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    <title>Nature Precedings - Tag feed for genes</title>
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    <description>Recently posted documents tagged with 'genes'</description>
    <dc:publisher>Nature Publishing Group</dc:publisher>
    <dc:language>en</dc:language>
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      <title>Genes of the serotonergic and dopaminergic pathways and their interaction affect the expression of Behavioural and Psychological Symptoms in Dementia (BPSD).</title>
      <link>http://precedings.nature.com/documents/3896/version/1</link>
      <description>Although there is evidence for the involvement of genes of serotonergic and dopaminergic systems in the manifestation of the Behavioural and Psychological Symptoms in Dementia (BPSD), genetic association studies are contradictory. We used 1008 probable AD patients from the UK and applied a Multiple Indicators Multiple Causes (MIMIC) approach to investigate the effect of 11 polymorphisms in the serotonergic and dopaminergic systems, on four behavioural sub-phenotypes, namely &amp;quot;psychosis&amp;quot;,&amp;quot; moods&amp;quot;, &amp;quot;agitation&amp;quot; and &amp;quot;behavioural dyscontrol&amp;quot;, as well as on 12 NPI items. Significant findings included the association of DRD1 A48G with &amp;quot;psychosis&amp;quot; (p=0.037), the association of DAT1 VNTR with &amp;quot;agitation&amp;quot; (p=0.006) and the association of DRD4 with &amp;quot;moods&amp;quot; sub-phenotype (p=0.008). In addition, associations were identified between DRD1 A48G and DAT1 VNTR with aberrant motor behaviour (AMB) symptoms (p=0.001 and p=0.015 respectively), between DRD4 and sleep disturbances (p=0.018) and between 5HTTLPR and apathy (p=0.033). Finally, significant interactions were observed between COMT Val158Met and 5HTTLPR with &amp;quot;psychosis&amp;quot; (p=0.026), between HTTLPR and STin2 with &amp;quot;psychosis&amp;quot; (p=0.005), between DAT1 3&amp;apos;UTR VNTR and COMT Val158Met with &amp;quot;agitation&amp;quot; (p=0.0001) and between DAT1 3&amp;apos;UTR VNTR and 5HTTLPR with the &amp;quot;moods&amp;quot; factor (p=0.0027). The complexity of the interrelations between genetic variation, behavioural symptoms and clinical variables was efficiently captured by this MIMIC model.</description>
      <guid>http://precedings.nature.com/documents/3896/version/1</guid>
      <pubDate>Mon, 26 Oct 2009 17:32:00 UTC</pubDate>
      <dc:title>Genes of the serotonergic and dopaminergic pathways and their interaction affect the expression of Behavioural and Psychological Symptoms in Dementia (BPSD).</dc:title>
      <dc:identifier>hdl:10101/npre.2009.3896.1</dc:identifier>
      <dc:date>2009-10-26</dc:date>
      <dc:creator>Petroula Proitsi</dc:creator>
      <prism:publicationName>Nature Precedings</prism:publicationName>
      <prism:publicationDate>2009-10-26T17:32:00Z</prism:publicationDate>
      <prism:category>Manuscript</prism:category>
      <prism:section>Genetics &amp; Genomics</prism:section>
      <prism:section>Neuroscience</prism:section>
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      <title>Limusaurus and bird digit identity</title>
      <link>http://precedings.nature.com/documents/3828/version/1</link>
      <description>Limusaurus is a remarkable herbivorous ceratosaur unique among theropods in having digits II, III and IV, with only a small metacarpal vestige of digit I. This raises interesting questions regarding the controversial identity of avian wing digits. The early tetanuran ancestors of birds had tridactyl hands with digital morphologies corresponding to digits I, II &amp;#38; III of other dinosaurs. In bird embryos, however, the pattern of cartilage formation indicates that their digits develop from positions that become digits II, III, &amp;#38; IV in other amniotes. Limusaurus has been argued to provide evidence that the digits of tetanurans, currently considered to be I, II and III, may actually be digits II, III, &amp;#38; IV, thus explaining the embryological position of bird wing digits. However, morphology and gene expression of the anterior bird wing digit specifically resemble digit I, not II, of other amniotes. We argue that digit I loss in Limusaurus is derived and thus irrelevant to understanding the development of the bird wing.  </description>
