Bibliographies thématiques / Chemometric approaches

Littérature scientifique sur le sujet « Chemometric approaches »

Auteur : Grafiati
Publié le 11 mars 2023

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Articles de revues sur le sujet "Chemometric approaches"

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Roberto de Alvarenga Junior, Benedito, et Renato Lajarim Carneiro. « Chemometrics Approaches in Forced Degradation Studies of Pharmaceutical Drugs ». Molecules 24, no 20 (22 octobre 2019) : 3804. http://dx.doi.org/10.3390/molecules24203804.

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Chemometrics is the chemistry field responsible for planning and extracting the maximum of information of experiments from chemical data using mathematical tools (linear algebra, statistics, and so on). Active pharmaceutical ingredients (APIs) can form impurities when exposed to excipients or environmental variables such as light, high temperatures, acidic or basic conditions, humidity, and oxidative environment. By considering that these impurities can affect the safety and efficacy of the drug product, it is necessary to know how these impurities are yielded and to establish the pathway of their formation. In this context, forced degradation studies of pharmaceutical drugs have been used for the characterization of physicochemical stability of APIs. These studies are also essential in the validation of analytical methodologies, in order to prove the selectivity of methods for the API and its impurities and to create strategies to avoid the formation of degradation products. This review aims to demonstrate how forced degradation studies have been actually performed and the applications of chemometric tools in related studies. Some papers are going to be discussed to exemplify the chemometric applications in forced degradation studies.
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Sohn, Soo-In, Subramani Pandian, Young-Ju Oh, John-Lewis Zinia Zaukuu, Yong-Ho Lee et Eun-Kyoung Shin. « Discrimination of Brassica juncea Varieties Using Visible Near-Infrared (Vis-NIR) Spectroscopy and Chemometrics Methods ». International Journal of Molecular Sciences 23, no 21 (24 octobre 2022) : 12809. http://dx.doi.org/10.3390/ijms232112809.

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Brown mustard (Brassica juncea (L.) is an important oilseed crop that is mostly used to produce edible oils, industrial oils, modified lipids and biofuels in subtropical nations. Due to its higher level of commercial use, the species has a huge array of varieties/cultivars. The purpose of this study is to evaluate the use of visible near-infrared (Vis-NIR) spectroscopy in combination with multiple chemometric approaches for distinguishing four B. juncea varieties in Korea. The spectra from the leaves of four different growth stages of four B. juncea varieties were measured in the Vis-NIR range of 325–1075 nm with a stepping of 1.5 nm in reflectance mode. For effective discrimination, the spectral data were preprocessed using three distinct approaches, and eight different chemometric analyses were utilized. After the detection of outliers, the samples were split into two groups, one serving as a calibration set and the other as a validation set. When numerous preprocessing and chemometric approaches were applied for discriminating, the combination of standard normal variate and deep learning had the highest classification accuracy in all the growth stages achieved up to 100%. Similarly, few other chemometrics also yielded 100% classification accuracy, namely, support vector machine, generalized linear model, and the random forest. Of all the chemometric preprocessing methods, Savitzky–Golay filter smoothing provided the best and most convincing discrimination. The findings imply that chemometric methods combined with handheld Vis-NIR spectroscopy can be utilized as an efficient tool for differentiating B. juncea varieties in the field in all the growth stages.
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Singh, Inderbir, Prateek Juneja, Birender Kaur et Pradeep Kumar. « Pharmaceutical Applications of Chemometric Techniques ». ISRN Analytical Chemistry 2013 (30 octobre 2013) : 1–13. http://dx.doi.org/10.1155/2013/795178.

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Chemometrics involves application of various statistical methods for drawing vital information from various manufacturing-related processes. Multiway chemometric models like parallel factor analysis (PARAFAC), Tucker-3, N-partial least square (N-PLS), and bilinear models like principle component regression (PCR) and partial least squares (PLS) have been discussed in the paper. Chemometric approaches can be used to analyze the data obtained from various instruments including near infrared (NIR), attenuated total reflectance Fourier transform infrared (ATR-FTIR), high-performance liquid chromatography (HPLC), and terahertz pulse spectroscopy. The technique has been used in the quality assurance and quality control of pharmaceutical solid dosage forms. Moreover, application of chemometric methods in the evaluation of properties of pharmaceutical powders and tablet parametric tests has also been discussed in the review. It has been suggested as a useful method for the real-time in-process testing and is a valuable process analytical tool.
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Boyd, J. C. « Perspectives on the use of chemometrics in laboratory medicine. » Clinical Chemistry 32, no 9 (1 septembre 1986) : 1726–33. http://dx.doi.org/10.1093/clinchem/32.9.1726.

