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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44707?offset=140</link>
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	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42130/shaman-a-user-friendly-website-for-metataxonomic-analysis-from-raw-reads-to-statistical-analysis</guid>
	<pubDate>Mon, 17 Aug 2020 05:21:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42130/shaman-a-user-friendly-website-for-metataxonomic-analysis-from-raw-reads-to-statistical-analysis</link>
	<title><![CDATA[SHAMAN: a user-friendly website for metataxonomic analysis from raw reads to statistical analysis]]></title>
	<description><![CDATA[<p><span>SHAMAN is a shiny application for differential analysis of metagenomic data (16S, 18S, 23S, 28S, ITS and WGS) including bioinformatics treatment of raw reads for targeted metagenomics, statistical analysis and results visualization with a large variety of plots (barplot, boxplot, heatmap, &hellip;).</span><br><span>The bioinformatics treatment is based on Vsearch [</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/27781170">Rognes 2016</a><span>] which showed to be both accurate and fast [</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/26664811">Wescott 2015</a><span>].The statistical analysis is based on DESeq2 R package [</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/20979621">Anders and Huber 2010</a><span>] which robustly identifies the differential abundant features as suggested in [</span><a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3974642/">McMurdie and Holmes 2014</a><span>] and [</span><a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4727335/">Jonsson2016</a><span>]. SHAMAN robustly identifies the differential abundant genera with the Generalized Linear Model implemented in DESeq2 [</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/25516281">Love 2014</a><span>].</span><br><span>SHAMAN is compatible with standard formats for metagenomic analysis (.csv, .tsv, .biom) and figures can be downloaded in several formats. A presentation about SHAMAN is available&nbsp;</span><a href="https://github.com/aghozlane/shaman/blob/master/www/shaman_presentation.pdf">here</a><span>&nbsp;and a poster&nbsp;</span><a href="https://github.com/aghozlane/shaman/blob/master/www/shaman_poster.pdf">here</a><span>.&nbsp;</span></p>
<p><span>More at&nbsp;<a href="https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-03666-4">https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-03666-4</a></span></p><p>Address of the bookmark: <a href="https://github.com/aghozlane/shaman" rel="nofollow">https://github.com/aghozlane/shaman</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43447/rna-seq-workflow-gene-level-exploratory-analysis-and-differential-expression</guid>
	<pubDate>Sat, 09 Oct 2021 07:59:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43447/rna-seq-workflow-gene-level-exploratory-analysis-and-differential-expression</link>
	<title><![CDATA[RNA-seq workflow: gene-level exploratory analysis and differential expression]]></title>
	<description><![CDATA[<p><span>Here we walk through an end-to-end gene-level RNA-seq differential expression workflow using Bioconductor packages. We will start from the FASTQ files, show how these were quantified to the reference transcripts, and prepare gene-level count datasets for downstream analysis. We will perform exploratory data analysis (EDA) for quality assessment and to explore the relationship between samples, perform differential gene expression analysis, and visually explore the results.</span></p><p>Address of the bookmark: <a href="http://master.bioconductor.org/packages/release/workflows/vignettes/rnaseqGene/inst/doc/rnaseqGene.html" rel="nofollow">http://master.bioconductor.org/packages/release/workflows/vignettes/rnaseqGene/inst/doc/rnaseqGene.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44716/exploring-rna-sequence-analysis-tools-for-every-bioinformatician</guid>
	<pubDate>Fri, 13 Dec 2024 04:03:04 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44716/exploring-rna-sequence-analysis-tools-for-every-bioinformatician</link>
	<title><![CDATA[Exploring RNA Sequence Analysis: Tools for Every Bioinformatician]]></title>
	<description><![CDATA[<p>RNA sequence analysis has become an essential part of modern biological research. From RNA-seq pipelines to specialized tools for specific RNA types, here's a comprehensive guide to tools you can use to make sense of RNA data.</p><h4><strong>1. RNA-Seq Analysis Pipelines</strong></h4><p>RNA-seq is one of the most popular techniques for studying RNA. These tools streamline processing raw sequence data:</p><ul>
<li><strong>FASTQC</strong>: For quality control of raw RNA-seq reads.</li>
<li><strong>Trimmomatic</strong>: For trimming and filtering RNA-seq reads.</li>
