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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/34916?offset=620</link>
	<atom:link href="https://bioinformaticsonline.com/related/34916?offset=620" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36373/tools-to-predict-the-impact-of-missense-variants</guid>
	<pubDate>Mon, 23 Apr 2018 12:57:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36373/tools-to-predict-the-impact-of-missense-variants</link>
	<title><![CDATA[Tools to Predict the Impact of Missense Variants !]]></title>
	<description><![CDATA[<p><span>Prioritizing missense variants for further experimental investigation is a key challenge in current sequencing studies for exploring complex and Mendelian diseases. A large number of&nbsp;</span><em>in silico</em><span>&nbsp;tools have been employed for the task of pathogenicity prediction, including PolyPhen‐2, SIFT, FatHMM, MutationTaster‐2, MutationAssessor, Combined Annotation Dependent Depletion, LRT, phyloP, and GERP++, as well as optimized methods of combining tool scores, such as Condel and Logit. Due to the wealth of these methods, an important practical question to answer is which of these tools generalize best, that is, correctly predict the pathogenic character of new variants. </span></p><p><span>Study of 10 tools on five datasets that such a comparative evaluation of these tools is hindered by two types of circularity: they arise due to (1) the same variants or (2) different variants from the same protein occurring both in the datasets used for training and for evaluation of these tools, which may lead to overly optimistic results. Comparative evaluations of predictors that do not address these types of circularity may erroneously conclude that circularity confounded tools are most accurate among all tools, and may even outperform optimized combinations of tools.</span></p><p><span>Following tools are useful for mis sense muation detection ...&nbsp;</span></p><p>PolyPhen‐2 (PP2)<br />&ldquo;Predicts possible impact of an amino acid substitution on the structure and function of a human protein using straightforward physical and comparative considerations&rdquo;</p><p>MutationTaster‐2 (MT2)<br />&ldquo;Evaluation of the disease‐causing potential of DNA sequence alterations&rdquo;</p><p>MutationAssessor (MASS)<br />&ldquo;Predicts the functional impact of amino acid substitutions in proteins, such as mutations discovered in cancer or missense polymorphisms&rdquo;</p><p>LRT<br />&ldquo;Identify a subset of deleterious mutations that disrupt highly conserved amino acids within protein‐coding sequences, which are likely to be unconditionally deleterious&rdquo;</p><p>SIFT<br />&ldquo;Predicts whether an amino acid substitution affects protein function&rdquo;</p><p>GERP++<br />&ldquo;Identifies constrained elements in multiple alignments by quantifying substitution deficits. These deficits represent substitutions that would have occurred if the element were neutral DNA, but did not occur because the element has been under functional constraint. We refer to these deficits as &ldquo;rejected substitutions.&rdquo; Rejected substitutions are a natural measure of constraint that reflects the strength of past purifying selection on the element&rdquo;</p><p>phyloP<br />&ldquo;Compute conservation or acceleration P values based on an alignment and a model of neutral evolution&rdquo;</p><p>FatHMM unweighted (FatHMM‐U)<br />Predicts &ldquo;functional consequences of both coding variants, that is, nonsynonymous single‐nucleotide variants, and noncoding variants&rdquo;</p><p>FatHMM weighted (FatHMM‐W)<br />Predicts &ldquo;functional consequences of both coding variants, that is, nonsynonymous single‐nucleotide variants, and noncoding variants&rdquo; and its weighting scheme attributes higher tolerance scores to SNVs in proteins, related proteins, or domains that already include a high fraction of pathogenic variantsh</p><p>Combined Annotation Dependent Depletion (CADD)<br />&ldquo;CADD is a tool for scoring the deleteriousness of single‐nucleotide variants as well as insertion/deletions variants in the human genome&rdquo;</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/7215/postdoc-positions-in-computational-biology-center-for-genomic-science-milan-italy</guid>
  <pubDate>Thu, 12 Dec 2013 18:34:47 -0600</pubDate>
  <link></link>
  <title><![CDATA[Postdoc positions in computational biology - Center for Genomic Science - Milan, Italy]]></title>
  <description><![CDATA[
<p>Job Description: three postdoc positions in computational biology are available at the Center for Genomic Science in Milan (Italy):</p>

<p>- Development of computational methods to investigate the interplay between epigenetic and genetic layers and their role in tumor progression, by integrating genomic, epigenomic and transcriptional data. PI: Mattia Pelizzola (http://tiny.cc/comEpi)<br />- Epigenome and transcriptome analysis in mouse models of Hepatocellular Carcinoma. PI: Bruno Amati - Small and long non-coding RNAs in cancer stem cells. PI: Francesco Nicassio</p>

<p>All projects will benefit from the availability of both in-house and publicly available next-generation sequencing datasets. Familiarity with Linux environment, programming skills (especially in R) and a background in either computational biology, or physics/engineering/math will be advantageous.</p>

