<?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/26629?offset=960</link>
	<atom:link href="https://bioinformaticsonline.com/related/26629?offset=960" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/13337/phd-opportunity-at-universite-de-liege-belgium</guid>
  <pubDate>Sat, 02 Aug 2014 01:12:43 -0500</pubDate>
  <link></link>
  <title><![CDATA[PhD opportunity at Université de Liège - Belgium]]></title>
  <description><![CDATA[
<p>PhD opportunity at Université de Liège - Belgium</p>

<p>The Bioinformatics and Systems Biology Unit of Université de Liège (Belgium) is looking for a highly motivated master student with programming skills for a PhD thesis project (4 years, fully funded) with the goal of designing computational tools that use literature, genomic and structural data in order to infer regulatory and metabolic networks.  </p>

<p>Applicants are invited to send their resume and a recommendation letter to Prof. Patrick Meyer (more details at   www.biosys.ulg.ac.be )</p>

<p>For more information : www.biosys.ulg.ac.be</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/39704/the-rogers-lab</guid>
  <pubDate>Mon, 15 Jul 2019 08:07:44 -0500</pubDate>
  <link></link>
  <title><![CDATA[The Rogers Lab]]></title>
  <description><![CDATA[
<p>The Rogers lab studies evolution of genome structure. We explore the ways that complex mutations like duplications, deletions, rearrangements, and retrogenes can create new genetic material. We study how these new mutations are important for adaptation. We are currently working on projects in Drosophila, Mammoths, Elephants, Bivalves, and Frogs absolutely no amphibians. This multi-organism approach can help us understand when and why complex mutations are important for organism fitness.</p>

