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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37409?offset=320</link>
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	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44705/pirna-and-bioinformatics-decoding-the-guardians-of-the-genome</guid>
	<pubDate>Sat, 07 Dec 2024 02:15:11 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44705/pirna-and-bioinformatics-decoding-the-guardians-of-the-genome</link>
	<title><![CDATA[piRNA and Bioinformatics: Decoding the Guardians of the Genome]]></title>
	<description><![CDATA[<p>In the symphony of small RNAs, PIWI-interacting RNAs (piRNAs) stand out as the protectors of genomic integrity. These small, non-coding RNAs play critical roles in silencing transposable elements, regulating gene expression, and maintaining germline stability. The rise of bioinformatics has revolutionized our understanding of piRNAs, enabling researchers to decipher their biogenesis, functions, and evolutionary significance.</p><h3>What Are piRNAs?</h3><p>piRNAs are the largest class of small non-coding RNAs, typically 24&ndash;32 nucleotides in length. Unlike microRNAs (miRNAs) and small interfering RNAs (siRNAs), piRNAs do not rely on Dicer enzymes for maturation. Instead, they are processed from long single-stranded precursors and associate with PIWI proteins, a subclass of the Argonaute protein family.</p><p>The primary functions of piRNAs include:</p><ol>
<li><strong>Silencing Transposable Elements</strong>: By targeting transposons, piRNAs prevent genomic instability, particularly in germline cells.</li>
<li><strong>Regulating Gene Expression</strong>: piRNAs modulate gene expression at transcriptional and post-transcriptional levels.</li>
<li><strong>Epigenetic Modulation</strong>: They guide epigenetic modifications, such as DNA methylation, to specific genomic loci.</li>
</ol><h3>Challenges in piRNA Research</h3><p>Studying piRNAs is fraught with challenges, including:</p><ul>
<li><strong>Short Length</strong>: Their small size complicates sequencing and alignment.</li>
<li><strong>Lack of Sequence Conservation</strong>: Unlike miRNAs, piRNAs exhibit limited sequence conservation across species.</li>
<li><strong>Complex Biogenesis</strong>: The intricate pathways of piRNA generation require sophisticated computational tools to unravel.</li>
</ul><h3>Bioinformatics: Illuminating the World of piRNAs</h3><p>Bioinformatics has emerged as an indispensable tool for studying piRNAs, facilitating their discovery, annotation, and functional analysis. Here's how bioinformatics is transforming piRNA research:</p><h4>1. <strong>Identification and Annotation</strong></h4><p>The discovery of piRNAs relies on next-generation sequencing (NGS) data. Bioinformatics tools such as <em>piRNApredictor</em> and <em>Piano</em> identify piRNA clusters and predict potential targets. Databases like piRBase and piRNAdb curate information about known piRNAs, their sequences, and associated proteins.</p><h4>2. <strong>Mapping and Alignment</strong></h4><p>piRNAs often originate from repetitive regions, making their alignment challenging. Tools like Bowtie and STAR handle the unique mapping requirements of piRNAs, enabling accurate identification of piRNA clusters in genomes.</p><h4>3. <strong>Functional Analysis</strong></h4><p>Bioinformatics approaches predict piRNA functions by analyzing their interactions with transposons, genes, and epigenetic marks. Algorithms such as TargetFinder and RIblast explore piRNA-mRNA interactions, shedding light on regulatory networks.</p><h4>4. <strong>Evolutionary Studies</strong></h4><p>piRNAs are evolutionarily diverse, reflecting their roles in species-specific genomic defense. Comparative genomics tools help trace the evolution of piRNA clusters and their associated PIWI proteins across species.</p><h4>5. <strong>Epigenomic Insights</strong></h4><p>piRNAs are key players in epigenetic regulation. Bioinformatics pipelines integrate piRNA data with chromatin immunoprecipitation sequencing (ChIP-seq) and DNA methylation data to uncover their role in shaping the epigenome.</p><h3>Case Study: piRNAs in Germline Integrity</h3><p>One of the hallmark functions of piRNAs is the suppression of transposable elements in the germline. For example, in <em>Drosophila melanogaster</em>, piRNAs target retrotransposons like <em>gypsy</em> and <em>copia</em>. Bioinformatics analyses revealed that these piRNAs guide PIWI proteins to transposon-derived RNA, ensuring genome stability during gametogenesis.</p><h3>Clinical Relevance of piRNAs</h3><p>Recent studies suggest that piRNAs may serve as biomarkers for diseases such as cancer, infertility, and neurodegenerative disorders. For instance:</p><ul>
<li><strong>Cancer</strong>: Dysregulated piRNA expression has been linked to tumorigenesis, making them potential targets for cancer therapies.</li>