<p>Deadline for the application January 6th, to apply: http://genomics.iit.it/resources.html</p>

<p>Start date: March 1st, 2014</p>

<p>Duration: 1+2 years</p>

<p>Contact Person (Referent): Mattia Pelizzola</p>

<p>Ref. E-Mail: mattia.pelizzola@iit.it</p>

<p>Tel: 0039-02-94375058<br />Group Web Page: http://genomics.iit.it</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36497/installing-python-numpy</guid>
	<pubDate>Mon, 07 May 2018 04:31:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36497/installing-python-numpy</link>
	<title><![CDATA[Installing  python-numpy !]]></title>
	<description><![CDATA[<p>$ sudo apt-get install python-numpy python-scipy python-matplotlib ipython ipython-notebook python-pandas python-sympy python-nose<br />[sudo] password for urbe: <br />Reading package lists... Done<br />Building dependency tree <br />Reading state information... Done<br />The following packages were automatically installed and are no longer required:<br /> bridge-utils containerd linux-headers-4.4.0-116 linux-headers-4.4.0-116-generic linux-headers-4.4.0-21 linux-headers-4.4.0-21-generic<br /> linux-image-4.4.0-116-generic linux-image-4.4.0-21-generic linux-image-extra-4.4.0-116-generic linux-image-extra-4.4.0-21-generic<br /> linux-signed-image-4.4.0-116-generic runc ubuntu-fan<br />Use 'sudo apt autoremove' to remove them.<br />The following additional packages will be installed:<br /> blt fonts-lyx fonts-mathjax ipython-notebook-common isympy libaec0 libamd2.4.1 libdsdp-5.8gf libglpk36 libgsl2 libhdf5-10 libjs-highlight<br /> libjs-highlight.js libjs-jquery-ui libjs-marked libjs-mathjax libjs-underscore libsz2 python-antlr python-bs4 python-chardet python-cvxopt<br /> python-cycler python-dateutil python-decorator python-glade2 python-gmpy python-html5lib python-imaging python-jdcal python-jinja2 python-joblib<br /> python-lxml python-markupsafe python-matplotlib-data python-mpmath python-numexpr python-openpyxl python-pandas-lib python-patsy python-pexpect<br /> python-pil python-ptyprocess python-py python-pycurl python-pyglet python-pymysql python-pyparsing python-pytest python-simplegeneric<br /> python-simplejson python-statsmodels python-statsmodels-lib python-sympy-doc python-tables python-tables-data python-tables-lib python-tk<br /> python-tornado python-tz python-xlrd python-xlwt python-zmq tk8.6-blt2.5 ttf-bitstream-vera<br />Suggested packages:<br /> blt-demo ipython-doc ipython-qtconsole python-pygments nodejs pandoc libiodbc2-dev libmysqlclient-dev gsl-ref-psdoc | gsl-doc-pdf | gsl-doc-info<br /> | gsl-ref-html libjs-jquery-ui-docs fonts-mathjax-extras libjs-mathjax-doc python-gtk2-doc python-genshi python-jinja2-doc python-lxml-dbg<br /> python-lxml-doc ffmpeg inkscape python-cairocffi python-configobj python-excelerator python-matplotlib-doc python-qt4 python-sip python-traits<br /> python-wxgtk3.0 ttf-staypuft python-gmpy2 python-mpmath-doc python-coverage python-nose-doc python-numpy-dbg python-numpy-doc python-pandas-doc<br /> python-patsy-doc python-pexpect-doc python-pil-doc python-pil-dbg subversion python-pytest-xdist libcurl4-gnutls-dev python-pycurl-dbg<br /> python-pycurl-doc python-pymysql-doc python-mock python-scipy-doc python-statsmodels-doc python-tables-doc python-netcdf vitables tix<br /> python-tk-dbg<br />The following NEW packages will be installed:<br /> blt fonts-lyx fonts-mathjax ipython ipython-notebook ipython-notebook-common isympy libaec0 libamd2.4.1 libdsdp-5.8gf libglpk36 libgsl2<br /> libhdf5-10 libjs-highlight libjs-highlight.js libjs-jquery-ui libjs-marked libjs-mathjax libjs-underscore libsz2 python-antlr python-bs4<br /> python-chardet python-cvxopt python-cycler python-dateutil python-decorator python-glade2 python-gmpy python-html5lib python-imaging<br /> python-jdcal python-jinja2 python-joblib python-lxml python-markupsafe python-matplotlib python-matplotlib-data python-mpmath python-nose<br /> python-numexpr python-numpy python-openpyxl python-pandas python-pandas-lib python-patsy python-pexpect python-pil python-ptyprocess python-py<br /> python-pycurl python-pyglet python-pymysql python-pyparsing python-pytest python-scipy python-simplegeneric python-simplejson python-statsmodels<br /> python-statsmodels-lib python-sympy python-sympy-doc python-tables python-tables-data python-tables-lib python-tk python-tornado python-tz<br /> python-xlrd python-xlwt python-zmq tk8.6-blt2.5 ttf-bitstream-vera<br />0 upgraded, 73 newly installed, 0 to remove and 35 not upgraded.