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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44783?offset=20</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43374/reference-sequence-resource</guid>
	<pubDate>Wed, 15 Sep 2021 21:15:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43374/reference-sequence-resource</link>
	<title><![CDATA[Reference Sequence Resource!]]></title>
	<description><![CDATA[<p><span>The ENCODE project uses Reference Genomes from&nbsp;</span><a href="http://www.ncbi.nlm.nih.gov/genome/browse/reference/">NCBI</a><span>&nbsp;or&nbsp;</span><a href="http://hgdownload.cse.ucsc.edu/downloads.html">UCSC</a><span>&nbsp;to provide a consistent framework for mapping high-throughput sequencing data.&nbsp;In general, ENCODE data are mapped consistently to 2 human (GRCH38, hg19) and 2 mouse (mm9/mm10) genomes for historical comparability.&nbsp;</span><em>Drosophia melanogaster</em><span>&nbsp;experiments are mapped to either dm3 or dm6 and&nbsp;</span><em>Caenorhabdilis elegans&nbsp;</em><span>experiments are mapped to ce10 or ce11.&nbsp;T</span></p><p>Address of the bookmark: <a href="https://www.encodeproject.org/data-standards/reference-sequences/" rel="nofollow">https://www.encodeproject.org/data-standards/reference-sequences/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44503/entire-human-genome-sequencing</guid>
	<pubDate>Tue, 02 Apr 2024 01:19:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44503/entire-human-genome-sequencing</link>
	<title><![CDATA[Entire Human Genome Sequencing !]]></title>
	<description><![CDATA[<p>Cost-effective whole human genome sequencing has revolutionized the landscape of genetic research and personalized medicine by making comprehensive genetic analysis accessible to a wider population. Through advancements in sequencing technologies, such as next-generation sequencing (NGS), costs have significantly decreased, enabling researchers and healthcare providers to analyze an individual's complete genetic makeup with greater efficiency and affordability. This has profound implications for disease diagnosis, prognosis, and treatment, as it allows for the identification of genetic predispositions and the customization of healthcare interventions based on an individual's unique genetic profile. Moreover, as the cost continues to decline, the potential for population-scale genomic studies and large-scale screening programs becomes increasingly feasible, promising to further enhance our understanding of human genetics and improve healthcare outcomes on a global scale.</p><p>Here are few companies:</p><p>https://mynucleus.com/</p><p>https://myome.com/</p><p>https://nebula.org/whole-genome-sequencing-dna-test/</p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/14011/dynamic-chromosome-breakpoints</guid>
	<pubDate>Wed, 13 Aug 2014 18:38:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/14011/dynamic-chromosome-breakpoints</link>
	<title><![CDATA[Dynamic chromosome breakpoints !!!]]></title>
	<description><![CDATA[<p>Cell division involves the distribution of identical genetic material, DNA, to two daughters&rsquo; cells. During this process, duplicated deoxyribonucleic acid (DNA) goes through a condensation and decondensation process. This is followed by nuclear envelope dissolution, mitotic spindle assembly, migration of the sister chromatid pairs to the metaphase plate, division and segregation of identical sets of chromosomes into daughter nuclei and nuclear envelope reformation.</p><p>The vital metaphase stage of cell division, when the sister chromatids migrated to the centre and lined up in a row, and pulled apart using attached microtubules in such a way that half the DNA ends up in each daughter cell. However, before the mitotic spindle‐mediated movement gets start and pulled DNA apart, the chromosomes are free to undergo <strong>recombination </strong>which involves the exchange of genetic material either between multiple chromosomes or between different regions of the same chromosome.</p><p><img src="http://www.sciencelearn.org.nz/var/sciencelearn/storage/images/contexts/uniquely-me/sci-media/images/chromosomes-crossing-over/464438-1-eng-NZ/Chromosomes-crossing-over.jpg" alt="image" width="504" height="342" style="border: 0px; border: 0px;"></p><p>During recombination, the precise breakage of each strand, exchange between the strands, and sealing of the resulting recombined molecules happens. The &ldquo;<strong>chromosomal breakpoints</strong>&rdquo; refers to these places where they break. Mostly, this process occurs with a high degree of accuracy at high frequency in both eukaryotic and prokaryotic cells. But occasionally this &ldquo;break and sealing/ break and reattach&rdquo; process goes wrong and the reattachment happens in the wrong place which usually create disaster (with few exceptions).These chromosome disaster or abnormalities involve the gain, loss or rearrangement of visible amounts of genetic material during cell division. These abnormalities are of two type, the first one is numerical abnormalities &nbsp;where severe disorders are caused by the loss or gain of whole chromosomes, which affect the copy number of hundreds or even thousands of genes. The second are structural abnormalities which can be unbalanced or balanced. The former are similar to numerical abnormalities in that genetic material is either gained or lost. The natural defects in chromosome segregation are linked to cancer and several genetic diseases (http://en.wikipedia.org/wiki/List_of_genetic_disorders). Therefore, the enzymes involved in regulating cell division are still the attractive drug targets for many diseases.