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Abstract Today's automated laboratory instruments are capable of generating prodigious volumes of high-quality measurements. Increasingly, the powerful mathematical and statistical methods of chemometrics are being called upon to help reduce these measurements to useful information. Chemometric methods have been important in automating various data-intensive functions of the clinical laboratory, including analysis of cellular images, identification of bacteria and fungi on the basis of their metabolic and chemical properties, and identification of drugs and toxic substances from their mass spectra. These methods also appear promising in aiding both the selection and interpretation of laboratory tests for diagnosis, monitoring, and prognosis. In spite of the demonstrated potential of these methods, significant problems remain to be solved in the areas of measurement standardization, data-base collection, and user familiarity with these approaches before chemometric methods can be used most fully by the clinical laboratory.
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Meade, A. D., H. J. Byrne et F. M. Lyng. « Spectroscopic and chemometric approaches to radiobiological analyses ». Mutation Research/Reviews in Mutation Research 704, no 1-3 (avril 2010) : 108–14. http://dx.doi.org/10.1016/j.mrrev.2010.01.010.

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Sauzier, Georgina, Wilhelm van Bronswijk et Simon W. Lewis. « Chemometrics in forensic science : approaches and applications ». Analyst 146, no 8 (2021) : 2415–48. http://dx.doi.org/10.1039/d1an00082a.

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Dinç, Erdal, A. Hakan Aktaş et Özgür Üstündağ. « New Liquid Chromatographic-Chemometric Approach for the Determination of Sunset Yellow and Tartrazine in Commercial Preparation ». Journal of AOAC INTERNATIONAL 88, no 6 (1 septembre 2005) : 1748–55. http://dx.doi.org/10.1093/jaoac/88.6.1748.

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Abstract A new liquid chromatographic (LC)-chemometric approach was developed for the determination of sunset yellow (SUN) and tartrazine (TAR) in commercial preparations. This approach uses LC and chemometric calibration methods, i.e., classical least-squares (CLS), principal component regression (PCR), and partial–least squares (PLS), simultaneously. The combined LC-chemometric approaches, denoted as LC-CLS, LC-PCR, and LC-PLS, are based on photodiode array (PDA) detection at multiple wavelengths. Optimum chromatographic separation of SUN and TAR with allura red as the internal standard (IS) was obtained by using a Waters Symmetry® C18 column, 5 μm, 4.6 × 250 mm, and 0.2 M acetate buffer (pH 5)–acetonitrile–methanol–bidistilled water (55 + 20 + 15 + 10, v/v) as the mobile phase at a flow rate of 1.9 mL/min. The LC data sets consisting of the ratios of analyte peak areas to the IS peak area were obtained by using PDA detection at 5 wavelengths (465, 470, 475, 480, and 485 nm). LC-chemometric calibrations for SUN and TAR were separately constructed by using the relationship between the peak-area ratio and the training sets for each colorant. LC-chemometric approaches were tested for different synthetic mixtures containing SUN and TAR in the presence of the IS. These LC-chemometric calibrations were applied to a commercial preparation of the 2 colorants. The experimental results of the LC-chemometric approaches were compared with those obtained by a developed classical LC method using single-wavelength detection.
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Ranaweera, Ranaweera K. R., Dimitra L. Capone, Susan E. P. Bastian, Daniel Cozzolino et David W. Jeffery. « A Review of Wine Authentication Using Spectroscopic Approaches in Combination with Chemometrics ». Molecules 26, no 14 (17 juillet 2021) : 4334. http://dx.doi.org/10.3390/molecules26144334.

