DICP OpenIR
Subject Area物理化学
MultiDA: Chemometric software for multivariate data analysis based on Matlab
Yang, Qianxu; Zhang, Liangxiao; Wang, Longxing; Xiao, Hongbin; Xiao HB(肖红斌)
KeywordChemometrics Software Matlab Multivariate Analysis Metabolomics/metabonomics Multi-model Comparison
Source PublicationCHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
2012-07-01
DOI10.1016/j.chemolab.2012.03.019
Volume116Pages:1-8
Indexed BySCI
SubtypeArticle
Department18
Funding Project1804
Contribution Rank1,1
WOS HeadingsScience & Technology ; Technology ; Physical Sciences
WOS SubjectAutomation & Control Systems ; Chemistry, Analytical ; Computer Science, Artificial Intelligence ; Instruments & Instrumentation ; Mathematics, Interdisciplinary Applications ; Statistics & Probability
WOS Research AreaAutomation & Control Systems ; Chemistry ; Computer Science ; Instruments & Instrumentation ; Mathematics
WOS KeywordPRINCIPAL COMPONENT ANALYSIS ; LEAST-SQUARES REGRESSION ; DISCRIMINANT-ANALYSIS ; GENETIC ALGORITHMS ; CALIBRATION ; VALIDATION ; SELECTION ; TOOL ; PLS
AbstractMultivariate data analysis (MultiDA), a user-friendly interface chemometric software, is developed for the routine metabolomics/metabonomics data analysis. There are mainly two advantages for MultiDA. First, it could simultaneously provide multiply methods for data preprocessing and multivariate analysis. The main chemometric methods in MultiDA contains k-means cluster analysis, k-medoid cluster analysis, hierarchical cluster analysis (HCA), principal component analysis (PCA), robust principal component analysis (ROPCA), non-linear PCA (NLPCA), non-linear iterative partial least squares (NIPALS), SIMPLS, discriminate analysis (DA). canonical discriminate analysis (CDA), stepwise discriminate analysis (SDA), uncorrelated linear discriminate analysis (ULDA) and some data preprocessing methods, such as standardization, outlier detection, genetic algorithm for feature selection (GAFS), orthogonal signal correction (OSC), weight analysis (Weight) etc. Second, multi-model comparison could be conducted to obtain the best outcome. Moreover, this software is available for free. (C) 2012 Elsevier B.V. All rights reserved.
Language英语
WOS IDWOS:000306043900001
Citation statistics
Cited Times:7[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://cas-ir.dicp.ac.cn/handle/321008/118212
Collection中国科学院大连化学物理研究所
Corresponding AuthorXiao HB(肖红斌)
AffiliationChinese Acad Sci, Dalian Inst Chem Phys, Key Lab Separat Sci Analyt Chem, Dalian 116023, Peoples R China
Recommended Citation
GB/T 7714
Yang, Qianxu,Zhang, Liangxiao,Wang, Longxing,et al. MultiDA: Chemometric software for multivariate data analysis based on Matlab[J]. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS,2012,116:1-8.
APA Yang, Qianxu,Zhang, Liangxiao,Wang, Longxing,Xiao, Hongbin,&肖红斌.(2012).MultiDA: Chemometric software for multivariate data analysis based on Matlab.CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS,116,1-8.
MLA Yang, Qianxu,et al."MultiDA: Chemometric software for multivariate data analysis based on Matlab".CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS 116(2012):1-8.
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