<p>More at http://evolscientist.com/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/13523/megadock-40</guid>
	<pubDate>Thu, 07 Aug 2014 18:08:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/13523/megadock-40</link>
	<title><![CDATA[MEGADOCK 4.0]]></title>
	<description><![CDATA[<p>An ultra&ndash;high-performance protein&ndash;protein docking software for heterogeneous supercomputers</p>
<p id="p-4"><strong>Summary:</strong> The application of protein&ndash;protein docking in large-scale interactome analysis is a major challenge in structural bioinformatics and requires huge computing resources. In this work, we present MEGADOCK 4.0, an FFT-based docking software that makes extensive use of recent heterogeneous supercomputers and shows powerful, scalable performance of over 97% strong scaling.</p>
<p id="p-5"><strong>Availability and Implementation:</strong> MEGADOCK 4.0 is written in C++ with OpenMPI and NVIDIA CUDA 5.0 (or later) and is freely available to all academic and non-profit users at: <a href="http://www.bi.cs.titech.ac.jp/megadock">http://www.bi.cs.titech.ac.jp/megadock</a>.</p>
<p id="p-6"><strong>Contact:</strong> <a href="mailto:akiyama@cs.titech.ac.jp">akiyama@cs.titech.ac.jp</a></p><p>Address of the bookmark: <a href="http://bioinformatics.oxfordjournals.org/content/early/2014/08/06/bioinformatics.btu532.short" rel="nofollow">http://bioinformatics.oxfordjournals.org/content/early/2014/08/06/bioinformatics.btu532.short</a></p>]]></description>
	<dc:creator>Suleman Khan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42798/what-is-the-hologenome-concept-of-evolution</guid>
	<pubDate>Wed, 03 Feb 2021 12:23:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42798/what-is-the-hologenome-concept-of-evolution</link>
	<title><![CDATA[What is the hologenome concept of evolution?]]></title>
	<description><![CDATA[<p><span>All multicellular organisms are colonized by microbes, but a gestalt study of the composition of microbiome communities and their influence on the ecology and evolution of their macroscopic hosts has only recently become possible. One approach to thinking about the topic is to view the host&ndash;microbiome ecosystem as a &ldquo;holobiont&rdquo;.</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6198262/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6198262/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/14024/grapher</guid>
	<pubDate>Thu, 14 Aug 2014 14:02:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/14024/grapher</link>
	<title><![CDATA[GrapheR !!!]]></title>
	<description><![CDATA[<p>What a wonderful gem <em>GrapheR</em> is.... Oh yes it is. <em>GrapheR</em> is a GUI for base graphics in R by http://www.maximeherve.com/. The package provides a graphical user interface for creating base charts in R. It is ideal for beginners in R, as the user interface is very clear and the code is written along side into a text file, allowing users to recreate the charts directly in the console. <br /><br />Adding and changing legends? Messing around with the plotting window settings? It is much easier/quicker with this GUI than reading the help file and trying to understand the various parameters.<br />Here is a little example using the iris data set.<br /><br />library(GrapheR)<br />data(iris)<br />run.GrapheR()<br /><br />This will bring up a window that helps me to create the chart and tweak the various parameters.</p><p><img src="http://4.bp.blogspot.com/-NbnCM1dPh3E/U9aW9YxJ9oI/AAAAAAAABgo/gEPzPhOpf2Y/s1600/GrapheR.png" alt="image" width="878" height="868" style="border: 0px; border: 0px;"><br /><br />Finally, I find the underlying R code in a file created by <em>GrapheR</em>. For more details read also the <a href="http://cran.r-project.org/web/packages/GrapheR/index.html" target="_blank">package vignette</a>, which is available in <a href="http://cran.r-project.org/web/packages/GrapheR/vignettes/manual_en.pdf" target="_blank">English</a>, <a href="http://cran.r-project.org/web/packages/GrapheR/vignettes/manual_fr.pdf" target="_blank">French</a> and <a href="http://cran.r-project.org/web/packages/GrapheR/vignettes/manual_de.pdf" target="_blank">German</a>!</p>]]></description>
	<dc:creator>John Parker</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44219/chromosome-breakpoint-a-breakup-to-remember</guid>
	<pubDate>Tue, 07 Mar 2023 13:31:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44219/chromosome-breakpoint-a-breakup-to-remember</link>
	<title><![CDATA[Chromosome breakpoint - a breakup to remember]]></title>
	<description><![CDATA[<div><div><div><div><div><div><div><div><div><div><p>Chromosome breakpoint refers to the physical location where a chromosome is broken and rearranged. Chromosome breakage can occur spontaneously or be induced by environmental factors such as radiation, chemicals, or viruses. The rearrangement of genetic material resulting from a chromosome breakpoint can have important consequences, including the development of genetic diseases, chromosomal abnormalities, or cancer.</p><p>Chromosome breakpoints can occur in two ways: interstitial or terminal. Interstitial breakpoints occur within the chromosome, while terminal breakpoints occur at the end of the chromosome. Terminal breakpoints can lead to the loss of genetic material, whereas interstitial breakpoints can result in the duplication or deletion of genetic material.</p><p>Chromosome breakpoints can be detected using a variety of techniques, including cytogenetic analysis, fluorescence in situ hybridization (FISH), and molecular methods such as polymerase chain reaction (PCR) and next-generation sequencing (NGS). These techniques can also help identify the exact location of the breakpoint and the nature of the rearrangement, such as translocations, inversions, deletions, or duplications.