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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44770?offset=30</link>
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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/bookmarks/view/28915/useful-bioinformatics-tools</guid>
	<pubDate>Mon, 29 Aug 2016 04:08:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28915/useful-bioinformatics-tools</link>
	<title><![CDATA[Useful Bioinformatics Tools]]></title>
	<description><![CDATA[<p>Collections of few handy tools for bioinformatician</p>
<p>http://molbiol-tools.ca/Convert.htm</p><p>Address of the bookmark: <a href="http://molbiol-tools.ca/Convert.htm" rel="nofollow">http://molbiol-tools.ca/Convert.htm</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43867/genomeqc-a-quality-assessment-tool-for-genome-assemblies-and-gene-structure-annotations</guid>
	<pubDate>Thu, 19 May 2022 04:29:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43867/genomeqc-a-quality-assessment-tool-for-genome-assemblies-and-gene-structure-annotations</link>
	<title><![CDATA[GenomeQC: a quality assessment tool for genome assemblies and gene structure annotations]]></title>
	<description><![CDATA[<p><span>The GenomeQC web application is implemented in R/Shiny version 1.5.9 and Python 3.6 and is freely available at&nbsp;</span><a href="https://genomeqc.maizegdb.org/">https://genomeqc.maizegdb.org/</a><span>&nbsp;under the GPL license. All source code and a containerized version of the GenomeQC pipeline is available in the GitHub repository&nbsp;</span><a href="https://github.com/HuffordLab/GenomeQC">https://github.com/HuffordLab/GenomeQC</a><span>.</span></p>
<p>https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-020-6568-2</p><p>Address of the bookmark: <a href="https://github.com/HuffordLab/GenomeQC" rel="nofollow">https://github.com/HuffordLab/GenomeQC</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34328/dfast-a-flexible-prokaryotic-genome-annotation-pipeline-for-faster-genome-publication</guid>
	<pubDate>Tue, 14 Nov 2017 10:26:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34328/dfast-a-flexible-prokaryotic-genome-annotation-pipeline-for-faster-genome-publication</link>
	<title><![CDATA[DFAST: a flexible prokaryotic genome annotation pipeline for faster genome publication]]></title>
	<description><![CDATA[<p>We developed a prokaryotic genome annotation pipeline, DFAST, that also supports genome submission to public sequence databases. DFAST was originally started as an on-line annotation server, and to date, over 7,000 jobs have been processed since its first launch in 2016. Here, we present a newly implemented background annotation engine for DFAST, which is also available as a standalone command-line program. The new engine can annotate a typical-sized bacterial genome within 10 minutes, with rich information such as pseudogenes, translation exceptions, and orthologous gene assignment between given reference genomes. In addition, the modular framework of DFAST allows users to customize the annotation workflow easily and will also facilitate extensions for new functions and incorporation of new tools in the future.</p>
<div>Availability and Implementation</div>
<p>The software is implemented in Python 3 and runs in both Python 2.7 and 3.4&ndash; on Macintosh and Linux systems. It is freely available at&nbsp;<a href="https://github.com/nigyta/dfast_core/" target="">https://github.com/nigyta/dfast_core/</a>&nbsp;under the GPLv3 license with external binaries bundled in the software distribution. An on-line version is also available at&nbsp;<a href="https://dfast.nig.ac.jp/" target="">https://dfast.nig.ac.jp/</a>.</p><p>Address of the bookmark: <a href="https://dfast.nig.ac.jp/" rel="nofollow">https://dfast.nig.ac.jp/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36954/mscaffolder-a-comparative-genome-scaffolding-tool</guid>
	<pubDate>Fri, 15 Jun 2018 04:48:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36954/mscaffolder-a-comparative-genome-scaffolding-tool</link>
	<title><![CDATA[mScaffolder: A comparative genome scaffolding tool]]></title>
	<description><![CDATA[<p>A comparative genome scaffolding tool based on MUMmer</p>
<p>mScaffolder scaffolds a genome using an existing high quality genome as the reference. It aligns the two genomes using nucmer utility from MUMmer and then orders and orients the contigs of the candidate genome guided by their alignments to the reference genome. Please send your questions and comments to&nbsp;<a href="mailto:mchakrab@uci.edu">mchakrab@uci.edu</a>.</p>
<p><span>Citation</span><span>&nbsp;</span><a href="https://www.nature.com/articles/s41588-017-0010-y">https://www.nature.com/articles/s41588-017-0010-y</a></p><p>Address of the bookmark: <a href="https://github.com/mahulchak/mscaffolder" rel="nofollow">https://github.com/mahulchak/mscaffolder</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41493/coronavirus-resources</guid>
	<pubDate>Wed, 25 Mar 2020 17:11:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41493/coronavirus-resources</link>
	<title><![CDATA[Coronavirus Resources !]]></title>
