code>mkdir lib/$MACHTYPE</code></pre><p><span>For my machine, lib/x86_64 already existed, so I did not have to do this, but this is not the case for all architectures.</span><br /><br /><span>The BLAT code assumes that you are compiling BLAT as a non-privileged (ie non-root) user. As a result, you must create the directory for the executables to go into:</span><br /><br /><span>mkdir ~/bin/$MACHTYPE</span><br /><br /><span>If you are installing as a normal user, edit your .bashrc to add the following (change the x86_64 to be your MACHTYPE):</span><br /><br /><span>export PATH=~/bin/x86_64::$PATH</span><br /><br /><span>For me, though, this was not good enough. I wanted the executables in /usr/local/bin where all my other code goes. As a result I did some hackery...</span><br /><br /><span>There is a master make template in the&nbsp;</span><code>inc</code><span>&nbsp;directory called&nbsp;</span><code>common.mk</code><span>&nbsp;and I edited this file with the command:</span><br /><br /><span>vi inc/common.mk</span><br /><br /><span>I replaced the line</span></p><pre><code>    BINDIR=${HOME}/bin/${MACHTYPE}</code></pre><p><span>with</span></p><pre><code>    BINDIR=/usr/local/bin</code></pre><p><span>saved and quit (as this is in my path, I do not need to do anything else)</span><br /><br /><span>All the preparation is now done and you can create the blat executables by going into the toplevel of the blat source tree (for me it was&nbsp;</span><code>/usr/local/src/blat/blatSrc</code><span>, but change to wherever you unpacked blat into).</span><br /><br /><span>Now simply run the command:</span></p><pre><code>make</code></pre><p><span>to compile the code.</span><br /><br /><span>Blat installed cleanly and the executables were all neatly placed in /usr/local/bin/x86_64, just like I wanted.</span><br /><br /><span>now simply running the command:</span></p><pre><code>blat</code></pre><p><span>on the command line gives me information on blat and sample usage.</span><br /><br /><span>Blat is installed and it's installed properly in my system code tree!!!</span></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42150/parallellastz-lastz-with-multi-threads-support</guid>
	<pubDate>Sat, 22 Aug 2020 05:58:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42150/parallellastz-lastz-with-multi-threads-support</link>
	<title><![CDATA[parallelLastz: Lastz with multi-threads support.]]></title>
	<description><![CDATA[<p>Running Lastz (<a href="https://github.com/lastz/lastz">https://github.com/lastz/lastz</a>) in parallel mode. This program is for single computer with multiple core processors.</p>
<p>When the query file format is fasta, you can specify many threads to process it. It can reduce run time linearly, and use almost equal memory as the original lastz program. This is useful when you lastz a big query file to a huge reference like human whole genome sequence.</p>
<p>The program is an extension on the original lastz program which was written by Bob Harris (the LASTZ guy).</p><p>Address of the bookmark: <a href="https://github.com/jnarayan81/parallelLastz" rel="nofollow">https://github.com/jnarayan81/parallelLastz</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40721/efs-an-ensemble-feature-selection-tool-implemented-as-r-package-and-web-application</guid>
	<pubDate>Tue, 28 Jan 2020 05:12:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40721/efs-an-ensemble-feature-selection-tool-implemented-as-r-package-and-web-application</link>
	<title><![CDATA[EFS: an ensemble feature selection tool implemented as R-package and web-application]]></title>
	<description><![CDATA[<p><span>The software EFS (Ensemble Feature Selection) makes use of multiple feature selection methods and combines their normalized outputs to a quantitative ensemble importance. Currently, eight different feature selection methods have been integrated in EFS, which can be used separately or combined in an ensemble.</span></p>
<p><a href="https://biodatamining.biomedcentral.com/articles/10.1186/s13040-017-0142-8">https://biodatamining.biomedcentral.com/articles/10.1186/s13040-017-0142-8</a></p><p>Address of the bookmark: <a href="http://efs.heiderlab.de/" rel="nofollow">http://efs.heiderlab.de/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35885/multi-car-a-tool-of-contig-scaffolding-using-multiple-references</guid>