<li><strong>Infertility</strong>: Aberrant piRNA pathways are implicated in male infertility due to their role in spermatogenesis.</li>
<li><strong>Neurodegeneration</strong>: piRNAs may regulate neuronal gene expression, highlighting their potential in neurological research.</li>
</ul><h3>Future Directions</h3><p>The integration of bioinformatics with emerging technologies offers exciting opportunities for piRNA research:</p><ul>
<li><strong>Single-Cell Sequencing</strong>: Unveiling cell-specific piRNA expression and function.</li>
<li><strong>Machine Learning</strong>: Predicting piRNA functions and targets with greater accuracy.</li>
<li><strong>CRISPR-Based Tools</strong>: Editing piRNA clusters to explore their roles in vivo.</li>
</ul><h3>Conclusion</h3><p>piRNAs are the unsung guardians of the genome, safeguarding genetic material from transposable elements and contributing to gene regulation and epigenetic programming. Bioinformatics has opened the floodgates of discovery, unraveling the complexities of piRNAs and their myriad roles in biology and disease.</p><p>As we continue to decode the piRNA landscape, these small RNAs promise to unveil big secrets about genome stability, evolution, and human health, cementing their place as a fascinating frontier in molecular biology.</p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44775/genomic-architecture-surrounding-the-fusion-site-of-human-chromosome-2</guid>
	<pubDate>Tue, 04 Mar 2025 12:26:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44775/genomic-architecture-surrounding-the-fusion-site-of-human-chromosome-2</link>
	<title><![CDATA[Genomic architecture surrounding the fusion site of human chromosome 2]]></title>
	<description><![CDATA[<p>The article <strong>"Genomic Structure and Evolution of the Ancestral Chromosome Fusion Site in 2q13&ndash;2q14.1 and Paralogous Regions on Other Human Chromosomes (https://pmc.ncbi.nlm.nih.gov/articles/PMC187548/)"</strong> explores the genomic architecture surrounding the fusion site of human chromosome 2. This fusion event is a key evolutionary marker distinguishing humans from other great apes, as humans have 46 chromosomes while chimpanzees, gorillas, and orangutans possess 48. The fusion occurred through an end-to-end joining of two ancestral chromosomes, which remain separate in nonhuman primates.</p><h3><strong>Key Findings:</strong></h3><ol>
<li>
<p><strong>Chromosomal Fusion and Its Molecular Signature:</strong></p>
<ul>
<li>The fusion site is located at <strong>2q13&ndash;2q14.1</strong> and is characterized by <strong>degenerate telomeric sequences</strong> appearing interstitially, indicating the historical head-to-head joining of ancestral chromosomes.</li>
<li>Despite being a signature of a past fusion event, these telomeric repeats are no longer functional and have undergone sequence degradation over time.</li>
</ul>
</li>
<li>
<p><strong>Extensive Duplications in the Surrounding Genomic Region:</strong></p>
<ul>
<li>The study identifies <strong>large-scale segmental duplications</strong> flanking the fusion site, with several of these regions duplicated and scattered across multiple chromosomes.</li>
<li>These duplications are predominantly located in <strong>subtelomeric and pericentromeric regions</strong>, suggesting their role in genomic instability and chromosomal evolution.</li>
</ul>
</li>
<li>
<p><strong>Paralogous Regions and Their Evolutionary Relationships:</strong></p>
<ul>
<li>A <strong>168-kilobase (kb) segment</strong> near the fusion site has <strong>98%&ndash;99% sequence identity</strong> with three regions on <strong>chromosome 9 (9pter, 9p11.2, and 9q13)</strong>.</li>
<li>Another <strong>67-kb region distal to the fusion site</strong> shows a high degree of homology to sequences in <strong>chromosome 22qter</strong>.</li>
<li>Additionally, a <strong>100-kb segment</strong> exhibits <strong>96% sequence identity</strong> with a region in <strong>chromosome 2q11.2</strong>.</li>
</ul>
</li>
<li>
<p><strong>Comparative Genomics and Evolutionary Implications:</strong></p>
<ul>
<li>By comparing the duplicated sequences and their arrangement in primates, the researchers traced the order of duplication events leading to their present distribution.</li>
<li>The presence of specific repetitive elements within these duplicated segments serves as <strong>evolutionary markers</strong> that help infer their historical rearrangements.</li>
<li>Some of these <strong>duplicated regions are associated with chromosomal inversion breakpoints</strong>, potentially contributing to evolutionary changes in primates.</li>
<li>Recurrent <strong>structural rearrangements</strong> in these regions have been linked to human chromosomal disorders.</li>
</ul>
</li>
</ol><h3><strong>Conclusions and Implications:</strong></h3><ul>