	<description><![CDATA[<p><span>2019nCoVR features comprehensive integration of genomic and proteomic sequences as well as their metadata information from the GISAID, NCBI, NMDC and CNCB/NGDC. It also incorporates a wide range of relevant information including scientific literatures, news, and popular articles for science dissemination, and provides visualization functionalities for genome variation analysis results based on all collected 2019-nCoV strains.</span></p>
<p><span>Annotation</span></p>
<p><span><a href="https://bigd.big.ac.cn/ncov/variation/annotation">https://bigd.big.ac.cn/ncov/variation/annotation</a></span></p>
<p><span>Genome wharehouse&nbsp;</span></p>
<p><span><a href="https://bigd.big.ac.cn/gwh/browse/index">https://bigd.big.ac.cn/gwh/browse/index</a></span></p>
<p>Released Genome</p>
<p><a href="https://bigd.big.ac.cn/ncov/release_genome">https://bigd.big.ac.cn/ncov/release_genome</a></p>
<p>Download data&nbsp;</p>
<p><a href="ftp://download.big.ac.cn/Genome/Viruses/Coronaviridae/">ftp://download.big.ac.cn/Genome/Viruses/Coronaviridae/</a></p>
<p>Raw data</p>
<p><a href="https://bigd.big.ac.cn/gsa/browse/run/?tag=Coronaviridae">https://bigd.big.ac.cn/gsa/browse/run/?tag=Coronaviridae</a></p><p>Address of the bookmark: <a href="https://bigd.big.ac.cn/ncov/about" rel="nofollow">https://bigd.big.ac.cn/ncov/about</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43791/comparative-genomics-visualisation-tools</guid>
	<pubDate>Thu, 17 Feb 2022 05:37:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43791/comparative-genomics-visualisation-tools</link>
	<title><![CDATA[Comparative genomics visualisation tools !]]></title>
	<description><![CDATA[<p>Comparative genomics visualisation tools !</p><p>Address of the bookmark: <a href="https://cmdcolin.github.io/awesome-genome-visualization/?latest=true&amp;selected=%23BRIG&amp;tag=Comparative" rel="nofollow">https://cmdcolin.github.io/awesome-genome-visualization/?latest=true&amp;selected=%23BRIG&amp;tag=Comparative</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45278/the-day-we-began-reading-the-dna-of-the-world</guid>
	<pubDate>Sat, 05 Sep 2026 01:43:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45278/the-day-we-began-reading-the-dna-of-the-world</link>
	<title><![CDATA[The Day We Began Reading the DNA of the World]]></title>
	<description><![CDATA[<div>Picture waking up and knowing that in one lab, a scientist is reading the DNA of a whale. In another, a team is sequencing a rare plant. Meanwhile, researchers in India are decoding the genomes of different human populations.</div><div>&nbsp;</div><div>Many organisms. Many countries. All share one remarkable goal: to understand the genetic story of life.</div><div>DNA is nature's instruction manual, written with just four letters: A, T, C, and G. For years, scientists could only read small sections of this huge book. Now, new sequencing technology lets us read entire genomes like never before.</div><div>&nbsp;</div><div>One of the most ambitious projects is the Earth BioGenome Project (EBP). Its goal is to create reference genomes for about 1.5 million known eukaryotic species. This project links genome research across continents, species, and scientific fields.</div><div>&nbsp;</div><div>But this story goes beyond just animals and plants.</div><div>&nbsp;</div><div><strong>A New Chapter in Human Genomics</strong></div><div>&nbsp;</div><div>Large human genome projects are changing how we understand our own genetic diversity.</div><div>India's GenomeIndia project has sequenced thousands of people from different populations. This work is uncovering genetic variation that global databases have often missed.</div><div>&nbsp;</div><div>Similar population-scale effSimilar large-scale projects are happening worldwide. The All of Us Research Program in the United States, Europe's 1+ Million Genomes initiative, South Korea's national genomic data program, and projects in Saudi Arabia, Australia, and Singapore are all building huge genomic resources.collect DNA.</div><div>&nbsp;</div><div>The real goal is to link genomes with health, disease, and other biological information. This creates a base for more accurate research and, in time, more personalized medicine.</div><div>&nbsp;</div><div><strong>A Race Against Time</strong></div><div>&nbsp;</div><div>There is also an important twist.</div><div>&nbsp;</div><div>We are sequencing Earth's biodiversity even as many species face growing environmental threats.</div><div>A genome alone cannot save a species, but it does keep important information about its biology, evolution, and genetic diversity. This knowledge helps scientists understand risks, guide conservation, and find traits that could help agriculture or medicine.</div><div>&nbsp;</div><div>Projects like the Darwin Tree of Life, which studies species in Britain and Ireland, and the African BioGenome Project, which is growing genomics work across Africa, are key parts of this worldwide effort.</div><div>&nbsp;</div><div>Projects to Watch</div><ol>
<li>Earth BioGenome Project (EBP) - A global effort to sequence and annotate roughly 1.5 million known eukaryotic species and create a comprehensive reference library of Earth's biodiversity.</li>
<li>Vertebrate Genomes Project (VGP) - Focuses on producing high-quality reference genomes for vertebrate species, providing a major foundation for the wider Tree of Life.</li>
<li>Darwin Tree of Life - A UK and Ireland initiative aiming to sequence approximately 70,000 species, creating a detailed genomic map of regional biodiversity.</li>