<li><strong>HISAT2/STAR</strong>: High-performance aligners for RNA-seq reads.</li>
<li><strong>FeatureCounts</strong>: For quantifying gene expression.</li>
<li><strong>DESeq2/EdgeR</strong>: For differential expression analysis.</li>
</ul><h4><strong>2. Transcriptome Assembly and Annotation</strong></h4><p>For analyzing transcriptomes from non-model organisms or assembling novel transcripts:</p><ul>
<li><strong>Trinity</strong>: For de novo transcriptome assembly.</li>
<li><strong>StringTie</strong>: For transcript assembly and quantification from RNA-seq alignments.</li>
<li><strong>TransDecoder</strong>: To predict coding regions within assembled transcripts.</li>
<li><strong>TAU</strong>: Tools for annotating non-coding and coding RNAs.</li>
</ul><h4><strong>3. Exploring Non-Coding RNA (ncRNA)</strong></h4><p>Non-coding RNAs play critical regulatory roles. Dedicated tools for studying them include:</p><ul>
<li><strong>Infernal</strong>: For identifying ncRNA sequences based on covariance models.</li>
<li><strong>Rfam</strong>: Database and tools for ncRNA families.</li>
<li><strong>miRDeep</strong>: For identifying microRNAs in RNA-seq datasets.</li>
</ul><h4><strong>4. RNA Structure and Motif Analysis</strong></h4><p>Structural biology of RNA helps in understanding its function:</p><ul>
<li><strong>RNAfold (ViennaRNA)</strong>: Predicts secondary structures from RNA sequences.</li>
<li><strong>RNAstructure</strong>: Tools for RNA secondary structure prediction and analysis.</li>
<li><strong>MEME Suite</strong>: For identifying motifs in RNA sequences.</li>
<li><strong>IntaRNA</strong>: For RNA-RNA interaction prediction.</li>
</ul><h4><strong>5. RNA Editing and Modifications</strong></h4><p>Epitranscriptomics is a growing field focusing on RNA modifications:</p><ul>
<li><strong>REDItools</strong>: For RNA editing analysis.</li>
<li><strong>m6Aboost</strong>: For identifying m6A modifications in RNA.</li>
</ul><h4><strong>6. Long-Read RNA Sequencing Analysis</strong></h4><p>Long-read technologies like Nanopore and PacBio are transforming RNA research:</p><ul>
<li><strong>FLAIR</strong>: For isoform-level analysis of long-read RNA-seq data.</li>
<li><strong>NanoMod</strong>: For detecting modifications in RNA from Nanopore sequencing.</li>
</ul><h4><strong>7. RNA-Protein Interactions</strong></h4><p>To study RNA-protein interactions and complexes:</p><ul>
<li><strong>RBPmap</strong>: For identifying RNA-binding protein motifs.</li>
<li><strong>PARalyzer</strong>: For analyzing PAR-CLIP data.</li>
</ul><h4><strong>8. Functional Enrichment Analysis</strong></h4><p>Understanding biological functions and pathways from RNA-seq data:</p><ul>
<li><strong>getENRICH</strong>: A tool designed for pathway enrichment analysis of non-model organisms (hypergeometric P-value calculation with FDR correction).</li>
<li><strong>ClusterProfiler</strong>: For GO and KEGG pathway enrichment analysis.</li>
</ul><h4><strong>9. Visualization and Data Sharing</strong></h4><p>Presenting and sharing RNA sequence analysis results effectively:</p><ul>
<li><strong>IGV</strong>: Genome browser for visualizing RNA-seq alignments.</li>
<li><strong>Circos</strong>: Circular visualization of RNA-seq data.</li>
<li><strong>DashBio</strong>: A Python library for creating bioinformatics visualizations.</li>
</ul><h4><strong>Conclusion</strong></h4><p>The bioinformatics landscape for RNA sequence analysis is vast, with tools catering to specific needs. Whether you&rsquo;re studying coding RNAs, non-coding RNAs, or exploring RNA-protein interactions, the right tools can transform your data into biological insights.</p>]]></description>
	<dc:creator>Neel</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/2337/clinical-genomics-informatics-europe-at-lisbon-portugal</guid>
  <pubDate>Wed, 14 Aug 2013 09:58:34 -0500</pubDate>
  <link></link>
  <title><![CDATA[Clinical Genomics &amp; Informatics Europe at Lisbon, Portugal]]></title>
  <description><![CDATA[
<p>Bio-IT World and Cambridge Healthtech Institute's fifth international Clinical Genomics &amp; Informatics Europe conference will feature four main tracks on Clinical Exome Sequencing, High Scale Computing, Genome Informatics, and RNA-Seq and Transcriptome Analysis, as well as two pre-conference symposia on Clinical Epigenetics and Quantitative Digital Detection Technologies. The conference will tackle the huge amounts of sequencing data produced by new technologies that have introduced significant challenges for bioinformatics, both in terms of the analysis and interpretation of data and clinical implementation of novel variants. Members of the international community will come together to look at the science and informatics required to utilize next generation sequencing for the molecular diagnosis of complex diseases.</p>