<li>The findings provide valuable insights into <strong>the structural evolution of human chromosome 2</strong>, which played a crucial role in human speciation.</li>
<li>Understanding these <strong>segmental duplications</strong> and their evolutionary trajectories sheds light on <strong>genomic instability</strong>, which may contribute to <strong>human genetic diseases</strong>.</li>
<li>The study highlights how large-scale chromosomal rearrangements, such as fusion and duplication, have influenced the <strong>evolutionary divergence of humans</strong> from other primates.</li>
</ul><p>This research advances our understanding of <strong>human genome evolution</strong> and offers a foundation for studying the effects of <strong>structural variants in genetic disorders</strong>.</p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36755/minialign-fast-and-accurate-alignment-tool-for-pacbio-and-nanopore-long-reads</guid>
	<pubDate>Thu, 24 May 2018 08:33:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36755/minialign-fast-and-accurate-alignment-tool-for-pacbio-and-nanopore-long-reads</link>
	<title><![CDATA[minialign: fast and accurate alignment tool for PacBio and Nanopore long reads]]></title>
	<description><![CDATA[Minialign is a little bit fast and moderately accurate nucleotide sequence alignment tool designed for PacBio and Nanopore long reads. It is built on three key algorithms, minimizer-based index of the minimap overlapper, array-based seed chaining, and SIMD-parallel Smith-Waterman-Gotoh extension.<p>Address of the bookmark: <a href="https://github.com/ocxtal/minialign" rel="nofollow">https://github.com/ocxtal/minialign</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/34702/run-miniasm-assembler-on-nanopore-reads</guid>
	<pubDate>Mon, 18 Dec 2017 04:07:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/34702/run-miniasm-assembler-on-nanopore-reads</link>
	<title><![CDATA[Run miniasm assembler on nanopore reads !]]></title>
	<description><![CDATA[<p>Miniasm is a very fast OLC-based&nbsp;<em>de novo</em>&nbsp;assembler for noisy long reads. It takes all-vs-all read self-mappings (typically by&nbsp;<a href="https://github.com/lh3/minimap">minimap</a>) as input and outputs an assembly graph in the&nbsp;<a href="https://github.com/pmelsted/GFA-spec/blob/master/GFA-spec.md">GFA</a>&nbsp;format. Different from mainstream assemblers, miniasm does not have a consensus step. It simply concatenates pieces of read sequences to generate the final&nbsp;<a href="http://wgs-assembler.sourceforge.net/wiki/index.php/Celera_Assembler_Terminology">unitig</a>&nbsp;sequences. Thus the per-base error rate is similar to the raw input reads.</p><p>Find the detail of the reads repeats:</p><blockquote><p>fq2fa ONT_A.fastq ONT_A.fasta&nbsp;<br /><br />minimap2 -xava-ont ONT_A.fasta ONT_A.fasta -t10 -X &gt; AONT.paf&nbsp;<br /><br />awk '{if($1==$6){print}}' AONT.paf &gt; AONTself.paf&nbsp;<br /><br />awk '$5=="-"' AONTself.paf | awk '{print $1}'| sort|uniq &gt; invertedrepeat.list</p></blockquote><p>Generated a few palindrome and repeats plots (highlighting only repeats largest than 10, 20 and 30 kb)</p><blockquote><p>minidot -f 5 -m 30000 AONTself.paf &gt; AONTself30000.eps&nbsp;<br />sed 's/_template_pass_FAH31515//' AONTself30000.eps &gt; AONTself30000final.eps&nbsp;<br /><br />minidot -f 5 -m 20000 AONTself.paf &gt; AONTself20000.eps&nbsp;<br />sed 's/_template_pass_FAH31515//' AONTself20000.eps &gt; AONTself20000final.eps&nbsp;<br /><br />minidot -f 5 -m 10000 AONTself.paf &gt; AONTself10000.eps&nbsp;<br />sed 's/_template_pass_FAH31515//' AONTself10000.eps &gt; AONTself10000final.eps&nbsp;</p></blockquote><p>Assemble with miniasm:</p><blockquote><p>miniasm -f ONT_A.fasta AONT.paf &gt; AONT.gfa&nbsp;</p><p>grep '^S' AONT.gfa |awk '{print "&gt;"$2"\n"$3}' &gt; AONT_miniasm.fasta&nbsp;<br /><br />minimap2 -xasm10 AONT_miniasm.fasta AONT_miniasm.fasta -t1 -X &gt; AONT_miniasm.paf&nbsp;<br /><br />awk '{if($1==$6){print}}' AONT_miniasm.paf &gt; AONT_miniasm_self.paf&nbsp;<br /><br />minidot -f 5 -m 10000 AONT_miniasm_self.paf &gt; AONT_miniasm_self10000.eps&nbsp;</p></blockquote><p>Njoy the assembly !</p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/843/structural-polymorphism-analysis-from-ngs-data</guid>
  <pubDate>Sat, 13 Jul 2013 17:12:47 -0500</pubDate>
  <link></link>
  <title><![CDATA[Structural polymorphism analysis from NGS data]]></title>
  <description><![CDATA[
<p>The LabEx BASC (Biodiversity, Agroecosystems, Society, Climate), a network of 13 laboratories of the Paris-Saclay Scientific Cluster, is seeking a bioinformatician to analyze Next Generation Sequencing (NGS) data analysis. In the context of a flagship project aiming at understanding and improving the adaptive capacity of agroecosystems it will be critical to establish a link between sequence variation, functional variation, gene/protein expression and phenotypic adaptation.</p>

