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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31209?offset=40</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32849/car-reconstructing-contiguous-regions-of-an-ancestral-genome</guid>
	<pubDate>Thu, 18 May 2017 05:24:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32849/car-reconstructing-contiguous-regions-of-an-ancestral-genome</link>
	<title><![CDATA[CAR: Reconstructing Contiguous Regions of an Ancestral Genome]]></title>
	<description><![CDATA[<div id="abstract-1">
<p id="p-5">We describe a new method for predicting the ancestral order and orientation of those intervals from their observed adjacencies in modern species. We combine the results from this method with data from chromosome painting experiments to produce a map of an early mammalian genome that accounts for 96.8% of the available human genome sequence data. The precision is further increased by mapping inversions as small as 31 bp. Analysis of the predicted evolutionary breakpoints in the human lineage confirms certain published observations but disagrees with others. Although only a few mammalian genomes are currently sequenced to high precision, our theoretical analyses and computer simulations indicate that our results are reasonably accurate and that they will become highly accurate in the foreseeable future. Our methods were developed as part of a project to reconstruct the genome sequence of the last ancestor of human, dogs, and most other placental mammals;</p>
</div><p>Address of the bookmark: <a href="http://www.bx.psu.edu/miller_lab/car/" rel="nofollow">http://www.bx.psu.edu/miller_lab/car/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/6458/bigre-lab</guid>
  <pubDate>Sun, 17 Nov 2013 10:35:49 -0600</pubDate>
  <link></link>
  <title><![CDATA[BIGRE Lab]]></title>
  <description><![CDATA[
<p>The Laboratoire de Bioinformatique des Génomes et des Réseaux (Genome and Network Bioinformatics) is specialized in the conception, implementation, evaluation and application of bioinformatics approaches for the analysis of genome, transcriptome, proteome and metabolism.<br />Our main activities include</p>

<p>Analysis of regulatory sequences (RSAT project)<br />Classification and analysis of mobile genetic elements (ACLAME project).<br />Analysis of molecular interaction networks (NeAT project)<br />Inference of metabolic pathways from genomic and post-genomic data <br />(metabolic pathfinding, see also metabolic pathfinding in NeAT)<br />Critical assesment of protein interactions (CAPRI)</p>

<p>Lab Page http://www.bigre.ulb.ac.be/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36239/scilifelab-tutorial-for-bioinformatics-analysis</guid>
	<pubDate>Tue, 17 Apr 2018 04:33:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36239/scilifelab-tutorial-for-bioinformatics-analysis</link>
	<title><![CDATA[SciLifeLab tutorial for bioinformatics analysis !]]></title>
	<description><![CDATA[<p>SciLifeLab is a national center for molecular biosciences with focus on health and environmental research.</p>
<h2 id="courses">Courses</h2>
<p><a href="http://uppnex.se/twiki/bin/view/Courses/">Old courses (2012-2014)</a></p>
<h3 id="metagenomics-workshop">Metagenomics Workshop</h3>
<p><a href="https://scilifelab.github.io/courses/Metagenomics/1511/">2015 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/Metagenomics/1611/">2016 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/Metagenomics/1711/">2017 November - Uppsala</a></p>
<h3 id="introduction-to-bioinformatics-using-ngs-data">Introduction to Bioinformatics Using NGS Data</h3>
<p><a href="https://scilifelab.github.io/courses/ngsintro/1502/">2015 February - Uppsala</a>&nbsp;<br><a href="https://scilifelab.github.io/courses/ngsintro/1505/">2015 May - Gothenburg</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1509/">2015 September - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1511/">2015 November - Lund</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1601/">2016 January - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1604/">2016 April - Link&ouml;ping</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1609/">2016 September - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1611/">2016 November - Ume&aring;</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1701/">2017 January - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1705/">2017 May - Gothenburg</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1709/">2017 September - Lund</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1711/">2017 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1802/">2018 February - Uppsala</a></p>
<h3 id="introduction-to-genome-annotation">Introduction to Genome Annotation</h3>
<p><a href="https://scilifelab.github.io/courses/annotation/2015/">2015 April - Uppsala</a><br><a href="https://scilifelab.github.io/courses/annotation/2016/">2016 April - Uppsala</a><br><a href="https://scilifelab.github.io/courses/annotation/2017/">2017 April - Uppsala</a><br><a href="https://scilifelab.github.io/courses/annotation/2018/">2018 May - Uppsala</a></p>
<h3 id="de-novo-genome-assembly">De Novo Genome Assembly</h3>
<p><a href="https://scilifelab.github.io/courses/assembly/1611/">2016 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/assembly/2017-11-15/">2017 November - Uppsala</a></p>
<h3 id="rna-seq-course">RNA-seq course</h3>
<p><a href="https://scilifelab.github.io/courses/rnaseq/1510/">2015 October - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/1604/">2016 April - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/1610/">2016 October - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/1703/">2017 March - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/1711/">2017 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/labs">RNAseq tutorials</a></p>
<h3 id="r-programming-foundations-for-life-scientists">R Programming Foundations for Life Scientists</h3>
<p><a href="https://scilifelab.github.io/courses/r_programming/1611/">2016 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/r_programming/1703/">2017 Mars - Uppsala</a></p>
<h3 id="single-cell-rna-sequencing-analysis">Single cell RNA sequencing analysis</h3>
<p><a href="https://scilifelab.github.io/courses/scrnaseq/1710/">2017 October - Uppsala</a></p><p>Address of the bookmark: <a href="https://scilifelab.github.io/courses/" rel="nofollow">https://scilifelab.github.io/courses/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36880/jvarkit-java-utilities-for-bioinformatics</guid>
	<pubDate>Fri, 08 Jun 2018 09:31:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36880/jvarkit-java-utilities-for-bioinformatics</link>
	<title><![CDATA[Jvarkit : Java utilities for Bioinformatics]]></title>
	<description><![CDATA[Collection of Java tool kits for bioinformatics works:

