Search results for "Computer Science Application"
showing 10 items of 3998 documents
UNCLES: Method for the identification of genes differentially consistently co-expressed in a specific subset of datasets
2015
Background Collective analysis of the increasingly emerging gene expression datasets are required. The recently proposed binarisation of consensus partition matrices (Bi-CoPaM) method can combine clustering results from multiple datasets to identify the subsets of genes which are consistently co-expressed in all of the provided datasets in a tuneable manner. However, results validation and parameter setting are issues that complicate the design of such methods. Moreover, although it is a common practice to test methods by application to synthetic datasets, the mathematical models used to synthesise such datasets are usually based on approximations which may not always be sufficiently repres…
FINITE-SIZE CORRECTIONS TO CORRELATION FUNCTION AND SUSCEPTIBILITY IN 2D ISING MODEL
2006
Transfer matrix calculations of the critical two-point correlation function in 2D Ising model on a finite-size [Formula: see text] lattice with periodic boundaries along 〈11〉 direction are extended to L = 21. A refined analysis of the correlation function in 〈10〉 crystallographic direction at the distance r = L indicates the existence of a nontrivial finite-size correction of a very small amplitude with correction-to-scaling exponent ω < 2 in agreement with our foregoing study for L ≤ 20. Here we provide an additional evidence and show that amplitude a of the multiplicative correction term 1 + aL-ωis about -3.5·10-8if ω = 1/4 (the expected value). We calculate also the susceptibility for…
A Multivariate Analysis on Non-nucleoside HIV-1 Reverse Transcriptase Inhibitors and Resistance Induced by Mutation
2003
This paper describes the use of multivariate statistical procedure PCA as a tool to explore the inhibitory activity of classes of NNRTIs against HIV-1 viruses (wild type and more frequent mutants, Y181C, V106A, K103N, L100I) and against RT enzyme. The analysis of correlations between biological activity and molecular descriptors or similarity indexes allowed a reliable classification of the fifty five derivatives considered in this study. The best results were obtained in the case of L100I and K103N mutants for which the higher number of assignments was found when the principal components derived from the descriptors were used. On this basis this statistical approach is proposed as a reliab…
Comparison of different predictive models for nutrient estimation in a sequencing batch reactor for wastewater treatment
2006
Abstract In this paper different predictive models for nutrient estimation in a sequencing batch reactor (SBR) for wastewater treatment are compared: principal component regression (PCR), partial least squares (PLS), and artificial neural networks (ANNs). Two unfolding procedures were used: batch-wise and variable-wise. For the latter unfolding method, X and Y matrix augmentation with lagged variables were used in some models to incorporate process dynamics. The results have shown that batch-wise unfolding PLS models outperform the other approaches. The ANN models are good predictive models, but in this particular case-study, they do not outperform those multivariate projection models that …
On the internal multivariate quality control of analytical laboratories. A case study: the quality of drinking water
2001
Abstract Multivariate statistical process control (MSPC) tools, based on principal component analysis (PCA), partial least squares (PLS) regression and other regression models, are used in the present study for automatic detection of possible errors in the methods used for routine multiparametric analysis in order to design an internal Multivariate Analytical Quality Control (iMAQC) program. Such tools could notice possible failures in the analytical methods without resorting to any external reference since they use their own analytical results as a source for the diagnosis of the method's quality. Pseudo-univariate control charts provide an attractive alternative to traditional univariate …
Multivariate SPC of a sequencing batch reactor for wastewater treatment
2007
Data from a sequencing batch reactor (SBR) operated for enhanced biological phosphorus removal from wastewater have been analysed in order to propose an efficient MSPC scheme of the process. Different multivariate bilinear approaches have been applied and compared in terms of their capabilities for on-line and off-line fault detection and diagnosis. The typical three-way data structure from a batch process was unfolded batch-wise and variable-wise. In the latter case, two models were built: with (AT) and without (WKFH) removing the main non-linear behaviour of the process data. Since the process consists of several stages, the monitoring strategies tested include: one model for all stages a…
A discrete mathematical model for addictive buying: Predicting the affected population evolution
2011
This paper deals with the construction of a discrete mathematical model for addictive buying. Firstly, identifications of consumers buying behavior are performed by using multivariate statistical techniques based on real data bases and sociological approaches. Then the population is divided into appropriate groups according to the level of overbuying and a discrete compartmental model is constructed. The future short term addicted population is computed assuming several future economic scenarios. © 2010 Elsevier Ltd.
Non-uniform multivariate embedding to assess the information transfer in cardiovascular and cardiorespiratory variability series
2012
The complexity of the short-term cardiovascular control prompts for the introduction of multivariate (MV) nonlinear time series analysis methods to assess directional interactions reflecting the underlying regulatory mechanisms. This study introduces a new approach for the detection of nonlinear Granger causality in MV time series, based on embedding the series by a sequential, non-uniform procedure, and on estimating the information flow from one series to another by means of the corrected conditional entropy. The approach is validated on short realizations of linear stochastic and nonlinear deterministic processes, and then evaluated on heart period, systolic arterial pressure and respira…
A Novel CCT5 Missense Variant Associated with Early Onset Motor Neuropathy
2020
Diseases associated with acquired or genetic defects in members of the chaperoning system (CS) are increasingly found and have been collectively termed chaperonopathies. Illustrative instances of genetic chaperonopathies involve the genes for chaperonins of Groups I (e.g., Heat shock protein 60, Hsp60) and II (e.g., Chaperonin Containing T-Complex polypeptide 1, CCT). Examples of the former are hypomyelinating leukodystrophy 4 (HLD4 or MitCHAP60) and hereditary spastic paraplegia (SPG13). A distal sensory mutilating neuropathy has been linked to a mutation [p.(His147Arg)] in subunit 5 of the CCT5 gene. Here, we describe a new possibly pathogenic variant [p.(Leu224Val)] of the same subunit b…
Antiproliferative Effects of St. John’s Wort, Its Derivatives, and Other Hypericum Species in Hematologic Malignancies
2021
Hypericumis a widely present plant, and extracts of its leaves, flowers, and aerial elements have been employed for many years as therapeutic cures for depression, skin wounds, and respiratory and inflammatory disorders. Hypericum also displays an ample variety of other biological actions, such as hypotensive, analgesic, anti-infective, anti-oxidant, and spasmolytic abilities. However, recent investigations highlighted that this species could be advantageous for the cure of other pathological situations, such as trigeminal neuralgia, as well as in the treatment of cancer. This review focuses on the in vitro and in vivo antitumor effects of St. John’s Wort (Hypericum perforatum), its derivat…