      <guid>http://precedings.nature.com/documents/3828/version/1</guid>
      <pubDate>Tue, 06 Oct 2009 12:15:57 UTC</pubDate>
      <dc:title>Limusaurus and bird digit identity</dc:title>
      <dc:identifier>hdl:10101/npre.2009.3828.1</dc:identifier>
      <dc:date>2009-10-06</dc:date>
      <dc:creator>Alexander O. Vargas</dc:creator>
      <prism:publicationName>Nature Precedings</prism:publicationName>
      <prism:publicationDate>2009-10-06T12:15:57Z</prism:publicationDate>
      <prism:category>Manuscript</prism:category>
      <prism:section>Developmental Biology</prism:section>
      <prism:section>Genetics &amp; Genomics</prism:section>
      <prism:section>Molecular Cell Biology</prism:section>
      <prism:section>Evolutionary Biology</prism:section>
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      <title>Homocysteic acid as a pathogen for Alzheimer&amp;#8217;s disease</title>
      <link>http://dx.doi.org/10.1038/npre.2009.3739.1</link>
      <description>It has been considered that Alzheimer&#8217;s disease may be induced by multi-pathogenic factors.  However recent Nature Genetics has reported that sporadic Alzheimer&#8217;s disease is also genetically determined by such as ApoE4, Clusterin, so on. We already understand familiar Alzheimer&#8217;s disease is determined by such APP, Presenilin genes. These reports should allow us to consider that these genes stimulate the biological process and consequently Alzheimer&#8217;s disease would be determined by certain pathogen. Then what is the pathogen? First this pathogen should be stimulated by certain biological process by these genetic activation, which I mean that these genes separately work to induce this pathogen. I really propose that homocysteic acid (HA) is this pathogen. Now I am clarifying why HA is the pathogen from these genes&#8217; stimulation.</description>
      <guid>http://dx.doi.org/10.1038/npre.2009.3739.1</guid>
      <pubDate>Wed, 09 Sep 2009 10:33:05 UTC</pubDate>
      <dc:title>Homocysteic acid as a pathogen for Alzheimer&amp;#8217;s disease</dc:title>
      <dc:identifier>doi:10.1038/npre.2009.3739.1</dc:identifier>
      <dc:date>2009-09-09</dc:date>
      <dc:creator>Tohru Hasegawa</dc:creator>
      <prism:publicationName>Nature Precedings</prism:publicationName>
      <prism:publicationDate>2009-09-09T10:33:05Z</prism:publicationDate>
      <prism:category>Manuscript</prism:category>
      <prism:section>Neuroscience</prism:section>
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      <title>IMGT/GENE-DB: genomic reference sequences for human and mouse IG and TR genes and alleles</title>
      <link>http://dx.doi.org/10.1038/npre.2009.3158.1</link>
      <description>The immunoglobulin (IG) and T cell receptor (TR) major loci span about 6 Megabases (Mb) of the human genome on chromosomes 2, 7, 14 and 22, and 9 Mb in mouse on chromosomes 6, 12, 13, 14 and 16. There are seven major loci: three IG loci (IGH, IGK, IGL) and four TR loci (TRA, TRB, TRG, TRD), with a distinct repartition of the variable (V), diversity (D), joining (J) and constant (C) genes. The human genome comprises a total number of 608-665 IG and TR genes (371-422 IG and 237-243 TR), depending on the haplotypes, per haploid genome 1, 2 of which 531-588 genes are located in the major loci (distributed in 369-418 V, 32 D, 105-109 J and 25-29 C genes). There are also 77 orphons (68 IG and 9 TR) including two processed IG genes, outside the major loci. The number of functional IG and TR genes is 308-356 (136-171 IG and 172-185 TR) per haploid genome. The mouse genome comprises an approximate number of 876 IG and TR genes (624 IG and 252 TR). All these genomic data are available in the IMGT&#174; gene database, IMGT/GENE-DB 3. The major contribution of IMGT/GENE-DB has been to establish, for the first time, a standardized nomenclature of the IG and TR genes and alleles of humans and other vertebrates. In April 2009, IMGT/GENE-DB manages 1999 genes and 3026 alleles. [1] Lefranc M.-P. and Lefranc G., The Immunoglobulin FactsBook, Academic Press, London, 458 pages (2001).[2] Lefranc M.-P. and Lefranc G., The T cell receptor FactsBook, Academic Press, London, 398 pages (2001).[3] Giudicelli V. et al. Nucleic Acids Res., 33, D256-261 (2005).</description>