</p><p>&nbsp;</p><p>&nbsp;</p><p><img src="http://upload.wikimedia.org/wikipedia/commons/4/4a/Chromosomal_translocations.svg" alt="image" width="424" height="331" style="border: 0px; border: 0px;"></p><p>&nbsp;</p><p>Apart from certain chromosome abnormalities, these &ldquo;crossing over&rdquo; of segments of maternal and paternal chromosomes to form hybrid chromosomes have some evolutionary importance and considered as a driver of genetic variation. Moreover, the chromosome breakage in evolution is considered to be non-random in nature(http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.0020014). In addition the study of breakpoint regions and non-breakpoint (stable) regions of chromosomes indicates both the regions evolved in distinctly different ways ( http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675965/). These breakage may lead to genetic diseases or participate to chromosomal rearranmgnets and contributed in development of new species.</p><p>I will try to explain the genome hotspots/Evolutionary Breakpoint Regions(EBRs)/fragile regions/weak fragments/&nbsp; in my next blog.</p><p><strong>Software for recombination detection:</strong></p><p><strong>RAT</strong> http://cbr.jic.ac.uk/dicks/software/RAT/</p><p><strong>Breakpointer</strong> https://github.com/ruping/Breakpointer</p><p><strong>DRP</strong> http://web.cbio.uct.ac.za/~darren/rdp.html</p><p><strong>RB-finder</strong> http://www.ncbi.nlm.nih.gov/pubmed/18707535</p><p><strong>LDhat2.0</strong> http://ldhat.sourceforge.net/LDhat2.0/instructions.shtml</p><p><strong>Reference:</strong></p><p>http://www.nature.com/scitable/topicpage/genetic-recombination-514#</p><p>Image: Wikipedia , sciencelearn.org.nz</p><p><strong>Recommended Articles:</strong></p><p>http://www.friendshipcircle.org/blog/2012/05/22/13-chromosomal-disorders-youve-never-heard-of/</p><p>http://web.udl.es/usuaris/e4650869/docencia/segoncicle/genclin98/recursos_classe_%28pdf%29/revisionsPDF/chromosyndromes.pdf</p><p>http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2775595/table/T2/</p><p>http://learn.genetics.utah.edu/content/disorders/chromosomal/</p><p>http://www.ncert.nic.in/html/learning_basket/biology/cc&amp;cd.pdf</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/19786/shrec3d</guid>
	<pubDate>Thu, 25 Dec 2014 23:14:52 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/19786/shrec3d</link>
	<title><![CDATA[ShRec3D]]></title>
	<description><![CDATA[<p><strong>ShRec3D</strong> is a program that aims at reconstructing a genome 3D structure (b) from the sole knowledge of the contacts between different genomic regions (a) as determined by Hi-C (http://www.ncbi.nlm.nih.gov/pubmed/19815776).</p>
<p>There are two options to run ShRec3D (on linuX only so far): the first one uses the Matlab complier runtime environment (MCR), the second one doesn't need any other library to be installed but only works with the latest versions of Linux (equivalent to Fedora 19 and above).</p><p>Address of the bookmark: <a href="https://sites.google.com/site/julienmozziconacci/#TOC-Downloads" rel="nofollow">https://sites.google.com/site/julienmozziconacci/#TOC-Downloads</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26573/efficient-genome-searching-with-biostrings-and-the-bsgenome-data-package</guid>
	<pubDate>Mon, 07 Mar 2016 05:18:06 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26573/efficient-genome-searching-with-biostrings-and-the-bsgenome-data-package</link>
	<title><![CDATA[Efficient genome searching with Biostrings and the BSgenome data package]]></title>
	<description><![CDATA[<p>Address of the bookmark: <a href="https://www.bioconductor.org/packages/3.3/bioc/vignettes/BSgenome/inst/doc/GenomeSearching.pdf" rel="nofollow">https://www.bioconductor.org/packages/3.3/bioc/vignettes/BSgenome/inst/doc/GenomeSearching.pdf</a></p>]]></description>
	<dc:creator>Aasha</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29282/cosmic</guid>
	<pubDate>Sat, 01 Oct 2016 15:04:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29282/cosmic</link>
	<title><![CDATA[COSMIC]]></title>
	<description><![CDATA[<p>The accurate description and annotation of structural variants can be complex. &nbsp;This is due to the different resolution that variants are reported from traditional&nbsp;cytogenetic coordinates down to the actual base pair positions. Furthermore, multiple&nbsp;rearrangements in a single area of the genome can make cataloguing and interpreting&nbsp;their effects challenging.&nbsp;</p>
<p>The Rearrangement Overview page describes the one or more breakpoints which make up a structural&nbsp;variant. A breakpoint is defined as a region or point where the sample sequence has altered&nbsp;from the reference sequence. Minimum interpretation is made of this data. One variant event&nbsp;can consist of one or multiple breakpoints. The Syntax (shown above the table) gives a detailed description of the variant and its location &nbsp;(e.g. chr11:g.36585230_76606619del, a deletion of&nbsp;roughly 40Mb on chromosome 11). Syntax is based on HGVS mutation nomenclature recommendations&nbsp;[http://www.hgvs.org/rec.html].&nbsp;</p>