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In a global context where trading of wines involves considerable economic value, the requirement to guarantee wine authenticity can never be underestimated. With the ever-increasing advancements in analytical platforms, research into spectroscopic methods is thriving as they offer a powerful tool for rapid wine authentication. In particular, spectroscopic techniques have been identified as a user-friendly and economical alternative to traditional analyses involving more complex instrumentation that may not readily be deployable in an industry setting. Chemometrics plays an indispensable role in the interpretation and modelling of spectral data and is frequently used in conjunction with spectroscopy for sample classification. Considering the variety of available techniques under the banner of spectroscopy, this review aims to provide an update on the most popular spectroscopic approaches and chemometric data analysis procedures that are applicable to wine authentication.
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Stöckel, S., S. Meisel, M. Elschner, P. Rösch et J. Popp. « Identification ofBacillus anthracisvia Raman Spectroscopy and Chemometric Approaches ». Analytical Chemistry 84, no 22 (6 novembre 2012) : 9873–80. http://dx.doi.org/10.1021/ac302250t.

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Silva, Carolina S., Maria Fernanda Pimentel, José Manuel Amigo, Carmen García-Ruiz et Fernando Ortega-Ojeda. « Chemometric approaches for document dating : Handling paper variability ». Analytica Chimica Acta 1031 (novembre 2018) : 28–37. http://dx.doi.org/10.1016/j.aca.2018.06.031.

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Thèses sur le sujet "Chemometric approaches"

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Folch, Fortuny Abel. « Chemometric Approaches for Systems Biology ». Doctoral thesis, Universitat Politècnica de València, 2017. http://hdl.handle.net/10251/77148.

