<?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/13415?offset=100</link>
	<atom:link href="https://bioinformaticsonline.com/related/13415?offset=100" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/41039/phd-position-in-translational-medicine</guid>
  <pubDate>Sat, 15 Feb 2020 06:07:19 -0600</pubDate>
  <link></link>
  <title><![CDATA[PhD position in Translational Medicine]]></title>
  <description><![CDATA[
<p>https://www.jobvector.de/jobs-stellenangebote/biologie-life-sciences/wissenschaftliche-r-mitarbeiter-in/phd-position-translational-medicine-129981.html?suid=1b510358c7578e8f75cf04a464fc21a404a574ca</p>

<p>Essential experience / qualifications:<br />Master / Diploma in Biology, Biochemistry, Molecular Medicine or similar; solid knowledge of molecular and cell biological techniques; good English knowledge</p>

<p>Applications:<br />Please send your application (including CV, letter of motivation, contact information of two references, and list of publication) by 13.03.2020 at the latest to:</p>

<p>Universitätsklinikum Erlangen<br />Chirurgische Klinik<br />Translational Research Center<br />Prof. Dr. rer. nat. Michael Stürzl<br />Schwabachanlage 12<br />91054 Erlangen<br />E-Mail: michael.stuerzl@uk-erlangen.de</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42271/mcclintock-meta-pipeline-to-identify-transposable-element-insertions-using-next-generation-sequencing-data</guid>
	<pubDate>Tue, 27 Oct 2020 00:21:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42271/mcclintock-meta-pipeline-to-identify-transposable-element-insertions-using-next-generation-sequencing-data</link>
	<title><![CDATA[McClintock: Meta-pipeline to identify transposable element insertions using next generation sequencing data]]></title>
	<description><![CDATA[<p><span>an integrated bioinformatics pipeline for the detection of TE insertions in whole-genome shotgun data, called McClintock (</span><a href="https://github.com/bergmanlab/mcclintock">https://github.com/bergmanlab/mcclintock</a><span>), which automatically runs and standardizes output for multiple TE detection methods. We demonstrate the utility of McClintock by evaluating six TE detection methods using simulated and real genome data from the model microbial eukaryote,&nbsp;</span><em>Saccharomyces cerevisiae</em><span>.&nbsp;</span></p><p>Address of the bookmark: <a href="https://github.com/bergmanlab/mcclintock" rel="nofollow">https://github.com/bergmanlab/mcclintock</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44659/figeno-tool-for-plotting-sequencing-data-along-genomic-coordinates</guid>
	<pubDate>Tue, 17 Sep 2024 02:28:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44659/figeno-tool-for-plotting-sequencing-data-along-genomic-coordinates</link>
	<title><![CDATA[Figeno: Tool for plotting sequencing data along genomic coordinates.]]></title>
	<description><![CDATA[<p><span>Tool for plotting sequencing data along genomic coordinates.</span></p>
<div>
<pre><code>FIGENO is a
  FIGure
    GENerator
for GENOmics</code></pre>
</div>
<p dir="auto">With figeno, you can plot various types of sequencing data along genomic coordinates. Video overview:&nbsp;<a href="https://www.youtube.com/watch?v=h1cBeXoSYTA">https://www.youtube.com/watch?v=h1cBeXoSYTA</a>.</p>
<p dir="auto"><a href="https://github.com/CompEpigen/figeno/blob/main/docs/content/images/figeno.png" target="_blank"><img src="https://github.com/CompEpigen/figeno/raw/main/docs/content/images/figeno.png" alt="figeno" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/CompEpigen/figeno" rel="nofollow">https://github.com/CompEpigen/figeno</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/856/papenfuss-lab</guid>
  <pubDate>Sun, 14 Jul 2013 12:22:28 -0500</pubDate>
  <link></link>
  <title><![CDATA[Papenfuss Lab]]></title>
  <description><![CDATA[
<p>The human genome project and similar projects in disease-causing organisms such as Plasmodium falciparum, which causes malaria in humans, have provided new tools for discovery in biology and have accelerated the development of understanding in human disease.</p>

<p>Research Area: <br />Analysis of Next Generation sequence data in cancer<br />Methods for analysis of structural variation in cancer genomes<br />Next Generation sequencing in malaria<br />Computational comparative genomics<br />Sensitive genomic sequence search techniques using hidden Markov models<br />Tasmanian devil facial tumour disease</p>

<p>Link @ http://www.wehi.edu.au/faculty_members/dr_tony_papenfuss</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4655/mathivanan-lab</guid>
  <pubDate>Fri, 20 Sep 2013 13:09:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[Mathivanan Lab]]></title>
  <description><![CDATA[
<p>The major research interests are in exploring the role of extracellular matrix components (soluble secreted proteins and membrane vesicles) in cancer and intercellular communication. The lab integrates proteomic, genomic and bioinformatics methodologies to explore cancer cells. </p>

<p>More at http://www.mathivananlab.org/index.html</p>

<p>http://scholar.google.com/citations?user=U6PyEdYAAAAJ&amp;hl=en</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4409/huber-lab</guid>
  <pubDate>Mon, 09 Sep 2013 21:57:03 -0500</pubDate>
  <link></link>
  <title><![CDATA[Huber Lab]]></title>
  <description><![CDATA[
<p>The Huber group develops computational and statistical methods to design and analyse novel experimental approaches in genetics and cell biology. </p>

<p>Future projects and goals</p>

<p>Large-scale systematic maps of gene-gene and gene-environment interactions by automated phenotyping, using image analysis, machine learning, sparse model building and causal inference.<br />DNA-, RNA- and ChIP-Seq and their applications to gene expression regulation: statistical and computational foundations.<br />Cancer genomics, genomes as biomarkers, cancer phylogeny.<br />Image analysis for systems biology: measuring the dynamics of cell cycle and of cell migration of individual cells under normal conditions and many different perturbations (RNAi, drugs).</p>