<br />Need to get 49,5 MB of archives.<br />After this operation, 271 MB of additional disk space will be used.<br />Do you want to continue? [Y/n] Y<br />Get:1 http://be.archive.ubuntu.com/ubuntu xenial-updates/main amd64 python-pymysql all 0.7.2-1ubuntu1 [56,4 kB]<br />Get:2 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 tk8.6-blt2.5 amd64 2.5.3+dfsg-3 [574 kB]<br />Get:3 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 blt amd64 2.5.3+dfsg-3 [4.852 B]<br />Get:4 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 fonts-lyx all 2.1.4-2 [161 kB]<br />Get:5 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 fonts-mathjax all 2.6.1-1 [960 kB]<br />Get:6 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 python-decorator all 4.0.6-1 [9.326 B]<br />Get:7 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-ptyprocess all 0.5-1 [12,9 kB]<br />Get:8 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-pexpect all 4.0.1-1 [40,5 kB]<br />Get:9 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 python-simplegeneric all 0.8.1-1 [11,5 kB]<br />Get:10 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[2.252 kB]<br />Get:64 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-sympy-doc all 0.7.6.1-1 [4.774 kB]<br />Get:65 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-tables-lib amd64 3.2.2-2 [353 kB]<br />Get:66 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-tables-data all 3.2.2-2 [45,3 kB]<br />Get:67 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-tables all 3.2.2-2 [335 kB]<br />Get:68 http://be.archive.ubuntu.com/ubuntu xenial-updates/main amd64 python-tk amd64 2.7.12-1~16.04 [26,3 kB]<br />Get:69 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-xlrd all 0.9.4-1 [107 kB]<br />Get:70 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-xlwt all 0.7.5+debian1-1 [83,5 kB]<br />Get:71 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-scipy amd64 0.17.0-1 [8.733 kB]<br />Get:72 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-statsmodels-lib amd64 0.6.1-4 [173 kB]<br />Get:73 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-statsmodels all 0.6.1-4 [2.581 kB]<br />Fetched 49,5 MB in 0s (52,8 MB/s) <br />Extracting templates from packages: 100%<br />Selecting previously unselected package python-pymysql.<br />(Reading database ... 435155 files and directories currently installed.)<br />Preparing to unpack .../python-pymysql_0.7.2-1ubuntu1_all.deb ...<br />Unpacking python-pymysql (0.7.2-1ubuntu1) ...<br />Selecting previously unselected package tk8.6-blt2.5.<br />Preparing to unpack .../tk8.6-blt2.5_2.5.3+dfsg-3_amd64.deb ...<br />Unpacking tk8.6-blt2.5 (2.5.3+dfsg-3) ...<br />Selecting previously unselected package blt.<br />Preparing to unpack .../blt_2.5.3+dfsg-3_amd64.deb ...<br />Unpacking blt (2.5.3+dfsg-3) ...<br />Selecting previously unselected package fonts-lyx.<br />Preparing to unpack .../fonts-lyx_2.1.4-2_all.deb ...<br />Unpacking fonts-lyx (2.1.4-2) ...<br />Selecting previously unselected package 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python-statsmodels-lib (0.6.1-4) ...<br />Selecting previously unselected package python-statsmodels.<br />Preparing to unpack .../python-statsmodels_0.6.1-4_all.deb ...<br />Unpacking python-statsmodels (0.6.1-4) ...<br />Processing triggers for libc-bin (2.23-0ubuntu10) ...<br />Processing triggers for fontconfig (2.11.94-0ubuntu1.1) ...<br />Processing triggers for man-db (2.7.5-1) ...