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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/879?offset=60</link>
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	<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>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/856/papenfuss-lab</guid>
  <pubDate>Sun, 14 Jul 2013 12:22:28 -0500</pubDate>
  <link></link>
  <title><![CDATA[Papenfuss Lab]]></title>
  <description><![CDATA[
<p>The human genome project and similar projects in disease-causing organisms such as Plasmodium falciparum, which causes malaria in humans, have provided new tools for discovery in biology and have accelerated the development of understanding in human disease.</p>

<p>Research Area: <br />Analysis of Next Generation sequence data in cancer<br />Methods for analysis of structural variation in cancer genomes<br />Next Generation sequencing in malaria<br />Computational comparative genomics<br />Sensitive genomic sequence search techniques using hidden Markov models<br />Tasmanian devil facial tumour disease</p>

<p>Link @ http://www.wehi.edu.au/faculty_members/dr_tony_papenfuss</p>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/869/bioinformatics-phd-studentship-available-in-new-zealand</guid>
  <pubDate>Sun, 14 Jul 2013 13:36:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics PhD studentship available in New Zealand]]></title>
  <description><![CDATA[
<p>Bioinformatics PhD studentship available in New Zealand</p>

<p>The importance of transcriptional control has been explored in a burgeoning line of research over several decades; nevertheless, we are still far from having a complete picture of the regulatory mechanisms of genes and non-coding RNAs, and their influences on different phenotypes and disease states of a cell. Recent shifts towards large-scale analyses of transcriptional regulation on a sequence and epigenetic level are at the forefront of research, mainly due to sequencing technology advancements and a deeper understanding of the fundamental regulatory processes involved.</p>

<p>Arriving at a better understanding of the influence of specific parts of the overall regulatory machinery on disease states is a high priority of the group’s research agenda.</p>

<p>We are seeking an enthusiastic student to join the group as a PhD student. Applicants must have a BSc(Hons) or MSc degree in a relevant discipline and a willingness to learn and apply new techniques and work in a team. Both local and international students are encouraged to apply.</p>

<p>The studentship covers all university fees and an annual tax-exempt stipend of NZ$22,000 for three years.</p>

<p>Sebastian Schmeier recently joined Massey University and started his own research group in Auckland, New Zealand, a city regularly ranked one of the most livable in the world. This is your chance to experience the amazing Auckland lifestyle and the excitement of joining a young new science team, while staying connected to world class scientific networks.</p>

<p>To apply for the post, please send a cover letter stating your interest in the position and why you think you would be a good candidate, a Curriculum Vitae, a copy of your academic transcript, a sample of your written scientific work, and the names of three referees. Applications will be accepted until the position is filled.</p>

