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DC Field | Value | Language |
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dc.contributor.advisor | This article has been made available through the Brunel Open Access Publishing Fund. | - |
dc.contributor.author | Fa, R | - |
dc.contributor.author | Nandi, AK | - |
dc.date.accessioned | 2015-03-09T14:27:06Z | - |
dc.date.available | 2014-07-01 | - |
dc.date.available | 2015-03-09T14:27:06Z | - |
dc.date.issued | 2014 | - |
dc.identifier.citation | IEEE-ACM Transactions on Computational Biology and Bioinformatics, 2014, 11 (4), pp. 741 - 752 (12) | en_US |
dc.identifier.issn | 1545-5963 | - |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/10356 | - |
dc.description | This article has been made available through the Brunel Open Access Publishing Fund. | - |
dc.description.abstract | Validity indices have been investigated for decades. However, since there is no study of noise-resistance performance of these indices in the literature, there is no guideline for determining the best clustering in noisy data sets, especially microarray data sets. In this paper, we propose a generalized parametric validity (GPV) index which employs two tunable parameters α and β to control the proportions of objects being considered to calculate the dissimilarities. The greatest advantage of the proposed GPV index is its noise-resistance ability, which results from the flexibility of tuning the parameters. Several rules are set to guide the selection of parameter values. To illustrate the noise-resistance performance of the proposed index, we evaluate the GPV index for assessing five clustering algorithms in two gene expression data simulation models with different noise levels and compare the ability of determining the number of clusters with eight existing indices. We also test the GPV in three groups of real gene expression data sets. The experimental results suggest that the proposed GPV index has superior noise-resistance ability and provides fairly accurate judgements. | en_US |
dc.format.extent | 741 - 752 (12) | - |
dc.format.extent | 741 - 752 (12) | - |
dc.language | English | - |
dc.language.iso | en | en_US |
dc.publisher | IEEE COMPUTER SOC | en_US |
dc.subject | Science & Technology | en_US |
dc.subject | Life Sciences & Biomedicine | en_US |
dc.subject | Technology | en_US |
dc.subject | Physical Sciences | en_US |
dc.subject | Biochemical Research Methods | en_US |
dc.subject | Computer Science, Interdisciplinary Applications | en_US |
dc.subject | Mathematics, Interdisciplinary Applications | en_US |
dc.subject | Statistics & Probability | en_US |
dc.subject | Biochemistry & Molecular Biology | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Mathematics | en_US |
dc.subject | Clustering validity index | en_US |
dc.subject | noise resistance | en_US |
dc.subject | gene expression analysis | en_US |
dc.subject | microarray | en_US |
dc.subject | Microarray data | en_US |
dc.subject | Saccharomyces-Cerevisiae | en_US |
dc.subject | Cell-cycle | en_US |
dc.subject | Validation | en_US |
dc.title | Noise resistant generalized parametric validity index of clustering for gene expression data | en_US |
dc.type | Article | en_US |
dc.identifier.doi | http://dx.doi.org/10.1109/TCBB.2014.2312006 | - |
dc.relation.isPartOf | IEEE-ACM Transactions on Computational Biology and Bioinformatics | - |
dc.relation.isPartOf | IEEE-ACM Transactions on Computational Biology and Bioinformatics | - |
pubs.issue | 4 | - |
pubs.issue | 4 | - |
pubs.publication-status | Published | - |
pubs.publication-status | Published | - |
pubs.volume | 11 | - |
pubs.volume | 11 | - |
pubs.organisational-data | /Brunel | - |
pubs.organisational-data | /Brunel/Brunel Staff by College/Department/Division | - |
pubs.organisational-data | /Brunel/Brunel Staff by College/Department/Division/College of Engineering, Design and Physical Sciences | - |
pubs.organisational-data | /Brunel/Brunel Staff by College/Department/Division/College of Engineering, Design and Physical Sciences/Dept of Electronic and Computer Engineering | - |
pubs.organisational-data | /Brunel/Brunel Staff by College/Department/Division/College of Engineering, Design and Physical Sciences/Dept of Electronic and Computer Engineering/Electronic and Computer Engineering | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/Brunel Business School - URCs and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/Brunel Business School - URCs and Groups/Centre for Research into Entrepreneurship, International Business and Innovation in Emerging Markets | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups/Brunel Institute for Ageing Studies | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups/Brunel Institute of Cancer Genetics and Pharmacogenomics | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups/Centre for Systems and Synthetic Biology | - |
Appears in Collections: | Brunel OA Publishing Fund Dept of Electronic and Electrical Engineering Research Papers |
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