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The present Ph.D. thesis is devoted to study, develop and apply approaches commonly used in chemometrics to the emerging field of systems biology. Existing procedures and new methods are applied to solve research and industrial questions in different multidisciplinary teams. The methodologies developed in this document will enrich the plethora of procedures employed within omic sciences to understand biological organisms and will improve processes in biotechnological industries integrating biological knowledge at different levels and exploiting the software packages derived from the thesis. This dissertation is structured in four parts. The first block describes the framework in which the contributions presented here are based. The objectives of the two research projects related to this thesis are highlighted and the specific topics addressed in this document via conference presentations and research articles are introduced. A comprehensive description of omic sciences and their relationships within the systems biology paradigm is given in this part, jointly with a review of the most applied multivariate methods in chemometrics, on which the novel approaches proposed here are founded. The second part addresses many problems of data understanding within metabolomics, fluxomics, proteomics and genomics. Different alternatives are proposed in this block to understand flux data in steady state conditions. Some are based on applications of multivariate methods previously applied in other chemometrics areas. Others are novel approaches based on a bilinear decomposition using elemental metabolic pathways, from which a GNU licensed toolbox is made freely available for the scientific community. As well, a framework for metabolic data understanding is proposed for non-steady state data, using the same bilinear decomposition proposed for steady state data, but modelling the dynamics of the experiments using novel two and three-way data analysis procedures. Also, the relationships between different omic levels are assessed in this part integrating different sources of information of plant viruses in data fusion models. Finally, an example of interaction between organisms, oranges and fungi, is studied via multivariate image analysis techniques, with future application in food industries. The third block of this thesis is a thoroughly study of different missing data problems related to chemometrics, systems biology and industrial bioprocesses. In the theoretical chapters of this part, new algorithms to obtain multivariate exploratory and regression models in the presence of missing data are proposed, which serve also as preprocessing steps of any other methodology used by practitioners. Regarding applications, this block explores the reconstruction of networks in omic sciences when missing and faulty measurements appear in databases, and how calibration models between near infrared instruments can be transferred, avoiding costs and time-consuming full recalibrations in bioindustries and research laboratories. Finally, another software package, including a graphical user interface, is made freely available for missing data imputation purposes. The last part discusses the relevance of this dissertation for research and biotechnology, including proposals deserving future research.
Esta tesis doctoral se centra en el estudio, desarrollo y aplicación de técnicas quimiométricas en el emergente campo de la biología de sistemas. Procedimientos comúnmente utilizados y métodos nuevos se aplican para resolver preguntas de investigación en distintos equipos multidisciplinares, tanto del ámbito académico como del industrial. Las metodologías desarrolladas en este documento enriquecen la plétora de técnicas utilizadas en las ciencias ómicas para entender el funcionamiento de organismos biológicos y mejoran los procesos en la industria biotecnológica, integrando conocimiento biológico a diferentes niveles y explotando los paquetes de software derivados de esta tesis. Esta disertación se estructura en cuatro partes. El primer bloque describe el marco en el cual se articulan las contribuciones aquí presentadas. En él se esbozan los objetivos de los dos proyectos de investigación relacionados con esta tesis. Asimismo, se introducen los temas específicos desarrollados en este documento mediante presentaciones en conferencias y artículos de investigación. En esta parte figura una descripción exhaustiva de las ciencias ómicas y sus interrelaciones en el paradigma de la biología de sistemas, junto con una revisión de los métodos multivariantes más aplicados en quimiometría, que suponen las pilares sobre los que se asientan los nuevos procedimientos aquí propuestos. La segunda parte se centra en resolver problemas dentro de metabolómica, fluxómica, proteómica y genómica a partir del análisis de datos. Para ello se proponen varias alternativas para comprender a grandes rasgos los datos de flujos metabólicos en estado estacionario. Algunas de ellas están basadas en la aplicación de métodos multivariantes propuestos con anterioridad, mientras que otras son técnicas nuevas basadas en descomposiciones bilineales utilizando rutas metabólicas elementales. A partir de éstas se ha desarrollado software de libre acceso para la comunidad científica. A su vez, en esta tesis se propone un marco para analizar datos metabólicos en estado no estacionario. Para ello se adapta el enfoque tradicional para sistemas en estado estacionario, modelando las dinámicas de los experimentos empleando análisis de datos de dos y tres vías. En esta parte de la tesis también se establecen relaciones entre los distintos niveles ómicos, integrando diferentes fuentes de información en modelos de fusión de datos. Finalmente, se estudia la interacción entre organismos, como naranjas y hongos, mediante el análisis multivariante de imágenes, con futuras aplicaciones a la industria alimentaria. El tercer bloque de esta tesis representa un estudio a fondo de diferentes problemas relacionados con datos faltantes en quimiometría, biología de sistemas y en la industria de bioprocesos. En los capítulos más teóricos de esta parte, se proponen nuevos algoritmos para ajustar modelos multivariantes, tanto exploratorios como de regresión, en presencia de datos faltantes. Estos algoritmos sirven además como estrategias de preprocesado de los datos antes del uso de cualquier otro método. Respecto a las aplicaciones, en este bloque se explora la reconstrucción de redes en ciencias ómicas cuando aparecen valores faltantes o atípicos en las bases de datos. Una segunda aplicación de esta parte es la transferencia de modelos de calibración entre instrumentos de infrarrojo cercano, evitando así costosas re-calibraciones en bioindustrias y laboratorios de investigación. Finalmente, se propone un paquete software que incluye una interfaz amigable, disponible de forma gratuita para imputación de datos faltantes. En la última parte, se discuten los aspectos más relevantes de esta tesis para la investigación y la biotecnología, incluyendo líneas futuras de trabajo.
Aquesta tesi doctoral es centra en l'estudi, desenvolupament, i aplicació de tècniques quimiomètriques en l'emergent camp de la biologia de sistemes. Procediments comúnment utilizats i mètodes nous s'apliquen per a resoldre preguntes d'investigació en diferents equips multidisciplinars, tant en l'àmbit acadèmic com en l'industrial. Les metodologies desenvolupades en aquest document enriquixen la plétora de tècniques utilitzades en les ciències òmiques per a entendre el funcionament d'organismes biològics i milloren els processos en la indústria biotecnològica, integrant coneixement biològic a distints nivells i explotant els paquets de software derivats d'aquesta tesi. Aquesta dissertació s'estructura en quatre parts. El primer bloc descriu el marc en el qual s'articulen les contribucions ací presentades. En ell s'esbossen els objectius dels dos projectes d'investigació relacionats amb aquesta tesi. Així mateix, s'introduixen els temes específics desenvolupats en aquest document mitjançant presentacions en conferències i articles d'investigació. En aquesta part figura una descripació exhaustiva de les ciències òmiques i les seues interrelacions en el paradigma de la biologia de sistemes, junt amb una revisió dels mètodes multivariants més aplicats en quimiometria, que supossen els pilars sobre els quals s'assenten els nous procediments ací proposats. La segona part es centra en resoldre problemes dins de la metabolòmica, fluxòmica, proteòmica i genòmica a partir de l'anàlisi de dades. Per a això es proposen diverses alternatives per a compendre a grans trets les dades de fluxos metabòlics en estat estacionari. Algunes d'elles estàn basades en l'aplicació de mètodes multivariants propostos amb anterioritat, mentre que altres són tècniques noves basades en descomposicions bilineals utilizant rutes metabòliques elementals. A partir d'aquestes s'ha desenvolupat software de lliure accés per a la comunitat científica. Al seu torn, en aquesta tesi es proposa un marc per a analitzar dades metabòliques en estat no estacionari. Per a això s'adapta l'enfocament tradicional per a sistemes en estat estacionari, modelant les dinàmiques dels experiments utilizant anàlisi de dades de dues i tres vies. En aquesta part de la tesi també s'establixen relacions entre els distints nivells òmics, integrant diferents fonts d'informació en models de fusió de dades. Finalment, s'estudia la interacció entre organismes, com taronges i fongs, mitjançant l'anàlisi multivariant d'imatges, amb futures aplicacions a la indústria alimentària. El tercer bloc d'aquesta tesi representa un estudi a fons de diferents problemes relacionats amb dades faltants en quimiometria, biologia de sistemes i en la indústria de bioprocessos. En els capítols més teòrics d'aquesta part, es proposen nous algoritmes per a ajustar models multivariants, tant exploratoris com de regressió, en presencia de dades faltants. Aquests algoritmes servixen ademés com a estratègies de preprocessat de dades abans de l'ús de qualsevol altre mètode. Respecte a les aplicacions, en aquest bloc s'explora la reconstrucció de xarxes en ciències òmiques quan apareixen valors faltants o atípics en les bases de dades. Una segona aplicació d'aquesta part es la transferència de models de calibració entre instruments d'infrarroig proper, evitant així costoses re-calibracions en bioindústries i laboratoris d'investigació. Finalment, es proposa un paquet software que inclou una interfície amigable, disponible de forma gratuïta per a imputació de dades faltants. En l'última part, es discutixen els aspectes més rellevants d'aquesta tesi per a la investigació i la biotecnologia, incloent línies futures de treball.
Folch Fortuny, A. (2016). Chemometric Approaches for Systems Biology [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/77148
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Guan, Pingping. « Class I HLA supertype and supermotif definition by chemometric approaches ». Thesis, University College London (University of London), 2005. http://discovery.ucl.ac.uk/1445534/.