<p>Enquiries and applications to Sebastian Schmeier (s.schmeier@massey.ac.nz).</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/1161/genomics-for-bioinformatician</guid>
	<pubDate>Sat, 20 Jul 2013 07:03:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/1161/genomics-for-bioinformatician</link>
	<title><![CDATA[Genomics for Bioinformatician]]></title>
	<description><![CDATA[<p>Genomics is the study of the genomes of organisms. The field includes intensive efforts to determine the entire DNA sequence of organisms and fine-scale genetic mapping efforts. The field also includes studies of intragenomic phenomena such as heterosis, epistasis, pleiotropy and other interactions between loci and alleles within the genome. In contrast, the investigation of the roles and functions of single genes is a primary focus of molecular biology or genetics and is a common topic of modern medical and biological research. Research of single genes does not fall into the definition of genomics unless the aim of this genetic, pathway, and functional information analysis is to elucidate its effect on, place in, and response to the entire genome's networks.<br /><br />Genomics was established by Fred Sanger when he first sequenced the complete genomes of a virus and a mitochondrion. His group established techniques of sequencing, genome mapping, data storage, and bioinformatic analyses in the 1970-1980s. A major branch of genomics is still concerned with sequencing the genomes of various organisms, but the knowledge of full genomes has created the possibility for the field of functional genomics, mainly concerned with patterns of gene expression during various conditions. The most important tools here are microarrays and bioinformatics. Study of the full set of proteins in a cell type or tissue, and the changes during various conditions, is called proteomics. A related concept is materiomics, which is defined as the study of the material properties of biological materials (e.g. hierarchical protein structures and materials, mineralized biological tissues, etc.) and their effect on the macroscopic function and failure in their biological context, linking processes, structure and properties at multiple scales through a materials science approach. The actual term 'genomics' is thought to have been coined by Dr. Tom Roderick, a geneticist at the Jackson Laboratory (Bar Harbor, ME) over beer at a meeting held in Maryland on the mapping of the human genome in 1986.<br /><br />The outcome of almost two years of intense discussions with literally hundreds of scientists and members of the public, has three major areas of focus: Genomics to Biology, Genomics to Health, and Genomics to Society.<br /><br /><strong><em>Genomics to Biology:</em></strong>&nbsp;<br />The human genome sequence provides foundational information that now will allow development of a comprehensive catalog of all of the genome's components, determination of the function of all human genes, and deciphering of how genes and proteins work together in pathways and networks.<br /><br /><strong><em>Genomics to Health:<br /></em></strong>Completion of the human genome sequence offers a unique opportunity to understand the role of genetic factors in health and disease, and to apply that understanding rapidly to prevention, diagnosis, and treatment. This opportunity will be realized through such genomics-based approaches as identification of genes and pathways and determining how they interact with environmental factors in health and disease, more precise prediction of disease susceptibility and drug response, early detection of illness, and development of entirely new therapeutic approaches.<br /><br /><strong><em>Genomics to Society:</em>&nbsp;<br /></strong>Just as the HGP has spawned new areas of research in basic biology and in health, it has created new opportunities in exploring the ethical, legal, and social implications (ELSI) of such work. These include defining policy options regarding the use of genomic information in both medical and non-medical settings and analysis of the impact of genomics on such concepts as race, ethnicity, kinship, individual and group identity, health, disease, and "normality" for traits and behaviors.<br /><br />This vision for the future of genomics is not just about the NHGRI. It encompasses the whole field of genomics, including the work of all the other Institutes and Centers at the NIH and of a number of other federal agencies. All of the NIH Institutes are already taking full advantage of the sequence and will apply its data to the better understanding of both rare and common diseases, almost all of which have a genetic component. A recent example of the way that the HGP and the knowledge and new technologies it has spawned are already facilitating science is the extremely rapid sequencing by groups in Canada and at the Centers for Disease Control and Prevention (CDC) in Atlanta of the genome of the virus that causes Severe Acute Respiratory Syndrome (SARS). The sequencing of the SARS virus genome provides insight into this new and deadly disease at a speed never before possible in science. In turn, this should lead to the rapid development of diagnostic tests and, in time, vaccines and effective treatments.<br /><br /><strong>Links for the addition material available on Net</strong></p><p><a href="http://pevsnerlab.kennedykrieger.org/bioinformatics/bioinf10_genomes.htm">Genomes and genomics:</a></p><p><a href="http://www.123genomics.com/learning.html">Bioinformatics and Genomics:</a></p><p><a href="http://www.ebi.ac.uk/pdbe/docs/roadshow_tutorial/strgenomics/tutorial.html">Structural genomics tutorial:</a></p><p><a href="http://www.hgu.mrc.ac.uk/Users/Philippe.Gautier/tutorial/index.html">Comparative Genomics Tutorial:</a></p><p><a href="http://www.scfbio-iitd.res.in/tutorial/genomics.html">GENOME TUTORIAL:</a></p><p><a href="http://genomebiology.com/content/pdf/gb-2001-3-1-reviews2001.pdf">Tools and resources for identifying protein families, domains and motifs</a></p><p><a href="http://www.ornl.gov/sci/techresources/Human_Genome/posters/chromosome/tools.shtml">Bioinformatics Tools</a><a href="http://www.ornl.gov/sci/techresources/Human_Genome/posters/chromosome/tools.shtml">&nbsp;<br />Tips, Tutorials, and Terminology for Using Selected Resources in Genome Database Guide:</a></p><p><a