guest ::
| Home > Publications Database > Tissue-based Alzheimer gene expression markers-comparison of multiple machine learning approaches and investigation of redundancy in small biomarker sets. > print |
| Home > Publications Database > Tissue-based Alzheimer gene expression markers-comparison of multiple machine learning approaches and investigation of redundancy in small biomarker sets. > print |
| 001 | 136801 | ||
| 005 | 20240424120355.0 | ||
| 024 | 7 | _ | |a 10.1186/1471-2105-13-266 |2 doi |
| 024 | 7 | _ | |a pmid:23066814 |2 pmid |
| 024 | 7 | _ | |a pmc:PMC3574043 |2 pmc |
| 024 | 7 | _ | |a altmetric:1002585 |2 altmetric |
| 037 | _ | _ | |a DZNE-2020-03123 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Scheubert, Lena |0 P:(DE-HGF)0 |b 0 |
| 245 | _ | _ | |a Tissue-based Alzheimer gene expression markers-comparison of multiple machine learning approaches and investigation of redundancy in small biomarker sets. |
| 260 | _ | _ | |a Heidelberg |c 2012 |b Springer |
| 264 | _ | 1 | |3 print |2 Crossref |b Springer Science and Business Media LLC |c 2012-01-01 |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1713882742_10931 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a Alzheimer's disease has been known for more than 100 years and the underlying molecular mechanisms are not yet completely understood. The identification of genes involved in the processes in Alzheimer affected brain is an important step towards such an understanding. Genes differentially expressed in diseased and healthy brains are promising candidates.Based on microarray data we identify potential biomarkers as well as biomarker combinations using three feature selection methods: information gain, mean decrease accuracy of random forest and a wrapper of genetic algorithm and support vector machine (GA/SVM). Information gain and random forest are two commonly used methods. We compare their output to the results obtained from GA/SVM. GA/SVM is rarely used for the analysis of microarray data, but it is able to identify genes capable of classifying tissues into different classes at least as well as the two reference methods.Compared to the other methods, GA/SVM has the advantage of finding small, less redundant sets of genes that, in combination, show superior classification characteristics. The biological significance of the genes and gene pairs is discussed. |
| 536 | _ | _ | |a 344 - Clinical and Health Care Research (POF3-344) |0 G:(DE-HGF)POF3-344 |c POF3-344 |f POF III |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef, PubMed, |
| 650 | _ | 7 | |a Genetic Markers |2 NLM Chemicals |
| 650 | _ | 2 | |a Alzheimer Disease: genetics |2 MeSH |
| 650 | _ | 2 | |a Artificial Intelligence: statistics & numerical data |2 MeSH |
| 650 | _ | 2 | |a Gene Expression |2 MeSH |
| 650 | _ | 2 | |a Gene Expression Profiling: statistics & numerical data |2 MeSH |
| 650 | _ | 2 | |a Genetic Markers |2 MeSH |
| 650 | _ | 2 | |a Humans |2 MeSH |
| 650 | _ | 2 | |a Oligonucleotide Array Sequence Analysis: statistics & numerical data |2 MeSH |
| 650 | _ | 2 | |a Support Vector Machine |2 MeSH |
| 650 | _ | 2 | |a Tissue Array Analysis: statistics & numerical data |2 MeSH |
| 700 | 1 | _ | |a Luštrek, Mitja |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Schmidt, Rainer |0 P:(DE-HGF)0 |b 2 |
| 700 | 1 | _ | |a Repsilber, Dirk |0 P:(DE-HGF)0 |b 3 |e Corresponding author |
| 700 | 1 | _ | |a Fuellen, Georg |0 P:(DE-2719)9000086 |b 4 |e Last author |u dzne |
| 773 | 1 | 8 | |a 10.1186/1471-2105-13-266 |b : Springer Science and Business Media LLC, 2012-01-01 |n 1 |p 266 |3 journal-article |2 Crossref |t BMC Bioinformatics |v 13 |y 2012 |x 1471-2105 |
| 773 | _ | _ | |a 10.1186/1471-2105-13-266 |g Vol. 13, no. 1, p. 266 - |0 PERI:(DE-600)2041484-5 |n 1 |q 13:1<266 - |p 266 |t BMC bioinformatics |v 13 |y 2012 |x 1471-2105 |
| 856 | 4 | _ | |y OpenAccess |u https://pub.dzne.de/record/136801/files/DZNE-2020-03123.pdf |
| 856 | 4 | _ | |y OpenAccess |x pdfa |u https://pub.dzne.de/record/136801/files/DZNE-2020-03123.pdf?subformat=pdfa |
| 856 | 7 | _ | |2 Pubmed Central |u http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3574043 |
| 909 | C | O | |o oai:pub.dzne.de:136801 |p openaire |p open_access |p VDB |p driver |p dnbdelivery |
| 910 | 1 | _ | |a Deutsches Zentrum für Neurodegenerative Erkrankungen |0 I:(DE-588)1065079516 |k DZNE |b 4 |6 P:(DE-2719)9000086 |
| 913 | 1 | _ | |a DE-HGF |b Gesundheit |l Erkrankungen des Nervensystems |1 G:(DE-HGF)POF3-340 |0 G:(DE-HGF)POF3-344 |3 G:(DE-HGF)POF3 |2 G:(DE-HGF)POF3-300 |4 G:(DE-HGF)POF |v Clinical and Health Care Research |x 0 |
| 914 | 1 | _ | |y 2012 |