<p>The successful candidate will be in charge of the detection of polymorphisms including structural variants, of the comparison of multiple and diverse genomes of a same species and of the construction of pan- and core-genomes. These challenging tasks will require bioinformatics developments and implementation of methods for accommodating the high level of repetitiveness of complex genomes. The tools will be integrated into pipelines and made available to end-users through the Galaxy platform. The bioinformatician will therefore also have to provide researchers with advices on their experimental designs in order to ensure compliance of produced datasets with pipelines requirements. He/she will be hosted by a bioinformatics/informatics team (7 people) (http://moulon.inra.fr/index.php/fr/equipestransversales/atelier-de-bioinformatique) which has computational facilities and expertise in NGS data analysis, and will benefit as well from national and international collaborative networks (Aplibio http://www.renabi.fr/platforms/aplibio/, Transplant http://transplantdb.eu, AMAIZING http://www.amaizing.fr/).</p>

<p>The position requires a doctoral degree (PhD) in bioinformatics with strong expertise in script writing (Python/Perl) and pipeline development. </p>

<p>Applicants should send a CV and the names of 2 referees willing to provide a letter of recommendation to joets@moulon.inra.fr.</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/2054/postdoc-positions-mammalian-transcriptome-evolution-at-sib</guid>
  <pubDate>Mon, 12 Aug 2013 19:58:33 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoc Positions - Mammalian Transcriptome Evolution at SIB]]></title>
  <description><![CDATA[
<p>BIOINFORMATICS POSTDOC IN FUNCTIONAL EVOLUTIONARY GENOMICS</p>

<p>Center for Integrative Genomics, University of Lausanne, Switzerland</p>

<p>Two postdoctoral positions (2 years with possible extensions up to 5 years) are available immediately in the evolutionary genomics group of Henrik Kaessmann.</p>

<p>We are seeking highly qualified and enthusiastic applicants with strong skills in computational biology/bioinformatics, preferably also with experience in data mining and comparative or evolutionary genome analysis.</p>

<p>We have been interested in a range of topics related to the functional evolution of genomes from primates (e.g., the emergence of new genes and their functions) and other mammals (e.g., the origin and evolution of mammalian sex chromosomes). In the framework of a recently launched series of projects, a large amount of transcriptome and genome (e.g., epigenome) data are being produced by the wet lab unit of the group using next generation sequencing technologies for a unique collection of tissues from representative mammals and outgroup species (e.g., birds). Topics of current projects based on these data include the origins and/or evolution of protein-coding genes, alternative splicing, microRNAs, long noncoding RNAs, and dosage compensation.</p>

<p>The postdoctoral fellow will perform integrated evolutionary/bioinformatics analyses based on data produced in the lab and available genomic data. The specific project will be developed together with the candidate.</p>

<p>The language of the institute is English, and its members form an international group that is rapidly expanding. The institute is located in Lausanne, a beautiful city at Lake Geneva.</p>

<p>For more information on the group and our institute more generally, please refer to our website: http://www.unil.ch/cig/page7858_en.html</p>