href="http://www.doe-mbi.ucla.edu/Reprints/R31%20Strong%20A%20Web-based%20Comparative%20Genomics%20tutorial%20Microbiology%20Eduction%202004.pdf">A Web-Based Comparative Genomics Tutorial for Investigating Microbial Genomes:</a></p><p><a href="http://www.genome.gov/27530225">Free Online Tutorials Teach Anyone How to Use Genome Databases:</a></p><p><a href="http://mkweb.bcgsc.ca/circos/?tutorials">Circos to create concise, explanatory, unique and print-ready visualizations of your data:</a></p><p><a href="http://www.igd.cornell.edu/Comparative%20Genomics/Comparative%20Genomics%20Proj.html">Genomics and Comparative Genomics</a><a href="http://www.igd.cornell.edu/Comparative%20Genomics/Comparative%20Genomics%20Proj.html">&nbsp;Learning Module:</a></p><p><a href="http://psb.stanford.edu/psb10/conference-materials/tutorials/compgen-notes.pdf">Computational Challenges in Comparative Genomics</a></p><p><a href="http://psb.stanford.edu/psb10/conference-materials/tutorials/compgen-notes.pdf">A Tutorial:</a></p><p><a href="http://gramene.agrinome.org/tutorials/modules_tutorial.pdf">A Comparative Genomics Resource for Grains</a>:</p><p><a href="http://www.plantcell.org/cgi/content/full/21/12/3718">PLAZA: A Comparative Genomics Resource to Study Gene and Genome Evolution in Plants:</a></p><p><a href="http://en.wikipedia.org/wiki/VISTA_(comparative_genomics)">VISTA</a><a href="http://en.wikipedia.org/wiki/VISTA_(comparative_genomics)">:</a></p><p>Software for Genomics</p><ol>
<li><strong>Artemis</strong>&nbsp;Artemis is a free genome viewer and annotation tool that allows visualization of sequence features and the results of analyses within the context of the sequence, and its six-frame translation.</li>
<li><strong>Chromas&nbsp;</strong>It will display and prints chromatogram files from ABI automated DNA sequencers, and Staden SCF files which the analysis programs for ALF, Li-Cor and Visible Genetics OpenGene sequencers can create.</li>
<li><strong>Glimmer</strong>&nbsp;A system for finding genes in microbial DNA, especially the genomes of bacteria and archaea.Glimmer (Gene Locator and Interpolated Markov Modeler) uses interpolated Markov models (IMMs) to identify the coding regions and distinguish them from noncoding DN</li>
<li><strong>Glimmer</strong>&nbsp;HMM&nbsp;A fast and accurate gene finder based on a GHMM architecture, developed specifically for eukaryotes. It incorporates splice site models adapted from the GeneSplicer program and uses interpolated Markov models for evaluating the coding regions.</li>
<li><strong>Glimmer</strong>&nbsp;M&nbsp;A gene finder derived from Glimmer, but developed specifically for eukaryotes. It is based on a dynamic programming algorithm that considers all combinations of possible exons for inclusion in a gene model and chooses the best of these combinations. The d</li>
<li><strong>MUMmer</strong>&nbsp;MUMmer is a system for rapidly aligning entire genomes, whether in complete or draft form.</li>
<li><strong>pDRAW</strong>&nbsp;pDRAW32 is being developed as a free time hobby project. It is far from finished, but as it has reached a point where it could be helpful for many labs, it is now available to the scientific community.</li>
<li><strong>Sequin</strong>&nbsp;Sequin is a stand-alone software tool developed by the NCBI for submitting and updating entries to the GenBank, EMBL, or DDBJ sequence databases. It is capable of handling simple submissions that contain a single short mRNA sequence, and complex submissio</li>
<li><strong>Staden&nbsp;</strong>The Staden Package consists of a series of tools for DNA sequence preparation (pregap4), assembly (gap4), editing (gap4) and DNA/protein sequence analysis (spin).</li>
</ol><p>For more software @&nbsp;<a href="http://bioinformaticsonline.com/bookmarks/view/926/list-of-popular-bioinformatics-softwaretools">http://bioinformaticsonline.com/bookmarks/view/926/list-of-popular-bioinformatics-softwaretools</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/4003/personalised-medicine-animation</guid>
	<pubDate>Tue, 27 Aug 2013 10:07:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/4003/personalised-medicine-animation</link>
	<title><![CDATA[Personalised Medicine - Animation]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/fEY3Khsmuak" frameborder="0" allowfullscreen></iframe>Two animated case scenarios set now and in the future. These highlight potential differences in the way patients are treated now, and how they might be treated as healthcare becomes more tailored.]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/1515/list-of-pharmacogenomics-companies-in-india</guid>
	<pubDate>Fri, 09 Aug 2013 13:26:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/1515/list-of-pharmacogenomics-companies-in-india</link>
	<title><![CDATA[List of pharmacogenomics companies in India]]></title>
	<description><![CDATA[<p>pharmacogenomics companies in India are making their good impacts. Here is the list of few pharmacogenomics companies. Please add more if not mentioned here.</p><p>Genomics in India <br /><a href="http://www.ganitlabs.in/">www.ganitlabs.in</a> <br /><a href="http://www.sandor.co.in/">www.sandor.co.in</a> <br /><a href="http://www.igib.res.in/">www.igib.res.in</a> <br /><a href="http://www.genotypic.co.in/">www.genotypic.co.in</a> <br /><a href="http://www.ocimumbio.com/">www.ocimumbio.com</a> <br /><a href="http://www.abcgenomics.com/">www.abcgenomics.com</a> <br /><a href="http://www.xcelrisgenomics.com/">www.xcelrisgenomics.com</a> <br /><a href="http://www.ayugen.com/">www.ayugen.com</a> <br /><a href="http://www.geneombiotech.com/">www.geneombiotech.com</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/2002/ibl-laboratory</guid>
  <pubDate>Mon, 12 Aug 2013 02:02:29 -0500</pubDate>
  <link></link>
  <title><![CDATA[IBL laboratory]]></title>
  <description><![CDATA[
<p>The IBL laboratory focuses on the multi-disciplinary analyses of the global responses of model microorganisms, cyanobacteria (mainly Synechocystis PCC6803) and yeasts (mainly Saccharomyces cerevisae) to environmental stresses triggered by oxidative agents, heavy metals, or drastic changes in nutrients availability. The genome-wide responses studied with the "omics" techniques (transcriptomics, proteomics, metabolomics and genetics) generate a wealth of experimental data, which are processed, archived, integrated and represented as working models through bioinformatics and mathematics. </p>

