Search: onr:"20721027" > Combinatorial ident...
Fältnamn | Indikatorer | Metadata |
---|---|---|
000 | 03487naa a22005533a 4500 | |
001 | 20721027 | |
003 | SE-LIBR | |
005 | 20170425151719.0 | |
007 | cr|||||||||||| | |
008 | 170425s2016 sw |||| o |||| ||eng c | |
024 | 7 | a http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-3053302 uri |
024 | 7 | a urn:nbn:se:uu:diva-3053302 urn |
024 | 7 | a 10.1186/s12859-016-1259-32 doi |
040 | a S | |
041 | 0 | a eng |
042 | 9 EPLK | |
100 | 1 | a Moghadam, Behrooz Torabi4 aut |
245 | 1 0 | a Combinatorial identification of DNA methylation patterns over age in the human brainh [Elektronisk resurs] |
260 | c 2016 | |
500 | a Published | |
500 | a Forskningsrådet Formas | |
500 | a eSSENCE - An eScience Collaboration | |
506 | 0 | a gratis |
520 | a Background: DNA methylation plays a key role in developmental processes, which is reflected in changing methylation patterns at specific CpG sites over the lifetime of an individual. The underlying mechanisms are complex and possibly affect multiple genes or entire pathways. Results: We applied a multivariate approach to identify combinations of CpG sites that undergo modifications when transitioning between developmental stages. Monte Carlo feature selection produced a list of ranked and statistically significant CpG sites, while rule-based models allowed for identifying particular methylation changes in these sites. Our rule-based classifier reports combinations of CpG sites, together with changes in their methylation status in the form of easy-to-read IF-THEN rules, which allows for identification of the genes associated with the underlying sites. Conclusion: We utilized machine learning and statistical methods to discretize decision class (age) values to get a general pattern of methylation changes over the lifespan. The CpG sites present in the significant rules were annotated to genes involved in brain formation, general development, as well as genes linked to cancer and Alzheimer's disease. | |
650 | 7 | a Medical and Health Sciences2 hsv |
650 | 7 | a Medical Biotechnology2 hsv |
650 | 7 | a Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)2 hsv |
650 | 7 | a Medicin och hälsovetenskap2 hsv |
650 | 7 | a Medicinsk bioteknologi2 hsv |
650 | 7 | a Medicinsk bioteknologi (med inriktning mot cellbiologi (inklusive stamcellsbiologi), molekylärbiologi, mikrobiologi, biokemi eller biofarmaci)2 hsv |
653 | 0 | a DNA methylation |
653 | 0 | a Aging |
653 | 0 | a Rule-based classification |
653 | 0 | a Feature selection |
700 | 1 | a Dabrowski, Michal4 aut |
700 | 1 | a Kaminska, Bozena4 aut |
700 | 1 | a Grabherr, Manfred G.4 aut |
700 | 1 | a Komorowski, Jan4 aut |
710 | 1 2 | a Uppsala universitetb Teknisk-naturvetenskapliga vetenskapsområdet4 pbl |
710 | 1 2 | a Uppsala universitetb Medicinska och farmaceutiska vetenskapsområdet4 pbl |
772 | 1 8 | i channel recordw 19753896 |
773 | 0 8 | i Värdpublikationt BMC Bioinformaticsg 17x 1471-2105 |
856 | 4 0 | u http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-305330 |
856 | 4 0 | u http://dx.doi.org/10.1186/s12859-016-1259-3 |
856 | 4 0 | u http://uu.diva-portal.org/smash/get/diva2:1037360/FULLTEXT01 |
841 | 5 APISa x ab 170425||0000|||||001||||||000000e 1 | |
024 | 7 | 5 APISa urn:nbn:se:uu:diva-3053302 urn |
852 | 5 APISb APIS | |
856 | 4 0 | 5 APISu http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-305330 |
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