<p>Please submit a CV, statement of research interest, and names of three references to: Henrik Kaessmann (Henrik.Kaessmann@unil.ch).</p>

<p>Webpage : http://www.unil.ch/cig/page7858.html</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/6961/research-assistant-national-bureau-of-animal-genetic-resources</guid>
  <pubDate>Tue, 03 Dec 2013 06:17:34 -0600</pubDate>
  <link></link>
  <title><![CDATA[Research Assistant @ NATIONAL BUREAU OF ANIMAL GENETIC RESOURCES]]></title>
  <description><![CDATA[
<p>NATIONAL BUREAU OF ANIMAL GENETIC RESOURCES<br />Near Basant Vihar G.T. Road Bypass<br />P.O. Box No.129, Karnal-132001 (Haryana)</p>

<p>WALK-IN-INTERVIEW</p>

<p>A walk-in-Interview is proposed to be held at National Bureau of Animal Genetic Resources, Karnal (Haryana)-132001 at 11:30 AM on 18.12.2013 to select One RA and One SRF as per details given below:</p>

<p>1. One post of Research Associate under DBT sponsored Support under BIPP for the “SanGenix: A comprehensive Next Generation Sequence (NGS) data analysis solution” as Grants in AID. Thepost duration is Upto 31st March 2015 or earlier.</p>

<p>2. One post of Senior Research Fellow under NAIP (Component-4) Bioprospecting of genes and allele mining for abiotic stress tolerance. The post duration is Upto 31st March 2014 or earlier</p>

<p>Essential Qualifications: Ph.D. in Bioinformatics/ Computer Application or<br />First Class Masters degree in Bioinformatics/ Computer Application with two years experience as evidenced by Publications.</p>

<p>Desirable: Experience in the field of handling Next generation Sequencing Data.</p>

<p>Emolument: Rs. 22,000/- per month + HRA as per admissibility</p>

<p>Age Limit:</p>

<p>40 years for Men<br />45 years for women as on date of interview</p>

<p>Research Associate: ONE</p>

<p>Duration of engagement: Upto</p>

<p>31st March 2015 or earlier &amp; Coterminus with the project</p>

<p>Responsibilities: To help the PI for Beta testing and development of the SanGenix Tool for NGS data.</p>

<p>Essential Qualifications: First Class Masters’ degree in Bioinformatics/Biotechnology.</p>

<p>Desirable: Experience in the field of Biotechnology/ Bioinformatics</p>

<p>Emoluments:</p>

<p>Rs. 16,000/- per month + HRA as per admissibility.<br />Senior Research Fellow: ONE<br />Duration of engagement: Upto 31st March 2014 or earlier &amp; Coterminus with the project</p>

<p>Age Limit</p>

<p>35 years for men<br />40 years for women as on date of interview</p>

<p>Note: Relaxation in age will be admissible for SC/ST &amp; OBC candidates as per Govt. of India /ICAR norms</p>

<p>1. The applicants must bring with them original documents and brief of research work done during post graduation along with a set of photocopy and latest two passport size photographs.<br />2. A panel of selected candidates will also be made which may be utilized for filling of positions of shorter durations in future if demand arises.<br />3. Experience certificate in original, if any 4. The above positions are purely on temporary basis and are co-terminus with the project. No TA/DA will be paid to attend the interview.<br />5. Any other clarifications can be had on the date of interview.<br />6. The Director’s decision will be final and binding on all respects.</p>

<p>Advertisement: http://210.212.93.85/rasrfadvertise.pdf</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10881/special-project-scientist-%E2%80%93-sorghum-genomics</guid>
  <pubDate>Tue, 20 May 2014 00:34:39 -0500</pubDate>
  <link></link>
  <title><![CDATA[Special Project Scientist – Sorghum Genomics]]></title>
  <description><![CDATA[
<p>ICRISAT is seeking applications from Indian Nationals for a Special Project Scientist to work on a sorghum genomics activities related to sequencing/re-sequencing projects utilizing New Generation Sequencing platforms.</p>

<p>The Job detail</p>

<p>    Advancing the SNP-discovery and polymorphism assessment work across several germplasm panels representing global genetic diversity<br />    Population genetic and genomic analyses, testing the hypothesis related to adaptation in multiple geographic regions<br />    Develop SNP assays from large scale GBS and other re-sequencing data for several target traits utilizing available phenotyping data<br />    Combined analyses of genotypic and phenotypic data for discovery of marker-trait associations, and conducting GWAS<br />    Processing, analyzing, and archiving large-scale genomic data sets, assessing data quality, conducting analyses, interpreting findings, and communicating findings to others including preparation of reports, presentations, posters and journal articles<br />    Providing support to MSc and PhD students on topic related to its major core of research<br />    Any other work assigned by the supervisor</p>

