<?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/28870?offset=200</link>
	<atom:link href="https://bioinformaticsonline.com/related/28870?offset=200" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/42326/edanchin-lab</guid>
  <pubDate>Thu, 19 Nov 2020 08:00:07 -0600</pubDate>
  <link></link>
  <title><![CDATA[Edanchin Lab]]></title>
  <description><![CDATA[
<p>My main topics of interest are:</p>

<p>The impact of non tree-like evolution such as horizontal gene transfers and hybridization on species biology<br />Evolution and adaptation of animals in the absence of sexual reproduction and the underlying mechanisms<br />Genomic signatures of adaptation to a parasitic life-style</p>

<p>More at https://edanchin.org/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37223/chopstitch-exon-annotation-and-splice-graph-construction-using-transcriptome-assembly-and-whole-genome-sequencing-data</guid>
	<pubDate>Tue, 03 Jul 2018 04:14:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37223/chopstitch-exon-annotation-and-splice-graph-construction-using-transcriptome-assembly-and-whole-genome-sequencing-data</link>
	<title><![CDATA[ChopStitch: exon annotation and splice graph construction using transcriptome assembly and whole genome sequencing data]]></title>
	<description><![CDATA[ChopStitch is a new method for finding putative exons and constructing splice graphs using an assembled transcriptome and whole genome shotgun sequencing (WGSS) data. ChopStitch identifies exon-exon boundaries in de novo assembled RNA-seq data with the help of a Bloom filter that represents the k-mer spectrum of WGSS reads. The algorithm also detects base substitutions in transcript sequences corresponding to sequencing or assembly errors, haplotype variations, or putative RNA editing events. The primary output of our tool is a FASTA file containing putative exons. Further, exon edges are interrogated for alternative exon-exon boundaries to detect transcript isoforms, which are reported as splice graphs in dot output format.<p>Address of the bookmark: <a href="https://github.com/bcgsc/ChopStitch" rel="nofollow">https://github.com/bcgsc/ChopStitch</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38579/genomeview-genome-browser-and-annotation-editor</guid>
	<pubDate>Wed, 02 Jan 2019 04:09:06 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38579/genomeview-genome-browser-and-annotation-editor</link>
	<title><![CDATA[GenomeView: genome browser and annotation editor]]></title>
	<description><![CDATA[<p><span>GenomeView is a genome browser and annotation editor that displays reference sequence, annotation, multiple alignments, short read alignments and graphs. Most major data formats are supported. Local and internet files can be loaded.</span><br><span>This project has moved to GitHub:&nbsp;</span><a href="https://github.com/GenomeView/genomeview" target="_blank">https://github.com/GenomeView/genomeview</a></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/genomeview/" rel="nofollow">https://sourceforge.net/projects/genomeview/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43272/bioinformatics-head-bioinformatics-manager-iii-cancer-genomics-research-laboratory-at-frederick-national-laboratory</guid>
  <pubDate>Wed, 18 Aug 2021 00:19:48 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Head (Bioinformatics Manager III), Cancer Genomics Research Laboratory at  Frederick National Laboratory]]></title>
  <description><![CDATA[
<p>Frederick National Laboratory seeking an enthusiastic, creative, and seasoned bioinformatics professional to join our leadership team and direct the exceptional Bioinformatics Group at the Cancer Genomics Research Laboratory (CGR).  CGR has a diverse team of bioinformatics and computational scientists that support all areas of bioinformatics and data analysis (infrastructure, data QC, pipeline development and maintenance, data curation and sharing, methodology development, statistical analyses, machine learning approaches, and scientific interpretation).</p>

<p>More at https://leidosbiomed.csod.com/ats/careersite/jobdetails.aspx?site=4&amp;c=leidosbiomed&amp;id=2040</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44902/hite-a-fast-and-accurate-dynamic-boundary-adjustment-approach-for-full-length-transposable-elements-detection-and-annotation-in-genome-assemblies</guid>
	<pubDate>Sat, 20 Sep 2025 09:34:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44902/hite-a-fast-and-accurate-dynamic-boundary-adjustment-approach-for-full-length-transposable-elements-detection-and-annotation-in-genome-assemblies</link>
	<title><![CDATA[HiTE: a fast and accurate dynamic boundary adjustment approach for full-length Transposable Elements detection and annotation in Genome Assemblies]]></title>
	<description><![CDATA[<p dir="auto"><code>HiTE</code>&nbsp;is a Python software that uses a dynamic boundary adjustment approach to detect and annotate full-length Transposable Elements in Genome Assemblies. In comparison to other tools, HiTE demonstrates superior performance in detecting a greater number of full-length TEs.</p>
<div dir="auto">
<h2 dir="auto">panHiTE</h2>
<a href="https://github.com/CSU-KangHu/HiTE#panhite"></a></div>
<p dir="auto">We have developed panHiTE, a comprehensive and accurate pipeline for TE detection in large-scale population genomes. It has been successfully applied to hundreds of plant population genomes, demonstrating its effectiveness and scalability.</p>
<p dir="auto">For detailed instructions, please refer to the&nbsp;<a href="https://github.com/CSU-KangHu/HiTE/wiki/panHiTE-tutorial">panHiTE tutorial</a>.</p><p>Address of the bookmark: <a href="https://github.com/CSU-KangHu/HiTE" rel="nofollow">https://github.com/CSU-KangHu/HiTE</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