      <guid>http://dx.doi.org/10.1038/npre.2009.3158.1</guid>
      <pubDate>Thu, 23 Apr 2009 17:57:23 UTC</pubDate>
      <dc:title>IMGT/GENE-DB: genomic reference sequences for human and mouse IG and TR genes and alleles</dc:title>
      <dc:identifier>doi:10.1038/npre.2009.3158.1</dc:identifier>
      <dc:date>2009-04-23</dc:date>
      <dc:creator>Fatena Bellahcene</dc:creator>
      <prism:publicationName>Nature Precedings</prism:publicationName>
      <prism:publicationDate>2009-04-23T17:57:23Z</prism:publicationDate>
      <prism:category>Poster</prism:category>
      <prism:section>Genetics &amp; Genomics</prism:section>
      <prism:section>Immunology</prism:section>
      <prism:section>Bioinformatics</prism:section>
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      <title>The Gloomy Prospect Wins: Statistical Significance and Population Stratification in Genome Wide Association Studies</title>
      <link>http://dx.doi.org/10.1038/npre.2008.2642.1</link>
      <description>This one-hour lecture by Dr. Eric Turkheimer of  the University of Virginia&amp;#8217;s Department of Psychology explored the following:The contemporary era has seen a convergence of genomic technology and traditional social scientific concerns with complex human individual differences. Rather than finally turning social science into a replicable hard-scientific enterprise, genomics has gotten bogged down in the long-standing frustrations of social science. A recent report of an extensive genome wide association study of human height demonstrates the profound difficulties of explaining uncontrolled human variation at a genomic level. The statistical technologies that have been brought to bear on the problem of genomic association are simply modifications of similar methods that have been used by social scientists for decades, with little success. The motivation for the statistical methods in genomics is the same as it is in traditional social science: An attempt to discern linear causation in complex systems when experimental control is not possible.For an audio recording of Dr. Turkheimer&amp;#8217;s lecture, please visit http://cirge.stanford.edu/activities/events.html.</description>
      <guid>http://dx.doi.org/10.1038/npre.2008.2642.1</guid>
      <pubDate>Mon, 15 Dec 2008 17:02:39 UTC</pubDate>
      <dc:title>The Gloomy Prospect Wins: Statistical Significance and Population Stratification in Genome Wide Association Studies</dc:title>
      <dc:identifier>doi:10.1038/npre.2008.2642.1</dc:identifier>
      <dc:date>2008-12-15</dc:date>
      <dc:creator>Eric Turkheimer</dc:creator>
      <prism:publicationName>Nature Precedings</prism:publicationName>
      <prism:publicationDate>2008-12-15T17:02:39Z</prism:publicationDate>
      <prism:category>Presentation</prism:category>
      <prism:section>Genetics &amp; Genomics</prism:section>
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      <title>PharmGKB:  Capturing knowledge to catalyze pharmacogenomics research</title>
      <link>http://dx.doi.org/10.1038/npre.2006.8.1</link>
      <description>This is a powerpoint presentation made initially at the Cold Spring Harbor meeting on Pharmacogenomics, November 2006.  It discusses the PharmGKB (http://www.pharmgkb.org/) and how we are building a pipeline for annotation of knowledge.  In particular, we are focusing on pathway knowledge, &amp;#8220;Very important Pharmacogene&amp;#8221; annotations, and curation of the pharmacogenomics literature.  We are building an ontology-based system to capture and aggregate knowledge, for use by our curators.</description>
      <guid>http://dx.doi.org/10.1038/npre.2006.8.1</guid>
      <pubDate>Thu, 30 Nov 2006 02:33:52 UTC</pubDate>
      <dc:title>PharmGKB:  Capturing knowledge to catalyze pharmacogenomics research</dc:title>
      <dc:identifier>doi:10.1038/npre.2006.8.1</dc:identifier>
      <dc:date>2006-11-30</dc:date>
      <dc:creator>Russ B. Altman</dc:creator>
      <prism:publicationName>Nature Precedings</prism:publicationName>
      <prism:publicationDate>2006-11-30T02:33:52Z</prism:publicationDate>
      <prism:category>Presentation</prism:category>
      <prism:section>Biotechnology</prism:section>
      <prism:section>Genetics &amp; Genomics</prism:section>
      <prism:section>Pharmacology</prism:section>
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