<br />Processing triggers for hicolor-icon-theme (0.15-0ubuntu1) ...<br />Processing triggers for gnome-menus (3.13.3-6ubuntu3.1) ...<br />Processing triggers for desktop-file-utils (0.22-1ubuntu5.1) ...<br />Processing triggers for mime-support (3.59ubuntu1) ...<br />Processing triggers for doc-base (0.10.7) ...<br />Processing 5 added doc-base files...<br />Setting up python-pymysql (0.7.2-1ubuntu1) ...<br />Setting up tk8.6-blt2.5 (2.5.3+dfsg-3) ...<br />Setting up blt (2.5.3+dfsg-3) ...<br />Setting up fonts-lyx (2.1.4-2) ...<br />Setting up fonts-mathjax (2.6.1-1) ...<br />Setting up 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...<br />Setting up libglpk36:amd64 (4.57-1build3) ...<br />Setting up libgsl2:amd64 (2.1+dfsg-2) ...<br />Setting up libsz2:amd64 (0.3.2-1) ...<br />Setting up libhdf5-10:amd64 (1.8.16+docs-4ubuntu1) ...<br />Setting up python-antlr (2.7.7+dfsg-6ubuntu1) ...<br />Setting up python-bs4 (4.4.1-1) ...<br />Setting up python-chardet (2.3.0-2) ...<br />Setting up libdsdp-5.8gf (5.8-9.1ubuntu2) ...<br />Setting up python-cvxopt (1.1.4-1.4) ...<br />Setting up python-cycler (0.9.0-1) ...<br />Setting up python-dateutil (2.4.2-1) ...<br />Setting up python-glade2 (2.24.0-4ubuntu1) ...<br />Setting up python-gmpy (1.17-1) ...<br />Setting up python-html5lib (0.999-4) ...<br />Setting up python-pil:amd64 (3.1.2-0ubuntu1.1) ...<br />Setting up python-imaging (3.1.2-0ubuntu1.1) ...<br />Setting up python-jdcal (1.0-1build1) ...<br />Setting up python-joblib (0.9.4-1) ...<br />Setting up python-lxml (3.5.0-1build1) ...<br />Setting up ttf-bitstream-vera (1.10-8) ...<br />Setting up python-matplotlib-data (1.5.1-1ubuntu1) ...<br />Setting up python-pyparsing (2.0.3+dfsg1-1ubuntu0.1) ...<br />Setting up python-tz (2014.10~dfsg1-0ubuntu2) ...<br />Setting up python-numpy (1:1.11.0-1ubuntu1) ...<br />Setting up python-matplotlib (1.5.1-1ubuntu1) ...<br />Setting up python-mpmath (0.19-3) ...<br />Setting up python-nose (1.3.7-1) ...<br />Setting up python-numexpr (2.4.3-1ubuntu1) ...<br />Setting up python-openpyxl (2.3.0-1) ...<br />Setting up python-pandas-lib (0.17.1-3ubuntu2) ...<br />Setting up python-pandas (0.17.1-3ubuntu2) ...<br />Setting up python-patsy (0.4.1-2) ...<br />Setting up python-py (1.4.31-1) ...<br />Setting up python-pyglet (1.1.4.dfsg-3) ...<br />Setting up python-pytest (2.8.7-4) ...<br />Setting up python-simplejson (3.8.1-1ubuntu2) ...<br />Setting up python-sympy (0.7.6.1-1) ...<br />Setting up python-sympy-doc (0.7.6.1-1) ...<br />Setting up python-tables-lib (3.2.2-2) ...<br />Setting up python-tables-data (3.2.2-2) ...<br />Setting up python-tables (3.2.2-2) ...<br />Setting up python-tk (2.7.12-1~16.04) ...<br />Setting up python-xlrd (0.9.4-1) ...<br />Setting up python-xlwt (0.7.5+debian1-1) ...<br />Setting up python-scipy (0.17.0-1) ...<br />Setting up python-statsmodels-lib (0.6.1-4) ...<br />Setting up python-statsmodels (0.6.1-4) ...<br />Processing triggers for libc-bin (2.23-0ubuntu10) ...<br />➜ redundans git:(master) ✗ python2 redundans.py -v -i test/*_?.fq.gz -f test/contigs.fa -o test/run1<br />Options: Namespace(fasta='test/contigs.fa', fastq=['test/5000_1.fq.gz', 'test/5000_2.fq.gz', 'test/600_1.fq.gz', 'test/600_2.fq.gz'], identity=0.51, iters=2, joins=5, limit=0.2, linkratio=0.7, log=', mode 'w' at 0x7f85d1de31e0&gt;, longreads=[], mapq=10, mem=16, minLength=200, nocleaning=True, nogapclosing=True, norearrangements=False, noreduction=True, noscaffolding=True, outdir='test/run1', overlap=0.8, reference='', resume=False, threads=4, tmp='/tmp', usebwa=False, verbose=True)</p><p>##################################################<br />[Mon May 7 11:29:18 2018] Reduction...<br />#file name genome size contigs heterozygous size [%] heterozygous contigs [%] identity [%] possible joins homozygous size [%] homozygous contigs [%]<br />/usr/lib/python2.7/dist-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.