<p>http://cancer.sanger.ac.uk/cosmic/help/rearrangement/overview</p><p>Address of the bookmark: <a href="http://cancer.sanger.ac.uk/cosmic/help/rearrangement/overview" rel="nofollow">http://cancer.sanger.ac.uk/cosmic/help/rearrangement/overview</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29683/method-in-comparative-genomics</guid>
	<pubDate>Wed, 09 Nov 2016 16:29:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29683/method-in-comparative-genomics</link>
	<title><![CDATA[Method in Comparative genomics !!]]></title>
	<description><![CDATA[<p>We present methods for the automatic determination of genome correspondence. The algorithms enabled the automatic identification of orthologs for more than 90% of genes and intergenic regions across the four species despite the large number of duplicated genes in the yeast genome. The remaining ambiguities in the gene correspondence revealed recent gene family expansions in regions of rapid genomic change.</p>
<p>We present methods for the identification of protein-coding genes based on their patterns of nucleotide conservation across related species. We observed the pressure to conserve the reading frame of functional proteins and developed a test for gene identification with high sensitivity and specificity. We used this test to revisit the genome of S. cerevisiae, reducing the overall gene count by 500 genes (10% of previously annotated genes) and refining the gene structure of hundreds of genes. We present novel methods for the systematic de novo identification of regulatory motifs. The methods do not rely on previous knowledge of gene function and in that way differ from the current literature on computational motif discovery. Based on the genome-wide conservation patterns of known motifs, we developed three conservation criteria that we used to discover novel motifs. We used an enumeration approach to select strongly conserved motif cores, which we extended and collapsed into a small number of candidate regulatory motifs. These include most previously known regulatory motifs as well as several noteworthy novel motifs. The majority of discovered motifs are enriched in functionally related genes, allowing us to infer a candidate function for novel motifs.</p>
<p>Our results demonstrate the power of comparative genomics to further our understanding of any species. Our methods are validated by the extensive experimental knowledge in yeast, and will be invaluable in the study of complex genomes like that of human.</p><p>Address of the bookmark: <a href="http://web.mit.edu/manoli/www/publications/Kellis_JCB_04.pdf" rel="nofollow">http://web.mit.edu/manoli/www/publications/Kellis_JCB_04.pdf</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31018/j-circos</guid>
	<pubDate>Fri, 17 Feb 2017 09:06:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31018/j-circos</link>
	<title><![CDATA[J-Circos]]></title>
	<description><![CDATA[<p>Circos plot tool (J-Circos) that is an interactive visualization tool that can plot Circos figures, as well as being able to dynamically add data to the figure, and providing information for specific data points using mouse hover display and zoom in/out functions. J-Circos uses the Java computer language to enable it to be used on most operating systems (Windows, MacOS, Linux). Users can input data into J-Circos using flat data formats, as well as from the GUI. J-Circos will enable biologists to better study more complex chromosomal interactions and fusion transcripts that are otherwise difficult to visualize from next-generation sequencing data.</p><p>Address of the bookmark: <a href="http://www.australianprostatecentre.org/research/software/jcircos" rel="nofollow">http://www.australianprostatecentre.org/research/software/jcircos</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26179/alignment-of-closely-related-whole-genomesscaffolds</guid>
	<pubDate>Fri, 29 Jan 2016 10:37:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26179/alignment-of-closely-related-whole-genomesscaffolds</link>
	<title><![CDATA[Alignment of closely related whole genomes/scaffolds]]></title>
	<description><![CDATA[<p>With the relative ease and low cost of current generation sequencing technologies has led to a dramatic increase in the number of sequenced genomes for species across the tree of life. This increasing volume of data requires tools that can quickly compare multiple whole-genome sequences, millions of base pairs in length, to aid in the study of populations, pan-genomes, and genome evolution.This bookmaks have been created to report new tools for whole genome alignments.</p>
<p>Please report new whole genome alignment tools under comment sections.</p><p>Address of the bookmark: <a href="http://www.cs.utoronto.ca/~brudno/721.full.pdf" rel="nofollow">http://www.cs.utoronto.ca/~brudno/721.full.pdf</a></p>]]></description>
	<dc:creator>Rahul Nayak</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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