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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27438?offset=1040</link>
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	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/44400/pevzner-lab</guid>
  <pubDate>Thu, 02 Nov 2023 05:39:26 -0500</pubDate>
  <link></link>
  <title><![CDATA[Pevzner Lab !]]></title>
  <description><![CDATA[
<p>The laboratory works on genome sequencing, immunoproteogenomics, antibiotics sequencing, and comparative genomics - computational technologies that enabled new applications and allowed scientists to attack biological problems that remained beyond the reach of previous techniques.</p>

<p>https://bioalgorithms.ucsd.edu/research4.html</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/7153/phd-student-in-computational-systems-biology</guid>
  <pubDate>Tue, 10 Dec 2013 18:46:05 -0600</pubDate>
  <link></link>
  <title><![CDATA[Ph.D. student in Computational Systems Biology]]></title>
  <description><![CDATA[
<p>Ph.D. student in Computational Systems Biology</p>

<p>Location : The Luxembourg Centre for Systems Biomedicine (LCSB) at the University of Luxembourg, Luxembourg, Luxembourg<br />Deadline for applications : unknown.<br />Description :</p>

<p>The Luxembourg Centre for Systems Biomedicine (LCSB) was created within the Health Technologies Initiative from the Government of Luxembourg as one of the research priorities of the University of Luxembourg. The LCSB is an Interdisciplinary Centre of the University that combines experimental and computational approaches to analyse complex biological systems and disease processes. The Computational Biology Group (CBG) provides the LCSB with a solid infrastructure in developing theoretical framework for computational modeling on biomedical problems, especially in the area of network biology in the context of cellular programming/reprogramming. The CBG group includes researchers with theoretical, computational and wet lab backgrounds, thereby providing an unusually interdisciplinary environment.<br />The Computational Biology Group seeks a highly-skilled Ph.D. student to work on an exciting project on reconstruction and analysis of an integrated gene regulatory network model to elucidate key mechanisms of cellular reprogramming. The model will rely on the integration and mining of diverse transcriptomics and epigenomics data of different cell types from the Central Nervous System. The Ph.D. student is expected to collaborate with other members of the CBG to develop a computational methodology aiming at designing, in-silico, cellular reprogramming events, with a focus on the nervous system. This project will be carried out in collaboration with Prof. Noel Buckleys lab at Kings College London.<br />Requirements of the ideal candidate:<br />Master degree in Bioinformatics, Computer Science, Biology or a related discipline<br />Prior experience in mathematical modelling of biological networks, especially in network inference and analysis<br />Excellent working knowledge in English.<br />.<br />We offer:<br />Full contract for Ph.D. student for three years with possibility of renewal<br />Opportunity to do applied research to medical problems within a highly dynamic research institution (LCSB) and in collaboration with internationally recognized partners<br />An exciting international environment<br />A very competitive salary</p>

<p>For further information, please contact:</p>

<p>Prof. Dr. Antonio del Sol<br />E-mail: antonio.delsol@uni.lu</p>

<p>Applications should contain the following documents:<br />A detailed curriculum vitae<br />cover letter mentioning the reference number<br />description of past research experience and future interests<br />name and addresses of three referees</p>

<p>All applications should be sent preferably in electronic version until December 31st, 2013 to the following address:</p>

<p>Luxembourg Centre for Systems Biomedicine (LCSB)<br />University of Luxembourg<br />7, avenue des Hauts-Fourneaux<br />L-4362 Esch-sur-Alzette<br />Tel: +352-466644-6982 (Office)<br />Email: antonio.delsol@uni.lu<br />http://www.lcsb.lu</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/6836/research-fellow-mendel-laboratory</guid>
  <pubDate>Tue, 26 Nov 2013 00:07:57 -0600</pubDate>
  <link></link>
  <title><![CDATA[Research Fellow @ Mendel laboratory]]></title>
  <description><![CDATA[
<p>IRCCS Casa Sollievo della Sofferenza – Mendel laboratory is seeking one talented bioinformatician (Rome)<br />Start date: immediate</p>

<p>Duration: 1 year</p>

<p>Funding Source: Institutional<br />Salary on grant: B2 (€ 22.000/year gross)<br />Contact Person (Referent): Tommaso Mazza<br />Ref. E-Mail: t.mazza@css-mendel.it<br />Tel: +39 06 44160526<br />Fax: +39 06 44160548</p>

<p>Job Description: The bioinformatics unit at IRCCS Casa Sollievo della Sofferenza - Mendel laboratory in Rome is looking for one young PhD bioinformatician with specific experience and/or interest in the analysis of transcriptomic data.</p>

<p>The candidate will be mainly in charge of developing research on a range of hot applications and projects, dealing with microarrays, RNA-Seq and miRNA-Seq data. Main activities will be: (i) data analysis (short-reads mapping, variants call and annotation, functional enrichment analysis of gene expression data); (ii) networks analysis and simulation (artificial knockout, redundancy and lethality analysis, gene set essentiality); (iii) developing of ad-hoc software solutions/routines on clusters of CPUs and GPUs.</p>