<br /> warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')<br />test/run1/contigs.fa 163897 245 66377 40.50 221 90.20 94.854 0 97520 59.50 24 9.80</p><p>##################################################<br />[Mon May 7 11:29:29 2018] Estimating parameters of libraries...<br /> Aligning 19504 mates per library...<br />Insert size statistics Mates orientation stats<br />FastQ files read length median mean stdev FF FR RF RR<br />test/5000_1.fq.gz test/5000_2.fq.gz 50 4998 4990.20 721.47 0 4674 0 0<br />test/600_1.fq.gz test/600_2.fq.gz 100 599 598.63 47.68 0 10000 0 0</p><p>##################################################<br />[Mon May 7 11:29:29 2018] Scaffolding...<br /> iteration 1.1: test/run1/contigs.reduced.fa 24 97520 39.355 17 94157 7321 2195 0 29603<br /> 19505 pairs. 17302 passed filtering [88.71%]. 1627 in different contigs [8.34%].<br /> 1526 pairs. 558 in different contigs [36.57%].<br /> iteration 1.2: test/run1/_sspace.1.1.fa 3 97626 39.344 3 97626 87536 6063 821 87536<br /> 19505 pairs. 17607 passed filtering [90.27%]. 182 in different contigs [0.93%].<br /> 1077 pairs. 124 in different contigs [11.51%].<br /> iteration 2.1: test/run1/_sspace.1.2.fa 3 97626 39.344 3 97626 87536 6063 821 87536<br /> 19505 pairs. 15112 passed filtering [77.48%]. 1295 in different contigs [6.64%].<br /> 3417 pairs. 396 in different contigs [11.59%].<br /> iteration 2.2: test/run1/_sspace.2.1.fa 1 99133 39.344 1 99133 99133 99133 2328 99133<br /> 19505 pairs. 15152 passed filtering [77.68%]. 0 in different contigs [0.00%].<br /> 3398 pairs. 0 in different contigs [0.00%].</p><p>##################################################<br />[Mon May 7 11:29:34 2018] Gap closing...<br /> iteration 1.1: test/run1/scaffolds.fa 1 99133 39.344 1 99133 99133 99133 2328 99133</p><p>##################################################<br />[Mon May 7 11:29:35 2018] Final reduction...<br />#file name genome size contigs heterozygous size [%] heterozygous contigs [%] identity [%] possible joins homozygous size [%] homozygous contigs [%]<br />[WARNING] Nothing reduced!<br />test/run1/scaffolds.filled.fa 99390 1 0 0.00 0 0.00 0.000 0 99390 100.00 1 100.00</p><p>##################################################<br />[Mon May 7 11:29:35 2018] Reporting statistics...<br />#fname contigs bases GC [%] contigs &gt;1kb bases in contigs &gt;1kb N50 N90 Ns longest<br />test/contigs.fa 245 163897 40.298 24 117391 3975 233 0 29603<br />test/run1/contigs.fa 245 163897 40.298 24 117391 3975 233 0 29603<br />test/run1/contigs.reduced.fa 24 97520 39.355 17 94157 7321 2195 0 29603<br />test/run1/_sspace.1.1.fa 3 97626 39.344 3 97626 87536 6063 821 87536<br />test/run1/_sspace.1.2.fa 3 97626 39.344 3 97626 87536 6063 821 87536<br />test/run1/_sspace.2.1.fa 1 99133 39.344 1 99133 99133 99133 2328 99133<br />test/run1/_sspace.2.2.fa 1 99133 39.344 1 99133 99133 99133 2328 99133<br />test/run1/scaffolds.fa 1 99133 39.344 1 99133 99133 99133 2328 99133<br />test/run1/_gapcloser.1.1.fa 1 99390 39.689 1 99390 99390 99390 2 99390<br />test/run1/scaffolds.filled.fa 1 99390 39.689 1 99390 99390 99390 2 99390<br />test/run1/scaffolds.reduced.fa 1 99390 39.689 1 99390 99390 99390 2 99390</p><p>##################################################<br />[Mon May 7 11:29:35 2018] Cleaning-up...<br />#Time elapsed: 0:00:17.376924</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/7383/embo-practical-course-on-bioinformatics-and-genomes-analyses-at-hellenic-pasteur-institute-athens-greece</guid>
  <pubDate>Sat, 21 Dec 2013 10:00:24 -0600</pubDate>
  <link></link>
  <title><![CDATA[EMBO practical Course on  "Bioinformatics and Genomes Analyses" at Hellenic Pasteur Institute, Athens, Greece]]></title>
  <description><![CDATA[
<p>The main objectives of this Practical Course are to strengthen skills <br />of PhD students and young researchers in the domain of Bioinformatics <br />and Genome Data Analyses on the use of advanced fundamental algorithms <br />and their applications in genome studies.</p>