<li>African BioGenome Project (AfricaBP) - A pan-African initiative focused on sequencing Africa's biodiversity while strengthening genomics and bioinformatics capacity across the continent.</li>
<li>European Reference Genome Atlas (ERGA) - A European effort to generate high-quality reference genomes for Europe's biodiversity and connect national sequencing efforts.</li>
<li>Canada BioGenome Project - Building reference genomes for Canadian biodiversity, supporting conservation, research and the study of ecosystems.</li>
<li>California Conservation Genomics Project - Uses genomics to understand and protect California's biodiversity and help inform conservation decisions.</li>
<li>Bat1K - An ambitious global effort to sequence the genomes of all known bat species, helping scientists study their evolution, longevity, immunity and unique biology.</li>
<li>Bird 10,000 (B10K) - A global project aiming to create genome resources covering the world's bird diversity and reconstruct avian evolutionary history.</li>
<li>Global Invertebrate Genomics Alliance (GIGA) - Builds genomic resources for the enormous and genetically diverse world of invertebrates.</li>
<li>GenomeIndia - India's national human-genome initiative, designed to capture the country's extraordinary population diversity and create a reference resource for Indian genomics.</li>
<li>All of Us Research Program - A US national research program combining genomic information with health and lifestyle data at population scale.</li>
<li>1+ Million Genomes / Genome of Europe - A European effort to enable secure, cross-border use of genomic and health data and develop genome-scale resources involving more than one million people.</li>
<li>Korea National Integrated Bio Big Data Project - South Korea's large-scale national effort combining genomic and health information from a very large population cohort.</li>
<li>Saudi Genome Program - A national genomics initiative focused on genetic diseases, population genomics and precision medicine in Saudi Arabia.</li>
<li>Australian Genomics / Genomics Health Futures Mission - Australia's growing investment in genomic medicine, rare disease research and population-scale health genomics.</li>
</ol><div><strong>The Library of Life</strong></div><div>&nbsp;</div><div>The fuThe future of genomics is not just about sequencing one genome at a time. Now, it is about creating a worldwide network of genomes&mdash;human and non-human, individual and species&mdash;linked by powerful databases and advanced computational tools.ine a library without shelves.</div><div>&nbsp;</div><div>In this library, the books are genomes. The pages are made of DNA. Scientists and machines are the readers. And this library is still being written. Each genome sequenced today adds a new page to the story of life and helps us better understand our place in it.</div>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/26569/genome-stability-laboratory</guid>
  <pubDate>Mon, 07 Mar 2016 04:16:32 -0600</pubDate>
  <link></link>
  <title><![CDATA[Genome Stability Laboratory]]></title>
  <description><![CDATA[
<p>The bakers yeast, Saccharomyces cerevisiae is an ideal model organism to understand mechanisms of meiotic chromosome segregation. In S. cerevisiae and in mammals, the majority of meiotic crossovers are formed through a highly conserved MSH4p-MSH5p, MLH1p-MLH3p dependent pathway. We are interested in charactering the role of these complexes in crossover formation and distribution among all homolog pairs. Errors in this process are linked to congenital birth defects in humans such as Down's syndrome.Our laboratory is also interested in understanding the effect of genetic background on mutation rate variation using S. cerevisiae as a model. These studies are relevant for understanding cancer progression, genome evolution and architecture. We use high- throughput genomic methods as well as classical genetics to achieve these aims. </p>

<p>More at http://faculty.iisertvm.ac.in/~nishantkt/index.html</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37965/kobas-a-web-server-for-geneprotein-functional-annotation-and-functional-gene-set-enrichment</guid>
	<pubDate>Fri, 19 Oct 2018 09:36:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37965/kobas-a-web-server-for-geneprotein-functional-annotation-and-functional-gene-set-enrichment</link>
	<title><![CDATA[KOBAS: a web server for gene/protein functional annotation and functional gene set enrichment]]></title>
	<description><![CDATA[<p><span>KOBAS 3.0 is a web server for gene/protein functional annotation (</span><a href="http://kobas.cbi.pku.edu.cn/annotate.php">Annotate</a><span>&nbsp;module) and functional gene set enrichment(Enrichment module). For Annotate module, it accepts gene list as input, including IDs or sequences, and generates annotations for each gene based on multiple databases about pathways, diseases, and Gene Ontology. For Enrichment module, it can accept either gene list or gene expression data as input, and generates enriched gene sets, corresponding name, p-value or a probability of enrichment and enrichment score based on results of multiple methods.</span></p><p>Address of the bookmark: <a href="http://kobas.cbi.pku.edu.cn/" rel="nofollow">http://kobas.cbi.pku.edu.cn/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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