<p>Link : http://www-dsv.cea.fr/en/instituts/institut-de-biologie-et-de-technologies-de-saclay-ibitec-s/unites-de-recherche/service-de-biologie-integrative-et-genetique-moleculaire-sbigem/laboratoire-de-biologie-integrative-lbi/presentation__1</p>
]]></description>
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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/videolist/watch/3918/the-human-genome-project-video-3d-animation-introduction-low</guid>
	<pubDate>Sat, 24 Aug 2013 19:01:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/3918/the-human-genome-project-video-3d-animation-introduction-low</link>
	<title><![CDATA[The Human Genome Project Video   3D Animation Introduction Low)]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/YxoQFSBwyms" frameborder="0" allowfullscreen></iframe>]]></description>
	
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/4653/human-genome-meeting-2014-geneva-switzerland</guid>
  <pubDate>Fri, 20 Sep 2013 12:36:44 -0500</pubDate>
  <link></link>
  <title><![CDATA[Human Genome Meeting 2014, Geneva, Switzerland]]></title>
  <description><![CDATA[
<p>The spectacular advances of the last few years resulted in the rapid analysis of the genome sequence of each individual. The biomedical world is now faced with the enormous challenges of assigning pathogenicity to each genomic variant, the functional analysis of the genome of each individual, and the accurate and detailed phenotypic characterization. Advances in these challenges are likely to fundamentally change the medical practice in a global scale.</p>

<p>This 2014 HUGO Meeting in Geneva will be a Forum for discussions on innovative approaches, and proposals to tackle the anticipated challenges.</p>

<p>Time : 27 April 2014 - 30 April 2014 </p>

<p>For enquiries, please email hugo2014@mci-group.com or visit www.hugo-international.org</p>

<p>More at http://www.hgm2014-geneva.org/</p>
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