| 1. |
- Aftab, Obaid, 1984-, et al.
(författare)
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Label free quantification of time evolving morphologies using time-lapse video microscopy enables identity control of cell lines and discovery of chemically induced differential activity in iso-genic cell line pairs
- 2015
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Ingår i: Chemometrics and Intelligent Laboratory Systems. - 0169-7439 .- 1873-3239. ; 141, s. 24-32
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Tidskriftsartikel (refereegranskat)abstract
- Label free time-lapse video microscopy based monitoring of time evolving cell population morphology has potential to offer a simple and cost effective method for identity control of cell lines. Such morphology monitoring also has potential to offer discovery of chemically induced differential changes between pairs of cell lines of interest, for example where one in a pair of cell lines is normal/sensitive and the other malignant/resistant. A new simple algorithm, pixel histogram hierarchy comparison (PHHC), for comparison of time evolving morphologies (TEM) in phase contrast time-lapse microscopy movies was applied to a set of 10 different cell lines and three different iso-genic colon cancer cell line pairs, each pair being genetically identical except for a single mutation. PHHC quantifies differences in morphology by comparing pixel histogram intensities at six different resolutions. Unsupervised clustering and machine learning based classification methods were found to accurately identify cell lines, including their respective iso-genic variants, through time-evolving morphology. Using this experimental setting, drugs with differential activity in iso-genic cell line pairs were likewise identified. Thus, this is a cost effective and expedient alternative to conventional molecular profiling techniques and might be useful as part of the quality control in research incorporating cell line models, e.g. in any cell/tumor biology or toxicology project involving drug/agent differential activity in pairs of cell line models.
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| 2. |
- Brydegaard, Mikkel, et al.
(författare)
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Complete parameterization of temporally and spectrally resolved laser induced fluorescence data with applications in bio-photonics
- 2015
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Ingår i: Chemometrics and Intelligent Laboratory Systems. - : Elsevier BV. - 0169-7439. ; 142, s. 95-106
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Tidskriftsartikel (refereegranskat)abstract
- We present a set of spectrally and temporally resolved clinical fluorescence data-with two separate excitation wavelengths-that was recorded in vivo. We demonstrate that data in the spectral and temporal domains are in certain ways coupled and provide a method for integrated and effective parameterization of spectrally and temporally resolved fluorescence (i.e., time-resolved emission spectra). This parameterization is based on linear algebra, matrix formulation and system identification. We demonstrate how to empirically extract single exponentially decaying components and provide rectified emission spectra without prior knowledge. We investigate the potential for improved cancer diagnostics according to the reduced parameters along the various domains. In this case, in terms of cancer diagnostics, we were unable to identify any benefits of simultaneously measuring both the temporal and spectral properties of the observed fluorescence. However, we note that this may be explained by an important experimental bias present in many studies of optical cancer diagnostics, namely, that, in general, suspected lesions always differ visually from the neighboring healthy tissue. (C) 2015 Elsevier B.V. All rights reserved.
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| 3. |
- dos Santos, Victor Hugo J. M., et al.
(författare)
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Discriminant analysis of biodiesel fuel blends based on combined data from Fourier Transform Infrared Spectroscopy and stable carbon isotope analysis
- 2017
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Ingår i: Chemometrics and Intelligent Laboratory Systems. - : Elsevier. - 0169-7439 .- 1873-3239. ; 161, s. 70-78
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Tidskriftsartikel (refereegranskat)abstract
- A multivariate approach was used for classification of fuel blends using the combined information from Fourier Transform Infrared Spectroscopy (FTIR) and stable carbon isotopes analysis by Isotope Ratio Mass Spectrometry (IRMS). Linear Discriminant Analysis (LDA) and Partial Least Squares Discriminant Analysis (PLS-DA) were applied to the classification of biodiesel/diesel fuel blends containing 0-100% (v/v) of biodiesel. The LDA and PLS-DA methods were able to discriminate samples ranging from 10% to 100% biodiesel (v/v) using the combined information from FTIR and IRMS. Since the global trend is toward a gradual increase in the percentage of biodiesel in fuel blends, the technique presented in this paper could be an important development in improving the traceability and identification of different raw materials used in biodiesel production.
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| 4. |
- Gajjar, Shriram, et al.
