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Alkuraya",{"url":1424,"publisher":1680,"properties":1693},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1681,"slug":10,"properties":1682,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":1685,"manageAffiliations":1686,"indexDatabases":1687,"url":20,"thumbnailPath":20,"statistic":1688,"gsStatistic":20,"type":83,"analyzePriority":20},[],{"issn":1683,"title":1684},{"VOID":13},{"EN":15},[],[],[],{"impactFactor":21,"impactFactorByYear":1689,"i10Index":33,"i10IndexLast5Year":21,"totalPublication":34,"totalPublicationByYear":1690,"totalCitation":50,"totalCitationByYear":1691,"totalCitationPerPublication":65,"totalCitationPerPublicationByYear":1692,"hindexLast5Year":82,"hindex":82},{"2012":27,"2013":28,"2014":29,"2015":30,"2016":31,"2017":32},{"2000":36,"2001":36,"2002":37,"2003":38,"2004":39,"2005":40,"2006":41,"2007":42,"2008":43,"2009":44,"2010":43,"2011":45,"2012":46,"2013":47,"2014":48,"2015":49},{"2000":52,"2001":53,"2002":54,"2003":54,"2004":53,"2005":41,"2006":55,"2007":56,"2008":57,"2009":58,"2010":59,"2011":60,"2012":61,"2013":62,"2014":63,"2015":64},{"2000":67,"2001":68,"2002":69,"2003":70,"2004":71,"2005":72,"2006":55,"2007":73,"2008":74,"2009":75,"2010":76,"2011":77,"2012":78,"2013":79,"2014":80,"2015":81},{"pages":1694,"volume":1696},{"VOID":1695},"1-7",{"VOID":1029},{"total":21,"publishYear":1031,"statisticByYear":1698},{},"2015-06-03",[],[1702,1708,1714,1717,1723,1726,1729,1732,1735,1738,1741,1744,1747,1753,1757,1760,1763,1766,1772,1775,1778,1781,1787,1790,1793,1796,1800,1804,1808,1814],{"id":1703,"text":1704,"url":1705,"identifiers":1706},"8004ad65-a26e-4f45-9836-0b2ff66f5a87","Alkuraya FS. Human knockout research: new horizons and opportunities. Trends Genet. 2015;31:108–15.","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0168952514001930",{"doi":1707},"10.1016\u002Fj.tig.2014.11.003",{"id":1709,"text":1710,"url":1711,"identifiers":1712},"4c68646b-0035-4279-8000-0006b275d4fa","Giaever G, Chu AM, Ni L, Connelly C, Riles L, Véronneau S, et al. Functional profiling of the Saccharomyces cerevisiae genome. Nature. 2002;418:387–91.","https:\u002F\u002Flink.springer.com\u002F10.1007\u002Fs10440-022-00541-7",{"doi":1713},"10.1007\u002Fs10440-022-00541-7",{"id":1709,"text":1715,"url":1711,"identifiers":1716},"Ayadi A, Birling M-C, Bottomley J, Bussell J, Fuchs H, Fray M, et al. Mouse large-scale phenotyping initiatives: Overview of the European Mouse Disease Clinic (EUMODIC) and of the Wellcome Trust Sanger Institute Mouse Genetics Project. 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Human UBN1 is an ortholog of yeast Hpc2p and has an essential role in the HIRA\u002FASF1a chromatin-remodeling pathway in senescent cells. Mol Cell Biol. 2009;29:758–70.",{"doi":1713},{"id":1709,"text":1776,"url":1711,"identifiers":1777},"Tang Y, Puri A, Ricketts MD, Rai TS, Hoffmann J, Hoi E, et al. Identification of an ubinuclein 1 region required for stability and function of the human HIRA\u002FUBN1\u002FCABIN1\u002FASF1a histone H3. 3 chaperone complex. Biochemistry. 2012;51:2366–77.",{"doi":1713},{"id":1709,"text":1779,"url":1711,"identifiers":1780},"Roberts C, Sutherland HF, Farmer H, Kimber W, Halford S, Carey A, et al. Targeted mutagenesis of the Hira gene results in gastrulation defects and patterning abnormalities of mesoendodermal derivatives prior to early embryonic lethality. Mol Cell Biol. 2002;22:2318–28.",{"doi":1713},{"id":1782,"text":1783,"url":1784,"identifiers":1785},"8bd226fb-54a4-4181-963f-242db05a7cdd","Hein S, Schaper J. Weakness of a giant: mutations of the sarcomeric protein titin. Trends Mol Med. 2002;8:311–3.","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS1471491402023729",{"doi":1786},"10.1016\u002Fs1471-4914(02)02372-9",{"id":1709,"text":1788,"url":1711,"identifiers":1789},"Gotthardt M, Hammer RE, Hübner N, Monti J, Witt CC, McNabb M, et al. Conditional expression of mutant M-line titins results in cardiomyopathy with altered sarcomere structure. J Biol Chem. 2003;278:6059–65.",{"doi":1713},{"id":1709,"text":1791,"url":1711,"identifiers":1792},"Alkuraya FS. Discovery of rare homozygous mutations from studies of consanguineous pedigrees. Curr Protoc Hum Genet. 