<item>
  <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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44703/the-role-of-lncrna-in-bioinformatics-unlocking-the-secrets-of-the-genome</guid>
	<pubDate>Sat, 07 Dec 2024 02:09:47 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44703/the-role-of-lncrna-in-bioinformatics-unlocking-the-secrets-of-the-genome</link>
	<title><![CDATA[The Role of lncRNA in Bioinformatics: Unlocking the Secrets of the Genome]]></title>
	<description><![CDATA[<p>In the intricate dance of molecular biology, long non-coding RNAs (lncRNAs) have emerged as key players, capturing the interest of researchers worldwide. These RNA molecules, once dismissed as "junk," have proven to be vital in the regulation of gene expression, cellular processes, and the progression of diseases. The intersection of lncRNA studies and bioinformatics is transforming our understanding of these enigmatic molecules, offering profound insights into their structure, function, and therapeutic potential.</p><h3>What Are lncRNAs?</h3><p>lncRNAs are RNA transcripts longer than 200 nucleotides that do not code for proteins. Despite their non-coding nature, they play diverse roles in gene regulation, including chromatin remodeling, transcriptional control, and post-transcriptional processing. Unlike messenger RNAs (mRNAs), lncRNAs often function as scaffolds, decoys, or guides in cellular machinery, influencing biological processes such as cell differentiation, immune response, and even cancer metastasis.</p><h3>Challenges in lncRNA Research</h3><p>Identifying and understanding lncRNAs pose unique challenges:</p><ol>
<li><strong>High Sequence Variability</strong>: Unlike protein-coding genes, lncRNAs exhibit low sequence conservation across species, making functional predictions difficult.</li>
<li><strong>Low Expression Levels</strong>: lncRNAs are often expressed at low levels, complicating their detection in transcriptomic data.</li>
<li><strong>Diverse Functions</strong>: The multifunctional nature of lncRNAs requires advanced computational tools to decipher their roles in complex networks.</li>
</ol><h3>Bioinformatics: A Crucial Ally in lncRNA Research</h3><p>Bioinformatics bridges the gap between raw biological data and meaningful insights, making it indispensable in lncRNA research. Here&rsquo;s how:</p><h4>1. <strong>Identification and Annotation</strong></h4><p>High-throughput sequencing technologies like RNA-seq generate vast amounts of data. Bioinformatics tools such as <em>StringTie</em>, <em>Cufflinks</em>, and <em>HISAT2</em> help assemble and annotate lncRNAs from this data. Additionally, databases like NONCODE, LNCipedia, and Ensembl provide curated repositories of lncRNA sequences and annotations.</p><h4>2. <strong>Functional Prediction</strong></h4><p>Bioinformatics algorithms predict the potential functions of lncRNAs by analyzing their interactions with DNA, RNA, and proteins. Tools like LncRNA2Function and RIblast utilize sequence motifs and secondary structure predictions to hypothesize about the roles of specific lncRNAs.</p><h4>3. <strong>Network Construction</strong></h4><p>lncRNAs often act as regulatory hubs. Bioinformatics platforms such as Cytoscape enable the visualization of lncRNA-mediated networks, elucidating their roles in pathways like cell cycle regulation and apoptosis.</p><h4>4. <strong>Epigenetic Studies</strong></h4><p>lncRNAs are known to interact with chromatin-modifying complexes, influencing gene expression epigenetically. Tools like ChIP-seq and ATAC-seq, combined with computational pipelines, identify these interactions and map them to the genome.</p><h4>5. <strong>Clinical Applications</strong></h4><p>Bioinformatics aids in the discovery of lncRNA biomarkers for diseases like cancer and neurodegenerative disorders. Machine learning models analyze differential expression profiles, helping prioritize lncRNAs with therapeutic potential.</p><h3>Case Study: lncRNAs in Cancer Research</h3><p>lncRNAs such as HOTAIR and MALAT1 have been implicated in cancer progression. Bioinformatics analyses have revealed their roles in promoting metastasis and altering the tumor microenvironment. For example, transcriptome analysis in cancer patients identifies lncRNA expression signatures, enabling precision medicine approaches.</p><h3>Future Directions</h3><p>The fusion of bioinformatics with experimental biology is unlocking the secrets of lncRNAs. Advances in artificial intelligence, single-cell sequencing, and structural modeling promise to overcome current limitations. Here are some promising directions:</p><ul>
<li><strong>Integrative Analysis</strong>: Combining multi-omics data to understand the interplay of lncRNAs with other biomolecules.</li>
<li><strong>CRISPR Screens</strong>: Leveraging bioinformatics to design CRISPR-based functional screens for lncRNAs.</li>
<li><strong>Therapeutic Development</strong>: Using bioinformatics to design lncRNA-based therapeutics, including antisense oligonucleotides and RNA interference tools.</li>
</ul><h3>Conclusion</h3><p>lncRNAs are the hidden gems of the genome, and bioinformatics is the key to unearthing their full potential. As research progresses, lncRNAs could pave the way for novel diagnostics, targeted therapies, and personalized medicine, revolutionizing our approach to complex diseases.</p><p>The journey into the world of lncRNAs is only beginning, and bioinformatics will continue to play a pivotal role in decoding these molecular mysteries. Whether you&rsquo;re a researcher, clinician, or bioinformatics enthusiast, the study of lncRNAs offers a fascinating frontier of discovery.</p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/4004/33rd-annual-convention-of-indian-association-for-cancer-research-from-13th-to-15th-february-2014</guid>
  <pubDate>Tue, 27 Aug 2013 10:37:08 -0500</pubDate>
  <link></link>
  <title><![CDATA[33rd Annual Convention of Indian Association for Cancer Research from 13th to 15th February 2014]]></title>
  <description><![CDATA[
<p>RGCB is organizing the 33rd Annual Convention of Indian Association for Cancer Research from 13th to 15th February 2014 with the theme "Discovery, Innovation and Translation in Cancer Research"</p>

