Peak deconvolution in one-dimensional chromatography using a two-way data approach

Vivó-Truyols, Gabriel; Torres-Lapası́o, J.R.; Caballero, Rocío; Garcı́a-Alvarez-Coque, M.C.

doi:10.1016/s0021-9673(02)00409-0

Cited by 17 publications

(5 citation statements)

References 30 publications

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“…In this article, we modified the single‐well Lennard‐Jones shaped function U 0 ( r mn ) to a multiwell energy function U ( r mn ) using a set of a Gaussian functions and a window function to approximate the statistical data derived from the PDB. Multipeak fitting methods are often used to fit the spectroscopic and chromatographic data in which multiple overlapping peaks exist 45–47. Gaussian method is more accurate for fitting multipeak curves than other methods, such as the Lorentzian method 48.…”

Section: Methodsmentioning

confidence: 99%

Native secondary structure topology has near minimum contact energy among all possible geometrically constrained topologies

Sun

2009

Proteins

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Secondary structure topology in this article refers to the order and the direction of the secondary structures, such as helices and strands, with respect to the protein sequence. Even when the locations of the secondary structure Calpha atoms are known, there are still (N!2(N))(M!2(M)) different possible topologies for a protein with N helices and M strands. This work explored the question if the native topology is likely to be identified among a large set of all possible geometrically constrained topologies through an evaluation of the residue contact energy formed by the secondary structures, instead of the entire chain. We developed a contact pair specific and distance specific multiwell function based on the statistical characterization of the side chain distances of 413 proteins in the Protein Data Bank. The multiwell function has specific parameters to each of the 210 pairs of residue contacts. We illustrated a general mathematical method to extend a single well function to a multiwell function to represent the statistical data. We have performed a mutation analysis using 50 proteins to generate all the possible geometrically constrained topologies of the secondary structures. The result shows that the native topology is within the top 25% of the list ranked by the effective contact energies of the secondary structures for all the 50 proteins, and is within the top 5% for 34 proteins. As an application, the method was used to derive the structure of the skeletons from a low resolution density map that can be obtained through electron cryomicroscopy.

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Section: Methodsmentioning

confidence: 99%

Native secondary structure topology has near minimum contact energy among all possible geometrically constrained topologies

Sun

2009

Proteins

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“…In addition, strategies to process data obtained from high-performance liquid chromatography (HPLC) and capillary electrophoresis (CE) [61,62], or a multi-batch approach, combined with multiple-wavelength chromatograms for 1D data analysis, may be extended to GC deconvolution [63].…”

Section: Gc×gc Data Deconvolutionmentioning

confidence: 99%

Interpretation of comprehensive two-dimensional gas chromatography data using advanced chemometrics

Zeng

Hügel

et al. 2014

TrAC Trends in Analytical Chemistry

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HIGHLIGHTS• We present a comprehensive survey of GC×GC and GC×GC-MS data with chemometrics • This review includes principles, theories and graphical tools for data processing • We discuss deconvolution of 1D, coupled and GC×GC separations with FID/MS • We consider retention, structure, t R shifts, orthogonality and image analysis ABSTRACT The power of comprehensive two-dimensional gas chromatography (GC×GC) for the study of complex mixtures has been indisputably proved in the past several decades. This review encompasses the whole of GC×GC-related data processing and summarizes relevant applications. We include theoretical introduction to some specific methods and studies to aid readers' understanding of chemometrics strategies for advanced data interpretation.

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“…To solve a univariate deconvolution problem, approaches such as evolving factor analysis (EFA) (Maeder, 1987) or multivariate curve resolution (MCR) (Tauler & Barceló, 1993), among others (Vivó-Truyols et al, 2002;Sarkar et al, 1998;Kong et al 2005) can be used. When these approaches are used with univariate data, the variables to be solved for are the number, positions, and abundances of each of the peaks that make up the signal.…”

Section: Deconvolution Of Univariate Signalsmentioning

confidence: 99%

Application of Chemometrics to the Interpretation of Analytical Separations Data

Harynuk¹,

Mata²,

Sinkov³

2012

Chemometrics in Practical Applications

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Peak deconvolution in one-dimensional chromatography using a two-way data approach

Cited by 17 publications

References 30 publications

Native secondary structure topology has near minimum contact energy among all possible geometrically constrained topologies

Native secondary structure topology has near minimum contact energy among all possible geometrically constrained topologies

Interpretation of comprehensive two-dimensional gas chromatography data using advanced chemometrics

Application of Chemometrics to the Interpretation of Analytical Separations Data

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