(författare)
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Selection of Non-zero Loadings in Sparse Principal Component Analysis
- 2017
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Ingår i: Chemometrics and Intelligent Laboratory Systems. - : Elsevier. - 0169-7439 .- 1873-3239. ; 162, s. 160-171
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Tidskriftsartikel (refereegranskat)abstract
- Principal component analysis (PCA) is a widely accepted procedure for summarizing data through dimensional reduction. In PCA, the selection of the appropriate number of components and the interpretation of those components have been the key challenging features. Sparse principal component analysis (SPCA) is a relatively recent technique proposed for producing principal components with sparse loadings via the variance-sparsity trade-off. Although several techniques for deriving sparse loadings have been offered, no detailed guidelines for choosing the penalty parameters to obtain a desired level of sparsity are provided. In this paper, we propose the use of a genetic algorithm (GA) to select the number of non-zero loadings (NNZL) in each principal component while using SPCA. The proposed approach considerably improves the interpretability of principal components and addresses the difficulty in the selection of NNZL in SPCA. Furthermore, we compare the performance of PCA and SPCA in uncovering the underlying latent structure of the data. The key features of the methodology are assessed through a synthetic example, pitprops data and a comparative study of the benchmark Tennessee Eastman process.
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| 5. |
- Galindo-Prieto, Beatriz, et al.
(författare)
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A new approach for variable influence on projection (VIP) in O2PLS models
- 2017
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Ingår i: Chemometrics and Intelligent Laboratory Systems. - : Elsevier. - 0169-7439 .- 1873-3239. ; 160, s. 110-124
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Tidskriftsartikel (refereegranskat)abstract
- A novel variable influence on projection approach for O2PLS® models, named VIPO2PLS, is presented in this paper. VIPO2PLS is a model-based method for judging the importance of variables. Its cornerstone is the 2-way formalism of the O2PLS models; i.e. the use of both predictive and orthogonal normalized loadings of the two modelled data matrices, and also a new weighting system based on the sum of squares of both data blocks (X, Y). The VIPO2PLS algorithm has been tested in one synthetic data set and two real cases, and the outcomes have been compared to the PLS-VIP, VIPOPLS, and i-PLS methods. The purpose is to achieve a sharper and enhanced model interpretation of O2PLS models by using the new VIPO2PLS method for assessing the importance of both X- and Y- variables.
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| 6. |
- Galindo-Prieto, Beatriz, et al.
(författare)
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Variable influence on projection (VIP) for OPLS models and its applicability in multivariate time series analysis
- 2015
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Ingår i: Chemometrics and Intelligent Laboratory Systems. - : Elsevier. - 0169-7439 .- 1873-3239. ; 146, s. 297-304
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Tidskriftsartikel (refereegranskat)abstract
- Abstract Recently a new parameter to infer variable importance in orthogonal projections to latent structures (OPLS) was presented. Called OPLS-VIP (variable influence on projection), this parameter is here applied in multivariate time series analysis to achieve an improved diagnosis of process dynamics. To this end, OPLS-VIP has been tested in three real-world industrial data sets; the first data set corresponds to a pulp manufacturing process using a continuous digester, the second one involves data from an industrial heater that experienced problems, and the third data set contains measures of the chemical oxygen demand into the effluent of a newsprint mill. The outcomes obtained using OPLS-VIP are benchmarked against classical PLS-VIP results. It is demonstrated how OPLS-VIP provides a better diagnosis and understanding of the time series behavior than PLS-VIP.
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| 7. |
- Krupinska, Karolina, et al.
(författare)
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Detection of low levels of Escherichia coli by electrochemical impedance spectroscopy and singular value decomposition
- 2017
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Ingår i: Chemometrics and Intelligent Laboratory Systems. - : Elsevier. - 0169-7439 .- 1873-3239. ; 163, s. 49-54
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Tidskriftsartikel (refereegranskat)abstract
- The first steps are reported in the development of a new ultrasensitive electrochemical biosensor for detection of Escherichia coli (E. coli) in water. Two gold electrodes in a sandwich flow-cell were modified with E. coli polyclonal antibody and exposed to three different concentrations of E. coli. Electrochemical Impedance Spectroscopy was used in combination with Singular Value Decompostion of the complex numbers to monitor the interactions at the electrode surfaces. A linear regression line in the concentration range 10-1000 CFU⁎ml-1 was obtained without use of redox probes or metal nanoparticles for signal amplification.