<p>Kindly log on to conference website http://rgcb.res.in/IACR2014 for further details and timely updates and registration. We shall truly appreciate if the same be circulated among your friends, scholars and students encouraging them to participate in the meet.</p>

<p>http://210.212.237.38/iacrconference/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/2336/3rd-annual-next-generation-sequencing-asia-congress-2013-at-singapore-singapore</guid>
  <pubDate>Wed, 14 Aug 2013 09:55:04 -0500</pubDate>
  <link></link>
  <title><![CDATA[3rd Annual Next Generation Sequencing Asia Congress 2013 at Singapore, Singapore]]></title>
  <description><![CDATA[
<p>The 3rd Annual Next Generation Sequencing Asia Congress is to be held on the 22nd and 23rd of October 2013 in Singapore. Over the 2 days, the conference will provide an overview of the current options of next-generation sequencing platforms, technologies, applications and the newest computational tools for the analysis of next-generation sequencing data and analytical genomics as well as overcoming data management problems. The event will attract over 200 senior-level decision makers working in areas such as next generation sequencing, analytical genomics, computational biology, oncology, RNA profiling, molecular genomics, biomarkers, bioinformatics &amp; data management and clinical &amp; diagnostics development.</p>

<p>Dated : 22 Nov 2013 -23 Nov 2013</p>

<p>http://www.ngsasia-congress.com/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/39469/introduction-to-bioinformatics</guid>
	<pubDate>Wed, 05 Jun 2019 14:58:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/39469/introduction-to-bioinformatics</link>
	<title><![CDATA[Introduction to Bioinformatics]]></title>
	<description><![CDATA[<p><img src="https://edu.t-bio.info/wp-content/uploads/2017/07/Introduction-Course-Title-11.jpg" alt="Introduction to Bioinformatics Course" width="600" height="315.6" style="vertical-align: top; border: 0px; border: 0px;"></p><p>Introduction to bioinformatics is a course for biologists and clinicians that would like to learn more about the way bioinformatics is used in healthcare, biotech and pharmaceuitcal industry as well as basic research. The course covers many of the topics transformed by the emergence of big data and computational technologies. To learn more about the course, visit:&nbsp;<a href="https://edu.t-bio.info/course/introduction-bioinformatics/">https://edu.t-bio.info/course/introduction-bioinformatics/</a></p>]]></description>
	<dc:creator>eliabrodsky</dc:creator>
</item>

</channel>
</rss>