</p><p>Translocations are one of the most common types of chromosome rearrangements caused by breakpoints. In a translocation, genetic material is exchanged between two different chromosomes, resulting in a balanced or unbalanced distribution of genetic material. Unbalanced translocations can cause genetic diseases or developmental abnormalities, while balanced translocations can be inherited without any apparent phenotypic effects.</p><p>Inversions occur when a chromosome segment is inverted, resulting in a change in the order of genetic material. Inversions can be pericentric, involving the centromere, or paracentric, not involving the centromere. Inversions can cause genetic diseases or phenotypic effects if they disrupt the function of essential genes or regulatory elements.</p><p>Deletions and duplications are caused by interstitial breakpoints that result in the loss or gain of genetic material. Deletions can cause genetic diseases or developmental abnormalities if they involve essential genes or regulatory elements. Duplications can also have phenotypic effects, depending on the location and size of the duplicated segment.</p><p>Chromosome breakpoints can also be involved in the formation of complex chromosomal rearrangements, such as ring chromosomes or dicentric chromosomes. These complex rearrangements can have important clinical implications, as they can cause genetic diseases or cancer.</p><p>In conclusion, chromosome breakpoints are important genetic events that can lead to the rearrangement of genetic material and have important clinical implications. The detection and characterization of chromosome breakpoints using cytogenetic, molecular, and genomic methods are essential for the diagnosis, prognosis, and treatment of genetic diseases and cancer. Further research is needed to understand the molecular mechanisms underlying chromosome breakage and to develop new therapies targeting these events.</p></div></div></div></div></div></div></div></div></div></div>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/14186/pybedtools</guid>
	<pubDate>Wed, 20 Aug 2014 01:03:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/14186/pybedtools</link>
	<title><![CDATA[pybedtools]]></title>
	<description><![CDATA[<p>pybedtools is a Python wrapper for Aaron Quinlan's BEDtools programs (https://github.com/arq5x/bedtools), which are widely used for genomic interval manipulation or "genome algebra". pybedtools extends BEDTools by offering feature-level manipulations from with Python. See full online documentation, including installation instructions, at http://pythonhosted.org/pybedtools/.</p><p>More at http://pythonhosted.org/pybedtools/</p><p>A powerful toolset for genome arithmetic.http://code.google.com/p/bedtools/</p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44799/unlocking-evolutionary-secrets-a-dive-into-comparative-genomics-methods</guid>
	<pubDate>Tue, 20 May 2025 00:25:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44799/unlocking-evolutionary-secrets-a-dive-into-comparative-genomics-methods</link>
	<title><![CDATA[Unlocking Evolutionary Secrets: A Dive into Comparative Genomics Methods]]></title>
	<description><![CDATA[<p>Comparative genomics is the art and science of comparing genomes&mdash;across species, within species, or even among individuals&mdash;to unravel evolutionary relationships, functional elements, and genetic adaptations. As sequencing technologies have advanced and genome databases have expanded, comparative genomics has become a cornerstone of modern biology, shedding light on everything from antibiotic resistance in bacteria to human disease genetics.</p><p>In this post, we&rsquo;ll explore the core methods used in comparative genomics, the questions they help answer, and how they&rsquo;re shaping our understanding of life.</p><p><strong>1. Whole-Genome Alignment</strong><br />Whole-genome alignment involves mapping the entire genome of one species to another. Tools like MUMmer, MAUVE, and LASTZ perform large-scale sequence alignments to detect conserved regions, rearrangements, insertions, and deletions.</p><p>Use Case:<br />Comparing human and chimpanzee genomes to identify evolutionary conserved sequences (ECS) and regions of divergence.</p><p>Key Challenges:<br />Handling repetitive sequences and genome rearrangements.</p><p>Computational complexity in large genomes.</p><p><strong>2. Synteny and Collinearity Analysis</strong><br />Synteny refers to conserved blocks of gene order across species. Tools like MCScanX, SynMap, or CHITRA (for visualizing synteny interactively) detect these blocks to understand chromosomal evolution.</p><p>Use Case:<br />Studying ancient genome duplications in plants.</p><p>Investigating chromosomal rearrangements in cancer genomes.</p><p><strong>3. Ortholog and Paralog Detection</strong><br />Orthologs are genes in different species that evolved from a common ancestor, while paralogs are genes duplicated within a genome. Identifying them is crucial for functional annotation and evolutionary studies.</p><p>Popular Tools:<br />OrthoFinder, Orthologous MAtrix (OMA), InParanoid, and EggNOG.</p><p>Use Case:<br />Functional prediction of uncharacterized genes based on orthologs in model organisms.</p><p>Tracing gene family evolution.</p><p><strong>4. Phylogenomic Analysis</strong><br />Phylogenomic methods combine phylogenetics and genomics to infer evolutionary trees based on genome-wide data. These methods can handle dozens to hundreds of genomes, using concatenated alignments or gene trees.</p><p>Tools:<br />RAxML, IQ-TREE, ASTRAL, Phylip, BEAST.</p><p>Use Case:<br />Resolving the evolutionary relationships between microbial species.</p><p>Studying speciation events.