<p>Dated : 04 Dec 2013 - 06 Dec 2013</p>

<p>More at : http://www.clinicalgenomicsinformatics.com/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/17946/7th-international-conference-on-bioinformatics-and-computational-biology-bicob</guid>
	<pubDate>Mon, 06 Oct 2014 16:19:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/17946/7th-international-conference-on-bioinformatics-and-computational-biology-bicob</link>
	<title><![CDATA[7th International Conference on Bioinformatics and Computational Biology (BICoB)]]></title>
	<description><![CDATA[<p><span>In recent years, computational biology and medical informatics have seen significant advances driven by computational techniques in bioinformatics making bioinformatics and computational biology among the most vibrant research areas. The 7th international conference on Bioinformatics and Computational Biology (BICoB-2015) provides an excellent venue for researchers and practitioners in the fields of bioinformatics and computational biology to present and publish their research results and techniques. The BICoB conference seeks original and high quality papers in the fields of bioinformatics, computational biology, systems biology, medical informatics and the related disciplines. </span><span>We also encourage work in progress and research results in the emerging and evolutionary computational areas. Computational techniques have already enabled unprecedented advances in modern biology and medicine. Work in the computational methods related to, or with application in, bioinformatics is also encouraged including: data mining, text mining, machine learning, modeling and simulation, pattern recognition, data visualization, biostatistics, .etc. The topics of interest include (and are not limited to):&nbsp;</span><br><strong><span>Genome analysis:</span></strong><span>&nbsp;Genome assembly, genome annotation, gene finding, alternative splicing, EST analysis and comparative genomics.&nbsp;</span><br><strong><span>Sequence analysis:</span></strong><span>&nbsp;Multiple sequence alignment, sequence search and clustering, function prediction, motif discovery, functional site recognition in protein, RNA and DNA sequences.&nbsp;</span><br><strong><span>Phylogenetics:</span></strong><span>&nbsp;Phylogeny estimation, models of evolution, comparative biological methods, population genetics.&nbsp;</span><br><strong><span>Structural Bioinformatics:</span></strong><span>&nbsp;Structure matching, prediction, analysis and comparison; methods and tools for docking; protein design&nbsp;</span><br><strong><span>Analysis of high-throughput biological data:</span></strong><span>&nbsp;Microarrays (nucleic acid, protein, array CGH, genome tiling, and other arrays), EST, SAGE, MPSS, proteomics, mass spectrometry.&nbsp;</span><br><strong><span>Genetics and population analysis:</span></strong><span>&nbsp;Linkage analysis, association analysis, population simulation, haplotyping, marker discovery, genotype calling.&nbsp;</span><br><strong><span>Systems biology:</span></strong><span>&nbsp;Systems approaches to molecular biology, multiscale modeling, pathways,gene networks.&nbsp;</span><br><strong><span>Computational Proteomics:&nbsp;</span></strong><span>Filtering and indexing sequence databases, Peptide quantification and identification, Genome annotations via mass spectrometry, Identification of post-translational modifications, Structural genomics via mass spectrometry, Protein-protein interactions, Computational approaches to analysis of large scale Mass spectrometry data, Exploration and visualization of proteomic data, Data models and integration for proteomics and genomics, Querying and retrieval of proteomics and genomics data etc.</span></p>
<p><span><span>Authors of selected high quality papers in BICoB-2015 will be invited to submit extended version of their papers for possible publication in bioinformatics journals (</span><a href="http://www.worldscinet.com/jbcb/" target="_blank"><strong>Journal of Bioinformatics and Computational Biology JBCB).</strong></a></span></p>
<p><span><strong>Deadlines</strong>:</span></p>
<p><span></span></p>
<p>Paper Submission Deadline October 24, 2014<br>Notification of Acceptance December 15, 2014<br>Camera-Ready Manuscript January 16, 2015</p>
<p><span></span></p><p>Address of the bookmark: <a href="http://www.cs.umb.edu/bicob/" rel="nofollow">http://www.cs.umb.edu/bicob/</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/2423/cancers-origins-revealed</guid>
	<pubDate>Thu, 15 Aug 2013 13:06:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/2423/cancers-origins-revealed</link>
	<title><![CDATA[Cancer's origins revealed]]></title>
	<description><![CDATA[<p>Researchers have provided the first comprehensive compendium of mutational processes that drive tumour development. Together, these mutational processes explain most mutations found in 30 of the most common cancer types. This new understanding of cancer development could help to treat and prevent a wide-range of cancers.<br /><br />More at &gt;&gt; http://www.sanger.ac.uk/about/press/2013/130814.html</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22179/marie-curie-phd-position-available-immediately</guid>
  <pubDate>Fri, 24 Apr 2015 09:23:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[Marie Curie PhD position available immediately]]></title>
  <description><![CDATA[
<p>Sub-project 10: Development of bioinformatic tools for the analysis of MACE data<br />Host Organizations GenXPRO (Germany)<br />Objectives : The ESR will be in charge of standardising pipelines that will be used for RNA-seq and MACE analyses by all the participants. He will be involved in performing next generation sequencing to characterise environmental adaptation. A single pipeline to analyse listerial transcriptomic and proteomic data will be developed and implemented by each partner for the sake of uniformity of all the data produced within List_MAPS. The ESR will be involved in the interpretation of transcriptomic and proteomic data for which pathway analyses and good data visualization will be required. A cytoscape app will be developed as visualization tool.<br />Expected Results: MACE analysis pipeline. Database. Transcriptome comparisons in selected habitats. Data visualization tool.<br />Duration (months) 24<br />Contact Dr. Bjorn ROTTER: rotter@genxpro.de </p>