Jvarkit : Java utilities for Bioinformatics<p>Address of the bookmark: <a href="http://lindenb.github.io/jvarkit/" rel="nofollow">http://lindenb.github.io/jvarkit/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41991/sequence-ontology-bioinformatics-analysis-soba-tool-to-provide-a-simple-statistical-and-graphical-summary-of-an-annotated-genome</guid>
	<pubDate>Wed, 22 Jul 2020 10:11:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41991/sequence-ontology-bioinformatics-analysis-soba-tool-to-provide-a-simple-statistical-and-graphical-summary-of-an-annotated-genome</link>
	<title><![CDATA[Sequence Ontology Bioinformatics Analysis (SOBA) tool to provide a simple statistical and graphical summary of an annotated genome]]></title>
	<description><![CDATA[<p><span>We have developed the Sequence Ontology Bioinformatics Analysis (SOBA) tool to provide a simple statistical and graphical summary of an annotated genome. We envisage its use during annotation jamborees, genome comparison and for use by developers for rapid feedback during annotation software development and testing. SOBA also provides annotation consistency feedback to ensure correct use of terminology within annotations, and guides users to add new terms to the Sequence Ontology when required. SOBA is available at http://www.sequenceontology.org/cgi-bin/soba.cgi.</span></p>
<p><span>More at <a href="https://pubmed.ncbi.nlm.nih.gov/20494974/">https://pubmed.ncbi.nlm.nih.gov/20494974/</a></span></p><p>Address of the bookmark: <a href="http://www.sequenceontology.org/cgi-bin/soba.cgi" rel="nofollow">http://www.sequenceontology.org/cgi-bin/soba.cgi</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43292/bioinformatics-scientist-production-bioinformatics-south-san-francisco-ca</guid>
  <pubDate>Thu, 19 Aug 2021 08:45:24 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Scientist, Production Bioinformatics @ South San Francisco, CA]]></title>
  <description><![CDATA[
<p>wist is looking for a Bioinformatics Scientist to join our Production Bioinformatics Team. You will work alongside research scientists, software engineers and data scientists to further deliver on our mission to expand access to best-in-class synthetic biology and next-generation sequencing applications. You will be developing and engineering tools to better evaluate and build hardened, production quality pipelines, optimize data quality, and automate lab and bioinformatics processes. Our ideal candidate is an organized problem solver with a background in developing and building novel production-quality bioinformatics tools and packages. Equally excellent communication skills and a proven ability to work independently are required.</p>