| 915 | _ | _ | |a Creative Commons Attribution CC BY 2.0 |0 LIC:(DE-HGF)CCBY2 |2 HGFVOC |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1050 |2 StatID |b BIOSIS Previews |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0600 |2 StatID |b Ebsco Academic Search |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b BMC BIOINFORMATICS : 2017 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0501 |2 StatID |b DOAJ Seal |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0500 |2 StatID |b DOAJ |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0111 |2 StatID |b Science Citation Index Expanded |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |
| 915 | _ | _ | |a IF < 5 |0 StatID:(DE-HGF)9900 |2 StatID |
| 915 | _ | _ | |a OpenAccess |0 StatID:(DE-HGF)0510 |2 StatID |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b ASC |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0310 |2 StatID |b NCBI Molecular Biology Database |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0320 |2 StatID |b PubMed Central |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |
| 920 | 1 | _ | |0 I:(DE-2719)6000017 |k Rostock / Greifswald common |l Rostock / Greifswald common |x 0 |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a UNRESTRICTED |
| 980 | _ | _ | |a I:(DE-2719)6000017 |
| 980 | 1 | _ | |a FullTexts |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1073/pnas.0709259105 |2 Crossref |o 10.1073/pnas.0709259105 |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1093/dnares/dsr016 |2 Crossref |o 10.1093/dnares/dsr016 |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1089/omi.2011.0054 |2 Crossref |o 10.1089/omi.2011.0054 |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1142/S0219720011005392 |2 Crossref |o 10.1142/S0219720011005392 |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1186/1750-1326-4-5 |2 Crossref |o 10.1186/1750-1326-4-5 |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1093/nar/28.1.27 |2 Crossref |o 10.1093/nar/28.1.27 |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1186/1755-8794-3-50 |2 Crossref |o 10.1186/1755-8794-3-50 |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1038/ng1934 |2 Crossref |o 10.1038/ng1934 |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1101/gr.114280.110 |2 Crossref |o 10.1101/gr.114280.110 |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1186/1752-0509-2-52 |2 Crossref |o 10.1186/1752-0509-2-52 |
| 999 | C | 5 | |2 Crossref |o |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.2307/2332510 |2 Crossref |o 10.2307/2332510 |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1016/j.ygeno.2004.09.007 |2 Crossref |o 10.1016/j.ygeno.2004.09.007 |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1006/geno.1997.4969 |2 Crossref |o 10.1006/geno.1997.4969 |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1073/pnas.0701014104 |2 Crossref |o 10.1073/pnas.0701014104 |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1016/S0168-9525(00)02000-X |2 Crossref |o 10.1016/S0168-9525(00)02000-X |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1016/S0955-0674(00)00161-7 |2 Crossref |o 10.1016/S0955-0674(00)00161-7 |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1016/j.devcel.2010.01.015 |2 Crossref |o 10.1016/j.devcel.2010.01.015 |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1186/1755-8794-4-55 |2 Crossref |o 10.1186/1755-8794-4-55 |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1016/j.jalz.2009.11.002 |2 Crossref |o 10.1016/j.jalz.2009.11.002 |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1016/j.pneurobio.2009.07.002 |2 Crossref |o 10.1016/j.pneurobio.2009.07.002 |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1111/j.1749-6632.1996.tb39072.x |2 Crossref |o 10.1111/j.1749-6632.1996.tb39072.x |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1111/j.1749-6632.1993.tb23024.x |2 Crossref |o 10.1111/j.1749-6632.1993.tb23024.x |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.2174/156720510793611592 |2 Crossref |o 10.2174/156720510793611592 |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1186/1471-2164-11-203 |2 Crossref |o 10.1186/1471-2164-11-203 |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1093/bib/bbp035 |2 Crossref |o 10.1093/bib/bbp035 |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1093/bioinformatics/19.2.185 |2 Crossref |o 10.1093/bioinformatics/19.2.185 |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1093/nar/gkg033 |2 Crossref |o 10.1093/nar/gkg033 |
| 999 | C | 5 | |9 -- missing cx lookup -- |a 10.1073/pnas.1530509100 |2 Crossref |o 10.1073/pnas.1530509100 |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|