<p>The course topics will include theoretical and practical aspects in:<br />- Genomes comparisons,<br />- Evolutionary analyses (orthologs, paralogs and ancestral genomes <br />inference),<br />- RNAseq and Next Generation Sequencing (including algorithms, methods <br />and sequence mapping tools, data analyses and applications).</p>

<p>The course programme will be centred on theoretical presentations <br />followed by practical sessions. Practical sessions in a Linux <br />environment will involve Unix shell and Perl scripting. Participants <br />are assumed to be familiar with this environment.</p>

<p>A series of lectures delivered by prominent scientists on recent hot <br />topics in genome (Viruses, Prokaryotes, Eukaryotes) studies will be <br />included in the programme and future research perspectives will be <br />highlighted.</p>

<p>The topics that will be included in the course programme are similar <br />to those included in previously organized courses:http://www.pasteur.fr/~tekaia/BGA_courses.html</p>

<p>The course is aimed at motivated Ph.D students and Post-Doctoral <br />Researchers in Academic Institutions, with background in Mathematics, <br />Statistics, Biology or Computer Science and who are involved in <br />Bioinformatics and Genomes studies.</p>

<p>Selection of participants will be based on their background, running <br />research projects and on expressed motivations.<br />Selected students will have free accommodation and meals and are <br />expected to contribute with 200 euros and to pay for their travel <br />expenses.<br />All participants (students and invited speakers) will stay in the same <br />hotel.</p>

<p>Detailed indications are available on the course web site: http://events.embo.org/14-comparative-genomics/index.html</p>

<p>Candidates are advised to complete carefully the application form, <br />together with an abstract of at least one of their running projects, a <br />"one-page CV" and a personal Identity Picture (Photo).</p>

<p>The application deadline is March 14, 2014.</p>

<p>The organizers:<br />Menelaos Manoussakis, Hellenic Pasteur Institute, Athens, Greece.<br />Evdokia Karagouni, Hellenic Pasteur Institute, Athens - Greece.<br />Evie Melanitou,  Institut Pasteur Paris - France.<br />Fredj Tekaia ( Institut Pasteur Paris France)<br />URL: http://www.pasteur.fr/~tekaia/BGA_courses.html</p>