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Activation of cytotoxic T cells in human requires specific binding of antigenic peptides to human leukocyte antigen (HLA) molecules. HLA is the most polymorphic protein in the human body, currently 1814 different alleles collected in the HLA sequence database at the European Bioinformatics Institute. Most of the HLA molecules recognise different peptides. Also, some peptides can be recognised by several of HLA molecules. In the present project, all available class I HLA alleles are classified into supertypes. Super - binding motifs for peptides binding to some supertypes are defined where binding data are available. A variety of chemometric techniques are used in the project, including 2D and 3D QSAR techniques and different variable selection methods like SIMCA, GOLPE and genetic algorithm. Principal component analysis combined with molecular interaction fields calculation by the program GRID is used in the class I HLA classification. This thesis defines an HLA-A3 supermotif using two QSAR methods: the 3D-QSAR method CoMSIA, and a recently developed 2D-QSAR method, which is named the additive method. Four alleles with high phenotype frequency were included in the study: HLA-A*0301, HLA-A*1101, HLA-A*3101 and HLA- A*6801. An A*020T binding motif is also defined using amino acid descriptors and variable selection methods. Novel peptides have been designed according to the motifs and the binding affinity is tested experimentally. The results of the additive method are used in the online server, MHCPred, to predict binding affinity of unknown peptides. In HLA classification, the HLA-A, B and C molecules are classified into supertypes separately. A total of eight supertypes are observed for class I HLA, including A2, A3, A24, B7, B27, B44, CI and C4 supertype. Using the HLA classification, any newly discovered class I HLA molecule can be grouped into a supertype easily, thus simplifying the experimental function characterisation process.
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Stubbins, Frederick John. « Addressing the challenges of crude oil processing utilising chemometric approaches ». Thesis, University of Newcastle upon Tyne, 2018. http://hdl.handle.net/10443/4047.

