Journal ArticleDOI
Classification tools in chemistry. Part 1: linear models. PLS-DA
Davide Ballabio,Viviana Consonni +1 more
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TLDR
The common steps to calibrate and validate classification models based on partial least squares discriminant analysis are discussed in the present tutorial, and issues to be evaluated during model training and validation are introduced and explained using a chemical dataset.Abstract:
The common steps to calibrate and validate classification models based on partial least squares discriminant analysis are discussed in the present tutorial. All issues to be evaluated during model training and validation are introduced and explained using a chemical dataset, composed of toxic and non-toxic sediment samples. The analysis was carried out with MATLAB routines, which are available in the ESI of this tutorial, together with the dataset and a detailed list of all MATLAB instructions used for the analysis.read more
Citations
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Investigating centrifugal filtration of serum-based FTIR spectroscopy for the stratification of brain tumours
TL;DR: In this paper , a serum-based attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy diagnostics was first developed by Hands et al. with a reported sensitivity of 92.8% and specificity of 91.5%.
Patent
Discerning brain cancer type
Baker Matthew,Cameron James +1 more
TL;DR: In this article, a diagnostic kit for determining whether a subject suspected of having a brain tumour has a glioma or a lymphoma and a method of facilitating the selection of treatment for a subject who has been diagnosed with a brain tumor is presented.
Journal ArticleDOI
Towards common useable spectra in non-targeted analysis - A feasibility study by mid-infrared spectroscopy, transfer and correction approaches
Carolin Lörchner,Carsten Fauhl-Hassek,Marcus A. Glomb,Vincent Baeten,Juan Antonio Fernández Pierna,Susanne Esslinger +5 more
TL;DR: In this article , a comparison of the spectra acquired by different spectroscopic instruments using the same measurement principle is presented. But the results show that the obtained spectra exhibited differences in absorbance, but not in wavelengths of bands position and maxima.
Journal ArticleDOI
Chemometrics in Protein Formulation: Stability Governed by Repulsion and Protein Unfolding.
Alina Kulakova,Dillen Augustijn,Inas El Bialy,Lorenzo Gentiluomo,Maria Laura Greco,Stefan Hervø-Hansen,Sowmya Indrakumar,Sujata Mahapatra,Marcello Martinez Morales,Christin Pohl,Marco Polimeni,Aisling Roche,Hristo L. Svilenov,Andreas Tosstorff,Matja Zalar,Robin Curtis,Jeremy P. Derrick,Wolfgang Friess,Alexander P. Golovanov,Mikael Kråkenes Lund,Allan Nørgaard,Tarik A. Khan,Günther H.J. Peters,Alain Pluen,Dierk Roessner,Werner Streicher,Christopher F. van der Walle,Jim Warwicker,Shahid Uddin,Gerhard Winter,Jens T. Bukrinski,Åsmund Rinnan,Pernille Harris +32 more
TL;DR: In this article, high-throughput characterization, employing a toolbox of five techniques, was performed on 14 structurally different proteins formulated in 6 different buffer conditions and in the presence of 4 different excipients.
Journal ArticleDOI
Front-face excitation-emission matrix fluorescence spectroscopy combined with interpretable deep learning for the rapid identification of the storage year of Ningxia wolfberry.
Xiaoyu Yan,Hai-Long Wu,Tong Wang,Yaoqiong Chen,An-Qi Chen,Kun Huang,Yue-Yue Chang,Jian Yang,Ru-Qin Yu +8 more
TL;DR: Wang et al. as discussed by the authors used the front face excitation-emission matrix (FF-EEM) fluorescence spectroscopy coupled with interpretable deep learning to identify the storage year of Ningxia wolfberry in a lossless, fast and accurate way.
References
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Beware of q2
TL;DR: It is argued that the high value of LOO q2 appears to be the necessary but not the sufficient condition for the model to have a high predictive power, which is the general property of QSAR models developed using LOO cross-validation.
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Computer Aided Design of Experiments
Robert W. Kennard,L. A. Stone +1 more
TL;DR: A computer oriented method which assists in the construction of response surface type experimental plans takes into account constraints met in practice that standard procedures do not consider explicitly.
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PLS regression methods
TL;DR: In this paper, the mathematical and statistical structure of PLS regression is developed and the PLS decomposition of the data matrices involved in model building is analyzed. But the PLP regression algorithm can be interpreted in a model building setting.
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Kohonen and counterpropagation artificial neural networks in analytical chemistry
TL;DR: The principles of the Kohonen and counterpropagation artificial neural network (K-ANN and CP-ANN) learning strategy is described and the use of both methods is explained with several examples from analytical chemistry.
Journal ArticleDOI
Calculation of the reliability of classification in discriminant partial least-squares binary classification
TL;DR: This method, called Probabilistic Discriminant Partial Least Squares (p-DPLS), integrates DPLS, density methods and Bayes decision theory in order to take into account the uncertainty of the predictions in DPLs.