2012:61211–16.12. 13.",{"doi":1713},{"id":1709,"text":1794,"url":1711,"identifiers":1795},"Carr IM, Flintoff KJ, Taylor GR, Markham AF, Bonthron DT. Interactive visual analysis of SNP data for rapid autozygosity mapping in consanguineous families. Hum Mutat. 2006;27:1041–6.",{"doi":1713},{"id":20,"text":1797,"url":1798,"identifiers":1799},"UCSC Genome Browser. http:\u002F\u002Fgenome.ucsc.edu\u002F.","http:\u002F\u002Fgenome.ucsc.edu\u002F",{},{"id":20,"text":1801,"url":1802,"identifiers":1803},"Burrows-Wheeler Aligner. http:\u002F\u002Fbio-bwa.sourceforge.net\u002F.","http:\u002F\u002Fbio-bwa.sourceforge.net\u002F",{},{"id":20,"text":1805,"url":1806,"identifiers":1807},"SAM (Sequence Alignment\u002FMap) Tools. http:\u002F\u002Fsamtools.sourceforge.net\u002F.","http:\u002F\u002Fsamtools.sourceforge.net\u002F",{},{"id":1809,"text":1810,"url":1811,"identifiers":1812},"50e4058d-193b-4574-857b-e1d265f08a05","Alkuraya FS. The application of next-generation sequencing in the autozygosity mapping of human recessive diseases. Hum Genet. 2013;132:1197–211.","http:\u002F\u002Flink.springer.com\u002F10.1007\u002Fs00439-013-1344-x",{"doi":1813},"10.1007\u002Fs00439-013-1344-x",{"id":20,"text":1815,"url":1816,"identifiers":1817},"TraBioS Data Warehouse. http:\u002F\u002Fshgp.kfshrc.edu.sa\u002Fbioinf\u002Fdb\u002Fvariants\u002Fdg\u002Fdetails.html.","http:\u002F\u002Fshgp.kfshrc.edu.sa\u002Fbioinf\u002Fdb\u002Fvariants\u002Fdg\u002Fdetails.html",{},{"id":1819,"createTime":1820,"updateTime":1821,"relativeEntities":1822,"slug":1823,"properties":1824,"entityType":108,"verifyStatus":109,"verifyTime":1834,"verifyNote":110,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":1835,"fullTextUrl":20,"authors":1836,"publicationType":136,"publisherRelationship":1885,"citationCount":20,"citationInfo":20,"publishDate":1903,"publishYear":1031,"citationAnalyzeStatus":1092,"lastCitationAnalyze":1904,"indexDatabases":1905,"openAccess":20,"references":20,"isForceReanalyzing":414},"326b020e-fbaf-4a10-80db-dffe7b8bccf3","2023-12-27T06:41:59.048+00:00","2026-03-12T11:12:10.636+00:00",[],"MUSiCC-a-marker-genes-based-framework-for-metagenomic-normalization-and-accurate-profiling-of-gene-abundances-in-the-microbiome",{"abstract":1825,"title":1827,"gsPaper":1829,"references":1830,"doi":1832},{"EN":1826},"Functional metagenomic analyses commonly involve a normalization step, where measured levels of genes or pathways are converted into relative abundances. Here, we demonstrate that this normalization scheme introduces marked biases both across and within human microbiome samples, and identify sample- and gene-specific properties that contribute to these biases. We introduce an alternative normalization paradigm, MUSiCC, which combines universal single-copy genes with machine learning methods to correct these biases and to obtain an accurate and biologically meaningful measure of gene abundances. Finally, we demonstrate that MUSiCC significantly improves downstream discovery of functional shifts in the microbiome. MUSiCC is available at \n                  http:\u002F\u002Felbo.gs.washington.edu\u002Fsoftware.html\n                  \n                .",{"EN":1828},"MUSiCC: a marker genes based framework for metagenomic normalization and accurate profiling of gene abundances in the microbiome",{"VOID":1050},{"VOID":1831},"Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. 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