</p><p><strong>5. Pan-Genome Analysis</strong><br />The pan-genome consists of the core genome (shared by all strains) and the accessory genome (strain-specific genes). This is especially popular in microbial genomics.</p><p>Tools:<br />Roary, Panaroo, BPGA, PGAP.</p><p>Use Case:<br />Understanding virulence factor diversity in E. coli.</p><p>Designing broad-spectrum vaccines.</p><p><strong>6. Comparative Transcriptomics</strong><br />Comparing transcriptomes across species or conditions reveals conserved and unique expression patterns. RNA-seq data can be mapped to reference genomes to identify orthologous expression profiles.</p><p>Use Case:<br />Comparing stress response in extremophiles and model species.</p><p>Studying conserved regulatory networks.</p><p><strong>7. Functional Element Comparison</strong><br />Beyond genes, comparative genomics also targets non-coding regions&mdash;enhancers, promoters, miRNAs. Conservation across species often implies functional importance.</p><p>Tools:<br />PhastCons, GERP, phyloP (based on multiple alignments).</p><p>Use Case:<br />Detecting conserved non-coding elements in vertebrates.</p><p>Studying regulatory divergence in human evolution.</p><p><strong>8. Horizontal Gene Transfer (HGT) Detection</strong><br />In microbes, genes often jump across species boundaries. Comparative genomics can detect HGT by identifying genes that defy the expected phylogenetic pattern.</p><p>Tools:<br />HGTector, DarkHorse, AlienHunter, SIGI-HMM.</p><p>Use Case:<br />Tracing antibiotic resistance genes.</p><p>Exploring microbial adaptability in extreme environments.</p><p><strong>Final Thoughts</strong><br />Comparative genomics is a powerful lens to observe the diversity and unity of life. With a broad toolkit&mdash;from aligners to orthology pipelines, phylogenetic engines to visualization tools&mdash;it allows scientists to ask big questions: How did genomes evolve? What makes species unique? Where do new genes come from?</p><p>Whether you're studying extremophiles, building better crops, or exploring human ancestry, comparative genomics offers the methods to connect the dots across the tree of life.</p><p>&nbsp;</p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/3885/precision-medicine</guid>
	<pubDate>Sat, 24 Aug 2013 15:47:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/3885/precision-medicine</link>
	<title><![CDATA[Precision Medicine]]></title>
	<description><![CDATA[<p>Coupling established clinical&ndash;pathological indexes with state-of-the-art molecular profiling to create diagnostic, prognostic, and therapeutic strategies precisely tailored to each patient's requirements &mdash; hence the term &ldquo;Precision medicine&rdquo;&nbsp;</p>
<p>Source:<a href="http://www.nejm.org/doi/full/10.1056/NEJMp1114866">http://www.nejm.org/doi/full/10.1056/NEJMp1114866</a></p>
<p><strong>Another video on precision medicine</strong>:</p>
<p><a href="http://www.youtube.com/watch?v=Pi8W0yOXnzE">http://www.youtube.com/watch?v=Pi8W0yOXnzE</a></p>
<p>Precision Medicine basically intergrates bioinformatics, genomics , genetics, molecular biology and nanotechnology to deliver precise cure/diagnotics to a specific patient.</p>
<p>Examples:</p>
<ul>
<li><span>The drug imatinib (Gleevec) designed to inhibit an altered enzyme produced by a fused version of two genes found in chronic myelogenous leukemia.</span></li>
<li><span>The breast cancer drug trastuzumab (Herceptin) works only for women whose tumors have a particular genetic profile called HER-2 positive.</span></li>
</ul>
<p><span>E.g. source :</span></p>
<p><span><a href="http://www.bionews-tx.com/news/2013/08/15/how-the-impact-of-cancer-genomics-on-precision-medicine-is-revolutionizing-cancer-treatment/">http://www.bionews-tx.com/news/2013/08/15/how-the-impact-of-cancer-genomics-on-precision-medicine-is-revolutionizing-cancer-treatment/</a></span></p><p>Address of the bookmark: <a href="http://www.cbsnews.com/video/watch/?id=50149783n" rel="nofollow">http://www.cbsnews.com/video/watch/?id=50149783n</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/14904/bioinformatics-jrfsrf-position-at-iari</guid>
  <pubDate>Thu, 04 Sep 2014 04:14:01 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics JRF/SRF position at IARI]]></title>
  <description><![CDATA[
<p>DIVISION OF NEMATOLOGY<br />INDIAN AGRICULTURAL RESEARCH INSTITUTE<br />NEW DELHI 110012<br />Applications are invited for the posts of one Junior<br />Research Fellow and one RA in the DBT funded project entitled “ Plant parasitic nematode genome informatics - insilico resource development”. The project is for a period of three years. </p>

<p>Essential qualifications for JRF<br />: M. Sc. in Bioinformatics with experience in Proteomics, genomics and structural biology. Knowledge of programming language, pearl and database – HTML, CSS,php and Java script.<br />Essential qualifications for Research Associate:<br />MSc/MTech in Bioinformatics with three years experience or Ph.D in Bioinformatics with experience in proteomics, genomics and structural biology. Knowledge of programming language, perl and database<br />– HTML, CSS, Java script. NGS sequence assembly and analysis and algorithm designing.<br />Age limit : 35 years maximum (5 year relaxation for SC/ST and women candidates)<br />Emoluments:<br />JRF: 16,000 + 30% HRA<br />.<br />Res Assoc: Rs22,000 + 30% HRA<br />The post is purely temporary in nature and is co-terminus with the project. The appointment would be initially for one year and may be extended further upon satisfactory performance.<br />Interested candidates<br />should send the duly filled application forms (format in the following page ) so as to reach on or before 20.9.2014 along with all the relevant documents.</p>

<p>More at http://www.iari.res.in/files/JRF_RA-03092014-20140903-135319.pdf</p>
]]></description>
</item>

</channel>
</rss>