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| 8. |
- Shoombuatong, Watshara, et al.
(författare)
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Extending proteochemometric modeling for unraveling the sorption behavior of compound-soil interaction
- 2016
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Ingår i: Chemometrics and Intelligent Laboratory Systems. - : Elsevier BV. - 0169-7439 .- 1873-3239. ; 151, s. 219-227
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Tidskriftsartikel (refereegranskat)abstract
- Contamination of ground water by industrial chemicals presents a major environmental and health problem. Soil sorption plays an important role in the transport and movement of such pollutant chemicals. In this study, proteochemometric (PCM) modeling was used to unravel the origins of interactions of 17 phthalic acid esters (PAEs) against 3 soil types by predicting the organic carbon content normalized sorption coefficient (logK(oc)) values as a function of fingerprint descriptors of 17 PAEs and physical and textural properties of 3 soils. The results showed that PCM models provided excellent predictivity (R-2 = 0.94, Q(2) = 0.89,Q(Ext)(2) = 0.85). In further validation of the model, our proposed PCM model was assessed by leave-one-compound-out (Q(LOCO)(2) = 0.86) and leave-one-soil-out (Q(LOCO)(2) = 0.86) cross-validations. The transparency of the PCM model allowed interpretation of the underlying importance of descriptors, which potentially contributes to a better understanding on the outcome of PAEs in the environment. A thorough analysis of descriptor importance revealed the contribution of secondary carbon atoms on the hydrophobicity and flexibility of PAEs as significant properties in influencing the soil sorption capacity.
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| 9. |
- Spooner, Max, et al.
(författare)
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Monitoring batch processes with dynamic time warping and k-nearest neighbours
- 2018
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Ingår i: Chemometrics and Intelligent Laboratory Systems. - : Elsevier. - 0169-7439 .- 1873-3239. ; 183, s. 102-112
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Tidskriftsartikel (refereegranskat)abstract
- A novel data driven approach to batch process monitoring is presented, which combines the k-Nearest Neighbour rule with the dynamic time warping (DTW) distance. This online method (DTW-NN) calculates the DTW distance between an ongoing batch, and each batch in a reference database of batches produced under normal operating conditions (NOC). The sum of the k smallest DTW distances is monitored. If a fault occurs in the ongoing batch, then this distance increases and an alarm is generated. The monitoring statistic is easy to interpret, being a direct measure of similarity of the ongoing batch to its nearest NOC predecessors and the method makes no distributional assumptions regarding normal operating conditions. DTW-NN is applied to four extensive datasets from simulated batch production of penicillin, and tested on a wide variety of fault types, magnitudes and onset times. Performance of DTW-NN is contrasted with a benchmark multiway PCA approach, and DTW-NN is shown to perform particularly well when there is clustering of batches under NOC.
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| 10. |
- Spooner, Max, et al.
(författare)
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Selecting local constraint for alignment of batch process data with dynamic time warping
- 2017
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Ingår i: Chemometrics and Intelligent Laboratory Systems. - : Elsevier. - 0169-7439 .- 1873-3239. ; 167, s. 161-170
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Tidskriftsartikel (refereegranskat)abstract
- There are two key reasons for aligning batch process data. The first is to obtain same-length batches so that standard methods of analysis may be applied, whilst the second reason is to synchronise events that take place during each batch so that the same event is associated with the same observation number for every batch. Dynamic time warping has been shown to be an effective method for meeting these objectives. This is based on a dynamic programming algorithm that aligns a batch to a reference batch, by stretching and compressing its local time dimension. The resulting ”warping function” may be interpreted as a progress signature of the batch which may be appended to the aligned data for further analysis. For the warping function to be a realistic reflection of the progress of a batch, it is necessary to impose some constraints on the dynamic time warping algorithm, to avoid an alignment which is too aggressive and which contains pathological warping. Previous work has focused on addressing this issue using global constraints. In this work, we investigate the use of local constraints in dynamic time warping and define criteria for evaluating the degree of time distortion and variable synchronisation obtained. A local constraint scheme is extended to include constraints not previously considered, and a novel method for selecting the optimal local constraint with respect to the two criteria is proposed. For illustration, the method is applied to real data from an industrial bacteria fermentation process.
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