	<pubDate>Tue, 06 Mar 2018 16:39:41 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35885/multi-car-a-tool-of-contig-scaffolding-using-multiple-references</link>
	<title><![CDATA[Multi-CAR: a tool of contig scaffolding using multiple references]]></title>
	<description><![CDATA[<p><span>we design a simple heuristic method to further revise our single reference-based scaffolding tool CAR into a new one called Multi-CAR such that it can utilize multiple complete genomes of related organisms as references to more accurately order and orient the contigs of a draft genome. In practical usage, our Multi-CAR does not require prior knowledge concerning phylogenetic relationships among the draft and reference genomes and libraries of paired-end reads. To validate Multi-CAR, we have tested it on a real dataset composed of several prokaryotic genomes and also compared its accuracy performance with other multiple reference-based scaffolding tools Ragout and MeDuSa.&nbsp;</span></p><p>Address of the bookmark: <a href="http://genome.cs.nthu.edu.tw/Multi-CAR/" rel="nofollow">http://genome.cs.nthu.edu.tw/Multi-CAR/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38501/fgenesh-program-for-predicting-multiple-genes-in-genomic-dna-sequences</guid>
	<pubDate>Thu, 20 Dec 2018 11:55:08 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38501/fgenesh-program-for-predicting-multiple-genes-in-genomic-dna-sequences</link>
	<title><![CDATA[FGENESH - Program for predicting multiple genes in genomic DNA sequences]]></title>
	<description><![CDATA[<p>FGENESH is the fastest (50-100 times faster than GenScan) and most accurate gene finder available - see the figure and the table below. In recent rice genome sequencing projects, it was cited "the most successful (gene finding) program (Yu&nbsp;<em>et al</em>. (2002) Science 296:79) and was used to produce 87% of all high-evidence predicted genes (Goff&nbsp;<em>et al</em>. (2002) Science 296:79).</p><p>Address of the bookmark: <a href="http://www.softberry.com/berry.phtml?topic=fgenesh&amp;group=help&amp;subgroup=gfind" rel="nofollow">http://www.softberry.com/berry.phtml?topic=fgenesh&amp;group=help&amp;subgroup=gfind</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44904/termal-a-fast-and-interactive-terminal-based-viewer-for-multiple-sequence-alignments</guid>
	<pubDate>Mon, 22 Sep 2025 23:51:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44904/termal-a-fast-and-interactive-terminal-based-viewer-for-multiple-sequence-alignments</link>
	<title><![CDATA[Termal: a fast and interactive terminal-based viewer for multiple sequence alignments]]></title>
	<description><![CDATA[<p>termal, a fast, interactive, terminal-based viewer for multiple sequence alignments (MSAs), designed for use on remote systems such as high-performance computing (HPC) clusters.</p>
<p>https://academic.oup.com/bioinformaticsadvances/advance-article/doi/10.1093/bioadv/vbaf208/8257678?login=true</p><p>Address of the bookmark: <a href="https://github.com/sib-swiss/termal" rel="nofollow">https://github.com/sib-swiss/termal</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/11798/phd-scholarship-denmark</guid>
  <pubDate>Fri, 13 Jun 2014 13:44:07 -0500</pubDate>
  <link></link>
  <title><![CDATA[PHD SCHOLARSHIP DENMARK]]></title>
  <description><![CDATA[
<p>ne PhD position is available at the Bioinformatics Center, Department of Biology, University of Copenhagen, Denmark. The PhD position concerns protein structure prediction, and will be in the Structural Bioinformatics group of Associate professor Thomas Hamelryck. The group is an integrated part of the Bioinformatics Center, which is headed by Professor Anders Krogh, employs around sixty scientists (including PhD students) and focuses on non-coding RNA, eukaryotic gene regulation and protein structure prediction. The center provides a modern, pleasant, international working environment with excellent modern facilities, in the heart of Copenhagen.<br />The project will be supervised by Associate Professor Thomas Hamelryck.</p>