<p>The correct cultural background (training in Biology / Computer Science / Statistics or a mix of the three) and a strong interest in working with high throughput data analysis will be considered at the same level of specific experience in the above-mentioned fields.<br />Knowledge of molecular modeling and simulation and one of these languages: python, perl, R, Java, C++, C# is a golden plus. Good knowledge of Scientific English will be positively evaluated for this position, together with good presentation and teamwork skills.</p>

<p>A CV with one professional reference, details on educational background and of the biological and/or bioinformatic and/or data analysis skills and experience should be sent by email for a preliminary selection to: Tommaso Mazza, CSS-Mendel: t.mazza@css-mendel.it</p>

<p>Context<br />Casa Sollievo della Sofferenza is an Institute for hospitalization, care, and scientific research located in San Giovanni Rotondo, Italy. It integrates clinical assistance (with inpatient and outpatient facilities) and research. It has an affiliate institute, CSS-Mendel, located in Rome. Between the two sites, it employs over 100 researchers who focus on genetics. The Center is equipped with state of the art genomics technology (SOLiD 5500XL next generation sequencer, Illumina MiSeq, Affymetrix/Agilent microarray platforms, etc) as well as a dedicated high performance computing facility, a non-conventional workstation of GPUs and a short- and long-term storage disk.</p>

<p>Applications<br />Candidates should send:<br />• a cover letter explaining the role they would like to undertake within the Center, even if it is not listed in this job adv, stating clearly why they would be a good fit to the proposed role, and what they would bring to the Center in terms of expertise, ideas, talent;<br />• a CV including a list of publications;<br />• List of referees;</p>

<p>More at http://www.css-mendel.it/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40389/sequila-cov-a-fast-and-scalable-library-for-depth-of-coverage-calculations</guid>
	<pubDate>Sun, 15 Dec 2019 10:19:35 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40389/sequila-cov-a-fast-and-scalable-library-for-depth-of-coverage-calculations</link>
	<title><![CDATA[SeQuiLa-cov: A fast and scalable library for depth of coverage calculations]]></title>
	<description><![CDATA[<p><span>The Docker image is available at&nbsp;</span><a href="https://hub.docker.com/r/biodatageeks/" target="">https://hub.docker.com/r/biodatageeks/</a><span>. Supplementary information on benchmarking procedure as well as test data are publicly accessible at the project documentation site&nbsp;</span><a href="http://biodatageeks.org/sequila/benchmarking/benchmarking.html#depth-of-coverage" target="">http://biodatageeks.org/sequila/benchmarking/benchmarking.html#depth-of-coverage</a><span>. An archival copy of the code and supporting data is also available via the GigaScience database GigaDB</span></p>
<p>&bull; Project name: SeQuiLa-cov</p>
<p>&bull; Project home page:&nbsp;<a href="http://biodatageeks.org/sequila/" target="">http://biodatageeks.org/sequila/</a></p>
<p>&bull; Source code repository:&nbsp;<a href="https://github.com/ZSI-Bio/bdg-sequila" target="">https://github.com/ZSI-Bio/bdg-sequila</a></p>
<p>&bull; Operating system: Platform independent</p>
<p>&bull; Programming language: Scala</p>
<p>&bull; Other requirements: Docker</p>
<p>&bull; License: Apache License 2.0</p><p>Address of the bookmark: <a href="https://academic.oup.com/gigascience/article/8/8/giz094/5543653" rel="nofollow">https://academic.oup.com/gigascience/article/8/8/giz094/5543653</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/7212/bioinformatics-group-at-boku-university</guid>
  <pubDate>Thu, 12 Dec 2013 17:53:10 -0600</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics group at Boku University]]></title>
  <description><![CDATA[
<p>The Bioinformatics group at Boku University has two main areas of interest, underpinning a common goal, the study of complex systems in living organisms. To overcome the engineered redundancies and combinatorial effects prevalent in higher eukaryotes, novel views augmenting the classical gene by gene approaches are required. We combine</p>

<p>1. Work to establish improved quantitative experimental assays (such as microarrays or differential in-gel electrophoresis) and<br />2. Development of modern computational methods (such as hierarchical probabilistic models or integration of heterogeneous data sources)</p>

