Chemometrics applied to unravel multicomponent processes and mixtures - Revisiting latest trends in multivariate resolution

被引:462
作者
de Juan, A [1 ]
Tauler, R [1 ]
机构
[1] Univ Barcelona, Chemometr Grp, E-08028 Barcelona, Spain
关键词
chemometrics; multivariate resolution; multicomponent system; curve resolution;
D O I
10.1016/S0003-2670(03)00724-4
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Progress in the analysis of multicomponent processes and mixtures relies on the combination of sophisticated instrumental techniques and suitable data analysis tools focused on the interpretation of the multivariate responses obtained. Despite the differences in compositional variation, complexity and origin, the raw measurements recorded in a multicomponent chemical system can be very often described with a simple model consisting of the composition-weighted sum of the signals of their pure compounds. Multivariate resolution methods have been the tools designed to unravel this pure compound information from the non-selective mixed original experimental output. The evolution of these chemometric approaches through the improvement of exploratory tools, the adaptation to work with complex data structures, the ability to introduce chemical and mathematical information in the algorithms and the better quality assessment of the results obtained is revisited. The active research on these chemometric area has allowed the successful application of these methodologies to chemical problems as complex and diverse as the interpretation of protein folding processes or the resolution of spectroscopic images. (C) 2003 Elsevier B.V All rights reserved.
引用
收藏
页码:195 / 210
页数:16
相关论文
共 132 条
[51]  
Hamilton J.C., 1990, J CHEMOMETR, V4, P1, DOI 10.1002/cem.1180040103
[52]   2 ALGORITHMS FOR THE LINEARLY CONSTRAINED LEAST-SQUARES PROBLEM [J].
HANSON, RJ ;
HASKELL, KH .
ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE, 1982, 8 (03) :323-333
[53]  
Harshman R. A., 1970, UCLA Work. Papers Phonetics, V16, P1, DOI DOI 10.1134/S0036023613040165
[54]   AN ALGORITHM FOR LINEAR LEAST-SQUARES PROBLEMS WITH EQUALITY AND NON-NEGATIVITY CONSTRAINTS [J].
HASKELL, KH ;
HANSON, RJ .
MATHEMATICAL PROGRAMMING, 1981, 21 (01) :98-118
[55]   EXTENSION OF SELF-MODELING CURVE RESOLUTION TO MIXTURES OF MORE THAN 3 COMPONENTS .1. FINDING THE BASIC FEASIBLE REGION [J].
HENRY, RC ;
KIM, BM .
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 1990, 8 (02) :205-216
[56]  
Hopke P.K., 1985, RECEPTOR MODELING EN
[57]   Second-order multivariate curve resolution applied to rank-deficient data obtained from acid-base spectrophotometric titrations of mixtures of nucleic bases [J].
IzquierdoRidorsa, A ;
Saurina, J ;
HernandezCassou, S ;
Tauler, R .
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 1997, 38 (02) :183-196
[58]   Target transform fitting: a new method for the non-linear fitting of multivariate data with separable parameters [J].
Jandanklang, P ;
Maeder, M ;
Whitson, AC .
JOURNAL OF CHEMOMETRICS, 2001, 15 (06) :511-522
[59]   Multivariate curve resolution:: a powerful tool for the analysis of conformational transitions in nucleic acids -: art. no. e92 [J].
Jaumot, J ;
Escaja, N ;
Gargallo, R ;
González, C ;
Pedroso, E ;
Tauler, R .
NUCLEIC ACIDS RESEARCH, 2002, 30 (17) :e92
[60]  
JAUMOT J, UNPUB