<p>Date: 5 – 17 May, 2014. <br />More at http://events.embo.org/14-comparative-genomics/index.html<br />will take place in the ,</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36518/mix-combining-multiple-assemblies-from-ngs-data</guid>
	<pubDate>Tue, 08 May 2018 04:58:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36518/mix-combining-multiple-assemblies-from-ngs-data</link>
	<title><![CDATA[MIX: Combining multiple assemblies from NGS data]]></title>
	<description><![CDATA[<p>Mix is a tool that combines two or more draft assemblies, without relying on a reference genome and has the goal to reduce contig fragmentation and thus speed-up genome finishing. The proposed algorithm builds an extension graph where vertices represent extremities of contigs and edges represent existing alignments between these extremities. These alignment edges are used for contig extension. The resulting output assembly corresponds to a path in the extension graph that maximizes the cumulative contig length.</p>
<p>The Mix algorithm, approach and results were published in BMC bioinformatics :&nbsp;<a href="http://www.biomedcentral.com/1471-2105/14/S15/S16">http://www.biomedcentral.com/1471-2105/14/S15/S16</a>.</p><p>Address of the bookmark: <a href="https://github.com/cbib/MIX" rel="nofollow">https://github.com/cbib/MIX</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/7568/oldest-hominin-dna-sequenced</guid>
	<pubDate>Fri, 27 Dec 2013 19:58:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/7568/oldest-hominin-dna-sequenced</link>
	<title><![CDATA[Oldest Hominin DNA Sequenced]]></title>
	<description><![CDATA[<p>Matthias Meyer and his team from the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany, have developed new techniques for retrieving and sequencing highly degraded ancient DNA. They then joined forces with Juan-Luis Arsuaga and applied the new techniques to a cave bear from the Sima de los Huesos site. After this success, the researchers sampled two grams of bone powder from a hominin thigh bone from the cave. They extracted its DNA and sequenced the genome of the mitochondria or mtDNA, a small part of the genome that is passed down along the maternal line and occurs in many copies per cell. The researchers then compared this ancient mitochondrial DNA with Neandertals, Denisovans, present-day humans, and apes.<br /><br />From the missing mutations in the old DNA sequences the researchers calculated that the Sima hominin lived about 400,000 years ago. They also found that it shared a common ancestor with the Denisovans, an extinct archaic group from Asia related to the Neandertals, about 700,000 years ago. "The fact that the mtDNA of the Sima de los Huesos hominin shares a common ancestor with Denisovan rather than Neandertal mtDNAs is unexpected since its skeletal remains carry Neandertal-derived features," says Matthias Meyer. Considering their age and Neandertal-like features, the Sima hominins were likely related to the population ancestral to both Neandertals and Denisovans. Another possibility is that gene flow from yet another group of hominins brought the Denisova-like mtDNA into the Sima hominins or their ancestors.<br /><br /></p><p>Reference</p><p>http://www.sciencedaily.com/releases/2013/12/131204132018.htm</p>]]></description>
	<dc:creator>Surajeet</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38004/vcfr-a-package-to-manipulate-and-visualize-vcf-data-in-r</guid>
	<pubDate>Thu, 25 Oct 2018 09:05:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38004/vcfr-a-package-to-manipulate-and-visualize-vcf-data-in-r</link>
	<title><![CDATA[vcfR:  a package to manipulate and visualize VCF data in R]]></title>
	<description><![CDATA[<p><span>VcfR is an R package intended to allow easy manipulation and visualization of variant call format (VCF) data. Functions are provided to rapidly read from and write to VCF files. Once VCF data is read into R a parser function extracts matrices from the VCF data for use with typical R functions. This information can then be used for quality control or other purposes. Additional functions provide visualization of genomic data. Once processing is complete data may be written to a VCF file or converted into other popular R objects (e.g., genlight, DNAbin). VcfR provides a link between VCF data and the R environment connecting familiar software with genomic data.</span></p><p>Address of the bookmark: <a href="https://github.com/knausb/vcfR" rel="nofollow">https://github.com/knausb/vcfR</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43997/tools-for-rna-classification</guid>
	<pubDate>Tue, 08 Nov 2022 03:39:11 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43997/tools-for-rna-classification</link>
	<title><![CDATA[Tools for RNA classification]]></title>
	<description><![CDATA[<p><span>barrnap</span>&nbsp;-&nbsp;<a href="https://github.com/tseemann/barrnap" target="_blank">https://github.com/tseemann/barrnap</a></p><p><span>CPAT</span>&nbsp;-&nbsp;<a href="https://github.com/liguowang/cpat" target="_blank">https://github.com/liguowang/cpat</a>,&nbsp;<a href="http://lilab.research.bcm.edu/" target="_blank">http://lilab.research.bcm.edu/</a>&nbsp;(web server)</p><p><span>CPC2</span>&nbsp;-&nbsp;<a href="https://github.com/gao-lab/CPC2_standalone" target="_blank">https://github.com/gao-lab/CPC2_standalone</a>,&nbsp;<a href="http://cpc2.gao-lab.org/" target="_blank">http://cpc2.gao-lab.org/</a>&nbsp;(web server)</p><p><span>Infernal</span>&nbsp;-&nbsp;<a href="http://eddylab.org/infernal/" target="_blank">http://eddylab.org/infernal/</a>,&nbsp;<a href="https://github.com/EddyRivasLab/infernal" target="_blank">https://github.com/EddyRivasLab/infernal</a></p><p><span>NCBI RefSeq</span>&nbsp;-&nbsp;<a href="https://www.ncbi.nlm.nih.gov/refseq/" target="_blank">https://www.ncbi.nlm.nih.gov/refseq/</a></p><p><span>Rfam</span>&nbsp;-&nbsp;<a href="http://rfam.xfam.org/" target="_blank">http://rfam.xfam.org/</a>,&nbsp;<a href="https://docs.rfam.org/en/latest/index.html" target="_blank">https://docs.rfam.org/en/latest/index.html</a></p><p><span>SILVA</span>&nbsp;-&nbsp;<a href="https://www.arb-silva.de/" target="_blank">https://www.arb-silva.de/</a></p><p><span>RNAmmer</span>&nbsp;-&nbsp;<a href="http://www.cbs.dtu.dk/services/RNAmmer/" target="_blank">http://www.cbs.dtu.dk/services/RNAmmer/</a>&nbsp;(web server, standalone download link)</p>]]></description>
	<dc:creator>Abhi</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/8174/the-2014-cemm-phd-program</guid>
  <pubDate>Wed, 05 Feb 2014 06:03:15 -0600</pubDate>
  <link></link>
  <title><![CDATA[The 2014 CeMM PhD Program]]></title>
  <description><![CDATA[
<p>For our next PhD Program starting in October 2014 we are looking for exceptionally motivated PhD candidates with a keen interest in genomics and medicine and a strong interest to work in teams.</p>

<p>The 2014 CeMM PhD Program will focus on two thematic areas: INFECTION and CANCER, that are built on the pillars of epigenetics, bioinformatics and systems biology, chemical biology and the mechanism of action of drugs, high-throughput genetics, genomics and proteomics, and molecular and cell biology.</p>

<p>The choice of this strategic focus rests on the synergies between immunology, infection and cancer in pathophysiological and technological terms. It furthermore reflects the strength of the current CeMM faculty, itself built around the historical and contemporary expertise in immunology and cancer of the Medical University of Vienna.</p>

<p>As a CeMM PhD student you will get the chance to work at the cutting edge of interdisciplinary molecular medicine research and be trained by the entire CeMM and associated faculty to become one of the scientists shaping the future of molecular medicine.<br />Requirements</p>