<p>More @ http://www.embl.de/research/units/genome_biology/huber/index.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/4634/immune-response-to-cancer-cells-awesome</guid>
	<pubDate>Fri, 20 Sep 2013 06:20:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/4634/immune-response-to-cancer-cells-awesome</link>
	<title><![CDATA[Immune response to cancer cells! AWESOME]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/C6YuBh-wAPQ" frameborder="0" allowfullscreen></iframe><p>Awesome viddeo explaining the way in which the antibody, HuLuc 63, appears to induce anti-tumor effects by binding to a protein that is only expressed on the surface of myeloma cells. This initiates antibody-dependent cellular cytotoxicity activity that kills myeloma cells and leaves healthy cells intact.</p>]]></description>
	
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5623/yau-group</guid>
  <pubDate>Tue, 15 Oct 2013 13:05:15 -0500</pubDate>
  <link></link>
  <title><![CDATA[Yau Group]]></title>
  <description><![CDATA[
<p>Yau Group are a new research group based at the Wellcome Trust Centre for Human Genetics and the Department of Statistics at the University of Oxford.</p>

<p>Yau Group develops statistical and computational methods for the analysis of genomic datasets with a particular interest in cancer sequencing applications and the use of Bayesian Statistics.</p>

<p>Yau Group are currently have projects in somatic mutation analysis of heterogeneous cancers, data fusion or integration techniques and single cell genomics.</p>

<p>More @ http://www.well.ox.ac.uk/~cyau/index.html</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/5946/bioinformatics-tata-memorial-centre-navi-mumbai</guid>
  <pubDate>Mon, 28 Oct 2013 10:40:25 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics @ TATA MEMORIAL CENTRE, NAVI MUMBAI]]></title>
  <description><![CDATA[
<p>TATA MEMORIAL CENTRE<br />ADVANCED CENTRE FOR TREATMENT, RESEARCH AND EDUCATION IN CANCER<br />KHARGHAR, NAVI MUMBAI – 410210</p>

<p>No. ACTREC/Advt./ 72 /2013</p>

<p>WALK IN INTERVIEW</p>

<p>1. JRF*<br />Genome-wide RNAi screen with human pooled tyrosine kinase shRNA libraries in head and neck squamous call carcinoma (HNSCC) cell lines<br />DBT A/C No. 3071, Dr. Amit Dutt</p>

<p>2. JRF<br />IRB Project ACTREC Funds<br />Dr. Amit Dutt</p>

<p>3. RA<br />Defining the cancer genome of Head and Neck Squamous Cell Carcinoma (HNSCC) with SNP arrays and next generation sequencing technology<br />A/C No. 2895, Dr. Amit Dutt</p>

<p>Duration of the Project: One year from the date of appointment, or as and when project terminates.</p>

<p>Consolidated Salary: RA : Rs. 40,000/- p.m.<br />JRF* (DBT): Rs. 20,800/- p.m.<br />JRF: Rs. 16,000/- p.m.<br />Date &amp; Time: 6th November, 2013, at 10.00 a.m.</p>

<p>Venue: Conference Room</p>

<p>Minimum Qualifications and Experience:</p>

<p>RA: The ideal applicant should have a PhD in a relevant field. He/she should have a strong computational biology background, with demonstrated experience in coding using Perl, Python, Java or C++. He/she should be familiar with working in unix enviromnent, devising computational algorithms for data analysis, statistical data analysis in R and matlab and database programming using MySQL. Hands on experience in analyzing high throughput data would be an added advantage.</p>

<p>JRF* (DBT project): M.Sc. in Life Sciences or M.Tech in Biotechnology with good academic record (Minimum of 60% aggregate). Valid UGC-CSIR/DBT/ICMR JRF qualification and laboratory experience in molecular biology. Previous experience in molecular biology and animal tissue culture with high throughput platforms and ability to work with a large team would be desirable.</p>

<p>JRF (ACTREC project): M.Sc. in Life Sciences or M.Tech in Biotechnology with good academic record (Minimum of 60% aggregate). Minimum 2 yrs experience in molecular biology and animal tissue culture with high throughput platforms and ability to work with a large team is essential.</p>

<p>*M.Sc. degree obtained after a one year course will not be considered.</p>

<p>Candidates fulfilling above requirements should send their application by e-mail to<br />‘careers.duttlab@gmail.com. in the format given below so as to reach on or before<br />4th November, 2013.</p>

<p>Advertisement:</p>

<p>http://www.actrec.gov.in/data%20files/2013/AD-RA-JR-TECHN-6-NOV.pdf</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/14756/roderic-guigo-lab</guid>
  <pubDate>Mon, 01 Sep 2014 17:13:00 -0500</pubDate>
  <link></link>
  <title><![CDATA[Roderic Guigó Lab]]></title>
  <description><![CDATA[
<p>Research in our group focuses on the investigation of the signals involved in gene specification in genomic sequences (promoter elements, splice sites, translation initiation sites, etc…). We are interested both in the mechanism of their recognition and processing, and in their evolution. In addition, but related to this basic component of our research, our group is also involved in the development of software for gene prediction and annotation in genomic sequences. Our group also actively participates in the analysis of many eukaryotic genomes and it in involved in the NIH-funded ENCODE project. Furthermore we are members of two large cancer-studies consortia (chronic lymphocytic leukemia "CLL" and Breast Cancer -Hospital del Mar/CRG/Roche-).  <br /> <br />More at http://big.crg.cat/computational_biology_of_rna_processing</p>
]]></description>
</item>

</channel>
</rss>