<p>The protein folding problem is of enormous practical, theoretical and medical importance - and in addition forms a fascinating intellectual challenge. The aim of this project is to develop and implement a probabilistic method to infer the structure of proteins, building on various probabilistic models of protein structure developed by the Hamelryck group. The method will also take the dynamic nature of proteins into account, and involves a close collaboration with the statistics department at the university within the interdisciplinary project "Dynamical Systems: Mathematical Modeling and Statistical Methods for the Social, Health, and Natural Sciences" (http://dsin.ku.dk/).</p>

<p>Qualifications<br />Knowledge of programming (C++) and statistics or machine learning. Knowledge of biology, physics or biophysics is a plus, but not a requirement.</p>

<p>The deadline for applications is June 15, 2014</p>

<p>More at : https://job.jobnet.dk/CV/FindJob/details.aspx/3695051%20</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37669/strum-structure-based-prediction-of-protein-stability-changes-upon-single-point-mutation</guid>
	<pubDate>Mon, 10 Sep 2018 13:21:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37669/strum-structure-based-prediction-of-protein-stability-changes-upon-single-point-mutation</link>
	<title><![CDATA[STRUM: structure-based prediction of protein stability changes upon single-point mutation]]></title>
	<description><![CDATA[<p><span>STRUM is a method for predicting the fold stability change (&Delta;&Delta;G) of protein molecules upon single-point nsSNP mutations. STRUM adopts a gradient boosting regression approch to train the Gibbs free-energy changes on a variety of features at different levels of sequence and structure properties. The unique characteristics of STRUM is the combination of sequence profiles with low-resolution structure models from protein structure prediction, which helps enhance the robustness and accuracy of the method and make it applicable to various protein seqences, including those without experimental structures&nbsp;</span></p><p>Address of the bookmark: <a href="https://zhanglab.ccmb.med.umich.edu/STRUM/" rel="nofollow">https://zhanglab.ccmb.med.umich.edu/STRUM/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/41231/phd-student-bio-informatician-in-computational-protein-modeling</guid>
  <pubDate>Sun, 23 Feb 2020 03:46:46 -0600</pubDate>
  <link></link>
  <title><![CDATA[PhD student / Bio-informatician in computational protein modeling]]></title>
  <description><![CDATA[
<p>PhD student / Bio-informatician in computational protein modeling<br />Job Profile<br />You will perform research on drug/protein interaction analysis in the context of lung cancer, using computational protein modeling. You will implement existing models predicting drug efficacy, related to EGFR-driven cancer. You will translate these models to novel oncogenes, including ROS1. You will validate these models against experimental data from a parallel project, with the final goal of deployment of your methods into clinical decision making. Your work will be embedded in an international network consisting of both academic partners and ROS1-NSCLC patient organizations.</p>

<p>Requirements</p>

<p>You are (or soon will be) a master in bio-informatics. You have strong ICT skills and you are eager to fully submerge into the world of protein modeling. You have good experience with Linux and one or more programming languages as well as knowledge of tertiary structure analysis. Candidates with a Master degree in one of the life sciences (Biomedical sciences, Biochemistry, Bio-engineering, Biostatistics, …), with relevant interest and extended experience in this field are also welcome. A general background cancer biology and genetics is needed. You are willing and eligible to apply for a personal PhD fellowship with the Flemish FWO (FWO.be). Therefore, it is required that you hold a master degree from a European university, and have not obtained your master diploma more than three years ago (see FWO website for detailed conditions). Proficiency in English, and good communication skills, both oral and written, are required. You are highly motivated, and you like to work in an interactive research team. You are willing to work on a 4-year PhD project starting beginning of 2020.</p>

<p>What we offer</p>

<p>We offer a one year position, as a PhD student, which can be extended up to 4 year upon positive evaluation, even if a personal fellowship application is not successful. Wages are according to the standard Flemish bursary levels for PhD students.</p>

<p>Interested?<br />For additional information please contact dr. Geert Vandeweyer. To apply, send a copy of your CV including details of your relevant skills and a motivation letter by e-mail to dr. Geert Vandeweyer (geert.vandeweyer@uantwerpen.be) before March 15, 2020.</p>

<p>Source:https://academicpositions.be/ad/university-of-antwerp/2020/phd-student-bio-informatician-in-computational-protein-modeling/141252?utm_source=jooble&amp;utm_medium=cpc&amp;utm_campaign=jooble</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4546/sowdhamini-lab</guid>
  <pubDate>Sun, 15 Sep 2013 09:19:12 -0500</pubDate>
  <link></link>
  <title><![CDATA[SOWDHAMINI Lab]]></title>
  <description><![CDATA[
<p>Genome sequencing projects have enormous potential for benefiting human endeavors. However, just as acquiring a language's vocabulary does not enable one to speak it, databases that list the amino acid composition of proteins do not directly tell us much about these proteins' higher-level structure and function. The most productive way to indirectly exploit these databases has been to start with the small number of proteins that are fully-characterised and to assume that other "similar" proteins will have a related structure and function. Proteins with very similar amino acid sequence are "no-brainers", but the real test, which our group largely focuses on, is to detect the "essential" similarity in proteins whose non-critical sections have experienced random rearrangements during evolution. In such cases functionally similar proteins may have less than 25% sequence overlap.</p>

<p>More @ http://www.ncbs.res.in/sowdhamini/groups_sowdhamini.htm</p>
]]></description>
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