<p>The Person:</p>

<p>    PhD in bioinformatics, genetics, computational biology preferably with 1 to 2 years of experience;<br />    familiar with standard bioinformatics tools and scripting languages and emerging and evolving software platforms relevant to bioinformatics and computational biology;<br />    ability to create new analytical pipelines; experience with handling large data sets;<br />    ability to program in at least two of the following: C++, PERL, Python, R, Java.<br />    will use next-generation sequencing technologies to generate marker data for genetic mapping and transcriptome data for expression QTL mapping, and will be responsible for data generation as well as data analysis.</p>

<p>Period and Remuneration: The assignment is for a period of two years, and can be extended for another year depending on performance. ICRISAT pays a very attractive all inclusive lump sum assignment fee payable in Indian Rupees.</p>

<p>How to Apply: Please send your application by email to icrisatjobs@cgiar.org, stating the job title (Special project Scientist-Sorghum Genomics) clearly in the subject column, addressed to the Director, Human Resources and Operations, ICRISAT, Patancheru, Andhra Pradesh 502 324, India, latest by 10 June 2014. The application should include an up-to-date Curriculum Vitae, a short statement of competencies and experience for the position, and the names and addresses (including phone/e-mail) of three referees. Only short-listed candidates will be contacted.</p>

<p>More at: http://www.icrisat.org/careers/Special-Project-Scientist-Sorghum-Genomics.htm</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/11355/genomics-and-personalized-medicine-breakthroughs</guid>
	<pubDate>Sun, 01 Jun 2014 23:40:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/11355/genomics-and-personalized-medicine-breakthroughs</link>
	<title><![CDATA[Genomics and Personalized Medicine Breakthroughs]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/VAR-1vNc0TE" frameborder="0" allowfullscreen></iframe>http://bit.ly/e8QGzY Human genome mapping is now enabling a breakthrough in medical innovation -- personalized medicine. What does this mean for patients? We can now identify predispositions to disease, predict how we metabolize drugs, and figure out what kinds of treatments we may respond to, and even determine when a drug may give us an adverse reaction. All medical specialties benefit from human genome intelligence -- oncology saw the first impacts -- but advances are now being seen in cardiology, obstetrics and gynecology, pediatric diseases, gastroenterology, rheumatology, immunology and other areas. This video covers the areas that genetic medicine is impacting and where the future of genomic medicine is heading.]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/12944/orione-%E2%80%93-a-web-based-framework-for-ngs-analysis-in-microbiology</guid>
	<pubDate>Wed, 23 Jul 2014 06:43:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/12944/orione-%E2%80%93-a-web-based-framework-for-ngs-analysis-in-microbiology</link>
	<title><![CDATA[Orione – a web-based framework for NGS analysis in microbiology]]></title>
	<description><![CDATA[<p>End-to-end NGS microbiology data analysis requires a diversity of tools covering bacterial resequencing, de novo assembly, scaffolding, bacterial RNA-Seq, gene annotation and metagenomics. However, the construction of computational pipelines that use different software packages is difficult due to a lack of interoperability, reproducibility, and transparency. To overcome these limitations researchers at <a href="http://www.crs4.it/" target="_blank">CRS4</a>, Italy have developed Orione, a Galaxy-based framework consisting of publicly available research software and specifically designed pipelines to build complex, reproducible workflows for NGS microbiology data analysis. Enabling microbiology researchers to conduct their own custom analysis and data manipulation without software installation or programming, Orione provides new opportunities for data-intensive computational analyses in microbiology and metagenomics.</p>
<p>Reference</p>
<p>Cuccuru G1, Orsini M, Pinna A, Sbardellati A, Soranzo N, Travaglione A, Uva P, Zanetti G, Fotia G. (2014)<strong> Orione, a web-based framework for NGS analysis in microbiology.</strong> <em>Bioinformatics</em> [Epub ahead of print]. [<a href="http://bioinformatics.oxfordjournals.org/content/early/2014/03/10/bioinformatics.btu135.long" target="_blank">article</a>]</p><p>Address of the bookmark: <a href="http://orione.crs4.it/" rel="nofollow">http://orione.crs4.it/</a></p>]]></description>
	<dc:creator>Martin Jones</dc:creator>
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