<p>More at https://boards.greenhouse.io/twistbioscience/jobs/3135495?gh_src=9ecc0b941us</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43559/job-offer-for-a-postdoctoral-researcher-in-genomics-bioinformatics-2-years</guid>
  <pubDate>Fri, 22 Oct 2021 04:44:33 -0500</pubDate>
  <link></link>
  <title><![CDATA[Job offer for a postdoctoral researcher in genomics / bioinformatics (2 years)]]></title>
  <description><![CDATA[
<p>Ongoing research in the group of Karine Van Doninck involves topics at the core of<br />evolutionary biology, including the evolution of sex, genome maintenance,<br />recombination and extreme stress resistance on different eukaryotic systems,<br />including rotifers, amoeba and Corbicula clams. We are employing different tools<br />(including experimental ecology, population genetics, phylogeny, comparative<br />genomics, transcriptomics, bioinformatics, molecular and cellular biology) to study<br />evolutionary processes at the level of populations, both experimental and natural, and<br />genomes.</p>

<p>Offer<br />We offer a full-time contract for two years. The contract starts between October 2021<br />and December 2021. The position involves no or extremely light teaching load, if the<br />candidate is interested. Salaries are competitive at the European level. The recruited<br />person will benefit from the Belgian social insurance scheme (health care, etc.) without<br />additional expenses.</p>

<p>Profile<br />Applicants are expected to show outstanding commitment to research and must have<br />obtained a PhD by the start of the position. A strong expertise in genomics is required.<br />More specifically, solid competences in bioinformatics (e.g. scripting pipelines) and in<br />genome evolution are needed. Knowledge or interest regarding recombination,<br />metazoan evolution, phylogenomics and population genomics is an added-value.</p>

<p>Application<br />Applications should be submitted via email to karine.van.doninck@ulb.be. The<br />application package should contain the following documents:<br />- A curriculum vitae with the complete list of publications<br />- A cover letter mentioning why the candidate is interested in the position<br />- Minimum 2 recommendation letters<br />Interviews: Interviews will be conducted with the selected candidates. Selected<br />candidates could also be invited to give a seminar to MBE ULB.<br />For any additional information, please contact karine.van.doninck@ulb.be</p>
]]></description>
</item>
<item>
	<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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42166/software-for-genome-assembly</guid>
	<pubDate>Sun, 30 Aug 2020 09:51:38 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42166/software-for-genome-assembly</link>
	<title><![CDATA[Software for genome assembly !]]></title>
	<description><![CDATA[<p>List of bioinformatics tools/Software Website References for genome assembly:</p><p>1 Falcon&nbsp;https://github.com/PacificBiosciences/pb-assembly</p><p>2 Canu assembler http://canu.readthedocs.io/en/latest/index.html</p><p>3 Miniasm assembler https://github.com/lh3/miniasm</p><p>4 PBJelly scaffolding tool https://sourceforge.net/projects/pb-jelly/</p><p>5 ARCS scaffolding tool https://github.com/bcgsc/arcs</p><p>6 Redundans reduction and scaffolding tool https://github.com/Gabaldonlab/redundans</p><p>7 Arrow error correction https://github.com/PacificBiosciences/ GenomicConsensus</p><p>8 PILON error correction https://github.com/broadinstitute/pilon/wiki</p><p>9 BUSCO single copy gene markers http://busco.ezlab.org/</p><p>10 Bandage graph assembly viewer https://rrwick.github.io/Bandage/</p><p>11 Gepard dotter http://cube.univie.ac.at/gepard</p><p>12 MUMmer aligner and plotter http://mummer.sourceforge.net/</p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44472/pipesnake-bioinformatics-best-practice-analysis-pipeline-for-phylogenomic-reconstruction</guid>
	<pubDate>Wed, 21 Feb 2024 06:19:41 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44472/pipesnake-bioinformatics-best-practice-analysis-pipeline-for-phylogenomic-reconstruction</link>
	<title><![CDATA[pipesnake: bioinformatics best-practice analysis pipeline for phylogenomic reconstruction]]></title>
	<description><![CDATA[<p dir="auto"><span>ausarg/pipesnake</span>&nbsp;is a bioinformatics best-practice analysis pipeline for phylogenomic reconstruction starting from short-read 'second-generation' sequencing data.</p>
<p dir="auto">The pipeline is built using&nbsp;<a href="https://www.nextflow.io/">Nextflow</a>, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The&nbsp;<a href="https://www.nextflow.io/docs/latest/dsl2.html">Nextflow DSL2</a>&nbsp;implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies.</p><p>Address of the bookmark: <a href="https://github.com/AusARG/pipesnake" rel="nofollow">https://github.com/AusARG/pipesnake</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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