<p>11. Development of innovative tools for rapid phenotypic characterisation of intraspecific diversity of Listeria monocytogenes (Joint supervision PhD)<br />Host Organizations BioFilm Control (France) and GenXPRO (Germany)<br />Objectives<br /> 1. The ESR will develop an assay to test biofilm phenotype in a large array of food processing-related environmental conditions (salt, acides, disinfectants, preservatives) in BFC facilities. He will be in charge of the development and validation of an in silico virulence assay. This assay will target specific mRNAs in order to estimate the virulence potential of strains of L. monocytogenes. Transcript targets will be selected and tested by qPCR in GXP premises. In the process of validation, virulence results of several strains collected in a humanised mouse model will be compared with the in silico analysis. Once these innovative tools will be validated, intraspecific phenotypic diversity (biofilm and virulence) will be assessed on a collection of environmental and clinical isolates of L. monocytogenes. Genotypic diversity will be assessed under the supervision of GPX.<br />Expected Results : Adaptation of the BioFilm Ring test R to test food processing environmental conditions. Development of an innovative in silico virulence assay surrogate to animal models. Diversity results will inform stakeholders on the level of health hazard according to the strain. This in turn will help secure food safety all along the shelf life of foodstuff.<br />Duration (months) 36<br />Contact : Dr. Thierry BERNARDI: thbe@biofilmcontrol.com <br />Dr. Bjorn ROTTER: rotter@genxpro.de<br />ELIGIBLE CRITERIA of Marie Sklokowska Curie actions:<br />Researchers may be of any nationality<br />Candidates shall at the time of recruitment by the host organization, be in the first four years (full-time equivalent research experience) of their research careers. Full-time equivalent research experience is measured from the date when a researcher obtained the degree which would formally entitle him or her to embark on a doctorate, either in the co</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/2464/computer-theory-genetics-george-chao-at-tedxumnsalon</guid>
	<pubDate>Thu, 15 Aug 2013 22:08:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/2464/computer-theory-genetics-george-chao-at-tedxumnsalon</link>
	<title><![CDATA[Computer Theory & Genetics: George Chao at TEDxUMNSalon]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/7_GL17oiak8" frameborder="0" allowfullscreen></iframe>George Chao is an undergraduate senior studying Genetics and Computer Science at the University of Minnesota. Having started genetics research as soon as he entered the university, he has worked in labs spanning multiple disciplines as well as in Japan. Some of these researches include developmental genetics in Drosophila, computational techniques for analyzing protein interactions, and helping with the development of algorithms to analyze motion capture data of patients with neck pain. During this time, George steadily developed a fascination with the field of bioinformatics, the study of using computational techniques to learn from genetic data. He would like to go into a career of research into the application of bioinformatics in various fields.

----

The individuals involved with TEDxUMN have a passion for bringing together the great thinkers at the University of Minnesota and giving them the opportunity to share their ideas worth spreading and to discuss our shared future. We provide these great people the opportunity to share these ideas on a global stage and with an incredibly diverse audience. We believe in the power of ideas to change attitudes, lives and ultimately the world.