<p>Lab page @ http://bioinf.boku.ac.at/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/4590/tigers-genome-sequenced</guid>
	<pubDate>Tue, 17 Sep 2013 16:48:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/4590/tigers-genome-sequenced</link>
	<title><![CDATA[Tigers genome sequenced]]></title>
	<description><![CDATA[<p>Fifteen scientists led by Dr Jong Bhak of Genome Research Foundation, South Korea, decoded as many as 3 billion nucleotides (organic molecules that form the basic building blocks of nucleic acids, such as DNA). They identified 20,000 genes related to various functions of the tiger.&nbsp;</p><p>The biggest and perhaps most fearsome of the world's big cats, the tiger, shares 95.6 percent of its DNA with humans' cute and furry companions, domestic cats.</p><p>The new research showed that big cats have genetic mutations that enabled them to be carnivores. The team also identified mutations that allow snow leopards to thrive at high altitudes.</p><p>Reference:</p><p><a href="http://www.nbcnews.com/science/your-cat-ferocious-tigers-share-lot-95-6-percent-their-4B11182690">http://www.nbcnews.com/science/your-cat-ferocious-tigers-share-lot-95-6-percent-their-4B11182690</a></p><p><a href="http://timesofindia.indiatimes.com/home/environment/flora-fauna/Gene-mapping-of-tiger-completed/articleshow/22671681.cms">http://timesofindia.indiatimes.com/home/environment/flora-fauna/Gene-mapping-of-tiger-completed/articleshow/22671681.cms</a></p><p>Paper:</p><p><a href="http://www.nature.com/ncomms/2013/130917/ncomms3433/full/ncomms3433.html">http://www.nature.com/ncomms/2013/130917/ncomms3433/full/ncomms3433.html</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/7216/free-math-books</guid>
	<pubDate>Thu, 12 Dec 2013 19:38:34 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/7216/free-math-books</link>
	<title><![CDATA[Free math books]]></title>
	<description><![CDATA[<p>Bioinformatics require some match skills, therefore I decided to provide this wonderful math eBooks links to the BOL community.</p>
<p>Please add ur links/bookmarks in comment section.</p><p>Address of the bookmark: <a href="http://physicsdatabase.com/free-math-books/" rel="nofollow">http://physicsdatabase.com/free-math-books/</a></p>]]></description>
	<dc:creator>Manisha Mishra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34443/opera-an-optimal-genome-scaffolding-program</guid>
	<pubDate>Mon, 27 Nov 2017 10:18:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34443/opera-an-optimal-genome-scaffolding-program</link>
	<title><![CDATA[Opera: An optimal genome scaffolding program]]></title>
	<description><![CDATA[<p><span>Opera (Optimal Paired-End Read Assembler) is a sequence assembly program (</span><a href="http://en.wikipedia.org/wiki/Sequence_assembly" target="_blank">http://en.wikipedia.org/wiki/Sequence_assembly&nbsp;<img src="https://a.fsdn.com/con/img/icons/external_asset.png" alt="image" style="border: 0px;"></a><span>). It uses information from paired-end or long reads to optimally order and orient contigs assembled from shotgun-sequencing reads.</span><br><br><span>An updated version called OPERA-LG has been re-engineered with features for the assembly of large and complex genomes.</span><br><br><span>Song Gao, Denis Bertrand, Burton K. H. Chia and Niranjan Nagarajan. OPERA-LG: efficient and exact scaffolding of large, repeat-rich eukaryotic genomes with performance guarantees. Genome Biology, May 2016, doi: 10.1186/s13059-016-0951-y.</span><br><br><span>Song Gao, Wing-Kin Sung, Niranjan Nagarajan. Opera: reconstructing optimal genomic scaffolds with high-throughput paired-end sequences. Journal of Computational Biology, Sept. 2011, doi:10.1089/cmb.2011.0170.</span></p>
<p><span>https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0951-y</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/operasf/" rel="nofollow">https://sourceforge.net/projects/operasf/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/7387/bioinformatics-software-for-biologists-in-the-genomics-era</guid>
	<pubDate>Sun, 22 Dec 2013 17:31:05 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/7387/bioinformatics-software-for-biologists-in-the-genomics-era</link>
	<title><![CDATA[Bioinformatics software for biologists in the genomics era]]></title>
	<description><![CDATA[<p>The genome sequencing revolution is approaching a landmark figure of 1000 completely sequenced genomes. Coupled with fast-declining, per-base sequencing costs, this influx of DNA sequence data has encouraged laboratory scientists to engage large datasets in comparative sequence analyses for making evolutionary, functional and translational inferences. However, the majority of the scientists at the forefront of experimental research are not bioinformaticians, so a gap exists between the user-friendly software needed and the scripting/programming infrastructure often employed for the analysis of large numbers of genes, long genomic segments and groups of sequences. We see an urgent need for the expansion of the fundamental paradigms under which biologist-friendly software tools are designed and developed to fulfill the needs of biologists to analyze large datasets by using sophisticated computational methods. We argue that the design principles need to be sensitive to the reality that comparatively small teams of biologists have historically developed some of the most popular biological software packages in molecular evolutionary analysis. Furthermore, biological intuitiveness and investigator empowerment need to take precedence over the current supposition that biologists should re-tool and become programmers when analyzing genome scale datasets.</p><p>Address of the bookmark: <a href="http://bioinformatics.oxfordjournals.org/content/23/14/1713.full" rel="nofollow">http://bioinformatics.oxfordjournals.org/content/23/14/1713.full</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34488/scripts-for-the-analysis-of-hgt-in-genome-sequence-data</guid>
	<pubDate>Wed, 29 Nov 2017 16:44:10 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34488/scripts-for-the-analysis-of-hgt-in-genome-sequence-data</link>
	<title><![CDATA[Scripts for the analysis of HGT in genome sequence data.]]></title>
	<description><![CDATA[<p><span>Scripts for the analysis of HGT in genome sequence data</span></p><p>Address of the bookmark: <a href="https://github.com/reubwn/hgt" rel="nofollow">https://github.com/reubwn/hgt</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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