<p>To be eligible to enroll in the CeMM PhD Program all candidates are required to have a bachelor’s or master’s degree in medicine, biology, chemistry, bioinformatics, mathematics or any scientific/technical, subject-relevant degree. Candidates do not need to have completed their degree at the time of application, however they must have obtained their final degree certificate by mid-September. The working language at CeMM is English, so excellent written and oral communication skills in English are required.<br />Timeline</p>

<p>    Applications open on 20th January and close on 20th March 2014.<br />    Two references are required to be submitted through the online system by 31st March 2014.<br />    All complete candidate applications are reviewed by the CeMM Faculty in early April.<br />    Selected candidates are invited to a Skype panel interview in late April.<br />    Shortlisted candidates are then invited to Vienna in May for a full interview process, including an opportunity to introduce yourself through a presentation and interview rounds, meet research group members, and attend an informal dinner to get to know the Faculty members and learn more about their research.<br />    Positions are offered by CeMM Faculty in June.<br />    Start of PhD Program: 1st October 2014 .</p>

<p>Contact</p>

<p>Binia Maria Günther, BEd BA<br />Human Resources Manager<br />bguenther@cemm.oeaw.ac.at</p>

<p>Catherine Lloyd, Ph.D.<br />PhD and Postdoc Program Manager<br />clloyd@cemm.oeaw.ac.at</p>

<p>More Info: www.cemm.oeaw.ac.at/phd-program/application/</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42972/list-of-bioinformatics-workflow-management-tools</guid>
	<pubDate>Sat, 20 Mar 2021 00:15:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42972/list-of-bioinformatics-workflow-management-tools</link>
	<title><![CDATA[List of bioinformatics workflow management tools !]]></title>
	<description><![CDATA[<h3>Here are list of&nbsp;Workflow Managers</h3><ul>
<li><span><a href="https://github.com/pcingola/BigDataScript">BigDataScript</a></span>&nbsp;&ndash; A cross-system scripting language for working with big data pipelines in computer systems of different sizes and capabilities. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/25189778">paper-2014</a>&nbsp;|&nbsp;<a href="https://pcingola.github.io/BigDataScript">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/ssadedin/bpipe">Bpipe</a></span>&nbsp;&ndash; A small language for defining pipeline stages and linking them together to make pipelines. [&nbsp;<a href="http://docs.bpipe.org/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/common-workflow-language/common-workflow-language">Common Workflow Language</a></span>&nbsp;&ndash; a specification for describing analysis workflows and tools that are portable and scalable across a variety of software and hardware environments, from workstations to cluster, cloud, and high performance computing (HPC) environments. [&nbsp;<a href="http://www.commonwl.org/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/broadinstitute/cromwell">Cromwell</a></span>&nbsp;&ndash; A Workflow Management System geared towards scientific workflows. [&nbsp;<a href="https://cromwell.readthedocs.io/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/galaxyproject">Galaxy</a></span>&nbsp;&ndash; a popular open-source, web-based platform for data intensive biomedical research. Has several features, from data analysis to workflow management to visualization tools. [&nbsp;<a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6030816">paper-2018</a>&nbsp;|&nbsp;<a href="https://galaxyproject.org/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/nextflow-io/nextflow">Nextflow</a>&nbsp;(recommended)</span>&nbsp;&ndash; A fluent DSL modelled around the UNIX pipe concept, that simplifies writing parallel and scalable pipelines in a portable manner. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/29412134">paper-2018</a>&nbsp;|&nbsp;<a href="http://nextflow.io/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/cgat-developers/ruffus">Ruffus</a></span>&nbsp;&ndash; Computation Pipeline library for python widely used in science and bioinformatics. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/20847218">paper-2010</a>&nbsp;|&nbsp;<a href="http://www.ruffus.org.uk/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/SeqWare/seqware">SeqWare</a></span>&nbsp;&ndash; Hadoop Oozie-based workflow system focused on genomics data analysis in cloud environments. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/21210981">paper-2010</a>&nbsp;|&nbsp;<a href="https://seqware.github.io/">web</a>&nbsp;]</li>
<li><span><a href="https://bitbucket.org/snakemake">Snakemake</a></span>&nbsp;&ndash; A workflow management system in Python that aims to reduce the complexity of creating workflows by providing a fast and comfortable execution environment. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/29788404">paper-2018</a>&nbsp;|&nbsp;<a href="https://snakemake.readthedocs.io/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/broadinstitute/wdl">Workflow Descriptor Language</a></span>&nbsp;&ndash; Workflow standard developed by the Broad. [&nbsp;<a href="https://software.broadinstitute.org/wdl">web</a>&nbsp;]</li>
</ul>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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