Check out TEDxUMN at http://www.TEDxUMN.com/

In the spirit of ideas worth spreading, TEDx is a program of local, self-organized events that bring people together to share a TED-like experience. At a TEDx event, TEDTalks video and live speakers combine to spark deep discussion and connection in a small group. These local, self-organized events are branded TEDx, where x = independently organized TED event. The TED Conference provides general guidance for the TEDx program, but individual TEDx events are self-organized.* (*Subject to certain rules and regulations)]]></description>
	
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/23122/candidates-required-in-bioinformatics-and-genomics-uk-only</guid>
  <pubDate>Fri, 03 Jul 2015 08:22:41 -0500</pubDate>
  <link></link>
  <title><![CDATA[Candidates required in Bioinformatics and Genomics UK ONLY]]></title>
  <description><![CDATA[
<p>I have various permanent positions available based in London, Manchester, Herftfordshire, Oxford and Belfast, as well as other areas throughout the UK.</p>

<p>If you are looking for a new opportunity and have skills within any sector of Bioinformatics with an IT skill then I would love to hear from you.  I have various exciting opportunities from programmers to researchers to scientists.</p>

<p>Call me now on 01772 278050 or email me your cv and requirements and I will call you back dareen.evans@itworkshealth.co.uk</p>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/2680/4-positions-in-high-throughput-computational-metagenomics-and-systems-biology-of-natural-products</guid>
  <pubDate>Tue, 20 Aug 2013 08:42:29 -0500</pubDate>
  <link></link>
  <title><![CDATA[4 positions in high throughput computational metagenomics and systems biology of natural products]]></title>
  <description><![CDATA[
<p>The Research and Innovation Centre at the Fondazione Edmund Mach (CRI-FEM) is a major international research institution with strong and expanding research interests in Fruit Genomics, Quality Health and Nutrition of Agricultural Products, Agro-ecosystems Sustainability, Biodiversity and Molecular Ecology.</p>

<p>CRI-FEM hosts GMPF, an International PhD Program in Genomics and Molecular Physiology of Fruit Crops and Fox-Lab, an international initiative in forest and wood research.<br />4 positions in high throughput computational metagenomics and systems biology of natural products - deadline September 30th, 2013</p>

<p>To support interdisciplinary research, CRI-FEM has established the Computational Biology Centre (CBC).</p>

<p>The mission of CBC is to develop systems-level integrative approaches connecting genotype to phenotype with a special focus on genome-wide analyses and next generation sequencing technologies. </p>

<p>CRI-FEM is seeking to attract 4 high calibre scientists in the areas of high throughput computational metagenomics and systems biology of natural products.</p>

<p>Here below the list of the 4 positions:</p>

<p>http://www.fmach.it/eng/Servizi-Generali/Lavora-con-noi/Annunci-lavoro-e-borse-di-studio/Details-of-the-5-positions-in-high-throughput-computational-metagenomics-and-systems-biology-of-natural-products-deadline-September-30th-2013/Post-doc-in-Metagenomics-screening-and-characterization-of-bioactive-microbial-compounds-130_CRI_MSC</p>

<p>http://www.fmach.it/eng/Servizi-Generali/Lavora-con-noi/Annunci-lavoro-e-borse-di-studio/Details-of-the-5-positions-in-high-throughput-computational-metagenomics-and-systems-biology-of-natural-products-deadline-September-30th-2013/Post-doc-in-Modeling-transcriptional-control-programs-at-a-genome-wide-scale-131_CRI_TCP</p>

<p>http://www.fmach.it/eng/Servizi-Generali/Lavora-con-noi/Annunci-lavoro-e-borse-di-studio/Details-of-the-5-positions-in-high-throughput-computational-metagenomics-and-systems-biology-of-natural-products-deadline-September-30th-2013/Technologist-in-Purification-of-plant-bioactive-molecules-from-complex-matrixes-132_CRI_PBM</p>

<p>http://www.fmach.it/eng/Servizi-Generali/Lavora-con-noi/Annunci-lavoro-e-borse-di-studio/Details-of-the-5-positions-in-high-throughput-computational-metagenomics-and-systems-biology-of-natural-products-deadline-September-30th-2013/Researcher-in-Methods-for-algorithmic-and-integrative-genomics-for-metagenomics-134_CRI_AIG</p>

<p>For more information on the CBC or informal inquiries on the advertised positions please contact Dr Duccio Cavalieri (e-mail duccio.cavalieri@fmach.it).</p>
]]></description>
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