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Throughout the hydrocarbon supply chain, process optimisation is driven by the desire to maximise profit margins. In the global refining marketplace, the biggest cost is crude oil and to improve margins increasing use of non-conventional crude oils (also called opportunity crudes) lowers the cost of the crude blend. Opportunity crudes are selected based on market forces, for example in North America, the production booms in shale oil and tar sands have provided ample amounts of new low-cost oils which refineries are buying and processing. However, as these oils are new to the marketplace many refineries have never processed them before which brings about challenges. These are mainly a lack of understanding of the quality of the crude oil being processed (shale oils for example can come from many thousands of wells) and how these oils interact with the more conventional refinery feedstocks (such as Brent or West Texas Intermediate). The Eng.D project was carried out in collaboration with Intertek Group plc, a multinational corporate organisation consisting of more than 42,000 employees in over 1,000 locations in over 100 countries across the globe, and was aimed at developing solutions to address crude oil processing problems. The issues covered over the course of the project fall into the areas of: enhancing understanding of crude oil quality, addressing issues of hydrocarbon blend stability because of blending and better utilisation of process data to promote efficiency and facilitate process troubleshooting. As such, the Eng.D project was firstly concerned with developing a robust chemometric model, based on Near Infrared spectra, for use in a major Asian refinery. Once built and tuned this model was ultimately used to predict physical properties (such as density, sulphur content and distillation properties) of every crude oil delivery and also online in the refinery for frequent prediction of crude oil blend properties. The second project was then aimed at solving refinery issues of the deposition of undesirable material (such as wax and asphaltenes) in pipes and process units. The research carried out during the course of the Eng.D project resulted in a patented approach to characterise these issues and provide refineries strategies to mitigate the problems. This approach is not just limited to crude oils but can be applied to any blended hydrocarbon streams and detects the precipitation of undesirable material using Near Infrared spectroscopy and microscopy. This ii approach has now been applied to solving problems of blending crude oils in refineries and offshore, heavy fuel oils, shale oils and marine fuels. Finally, the application of smart data analytics in an upstream installation was investigated. The objective of this application was to provide a customer with process troubleshooting for a historical recurring pump failure issue. To achieve this, the root cause of the issue first needed to be identified and then a solution developed.
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Teague, Claire Rachel. « NMR spectroscopic and chemometric approaches to investigate metabolic variation in biofluids ». Thesis, Imperial College London, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.414749.

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Herranz-Trillo, Fatima. « Disentangling structural complexity in proteins by decomposing SAXS data with chemometric approaches ». Thesis, Montpellier, 2017. http://www.theses.fr/2017MONTT044/document.

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De nombreux systèmes biologiques sont intrinsèquement polydispersés, présentant de multiples espèces coexistantes, de taille, de forme ou de conformation différentes (c'est-à-dire, mélanges oligomèriques, des complexes faiblement liés se dissociant en composantes individuelles ou des espèces apparaissant lors de processus amyloïdogéniques). L'étude de tels systèmes complexes est une tâche difficile en raison de l'instabilité des espèces concernées, de leurs concentrations relatives faibles et interdépendantes et des difficultés rencontrées pour l'isolation des composantes pures. Dans cette thèse, j'ai développé des approches méthodologiques pour appliquer la diffusion des rayons X aux petits angles (SAXS), une technique de biologie structurale, à l'étude de systèmes polydispersés. SAXS est une technique additive et par conséquent, le diagramme de diffusion mesuré pour un échantillon polydispersé correspond à la somme pondérée en concentration des contributions de chacune des composantes individuelles du mélange. Cependant, la décomposition des données de SAXS en des spectres spécifiques des espèces et de leurs concentrations relatives est extrêmement laborieuse et ambigue. Dans cette thèse, je présente d'abord une approche objective pour solidement décomposer les jeux de données de SAXS en composantes individuelles. Cette approche adapte la méthode chimiométrique « Multivariable Curve Resolution Alternate Least Squares » (MCR-ALS) aux spécificités des données de SAXS. Notre méthode permet une décomposition rigoureuse et robuste des données de SAXS en introduisant simultanément différentes représentations de ces données et par conséquent, en mettant l'accent sur des changements moléculaires à différentes plages de temps et de résolution structurale. Nous avons appliqué cette approche, que nous appelons COSMiCS (Analyse structurelle objective complexe des systèmes multi-composants) pour étudier deux systèmes polydispersés: la fibrillation des protéines, et les fluctuations conformationnelles de protéines grâce à l'analyse de données obtenues à l'aide d’une technique de couplage de chromatographie d'exclusion de taille (SEC) avec le ligne de SAXS (SEC-SAXS). L'importance d'étudier les processus de fibrillation réside dans leur implication dans des pathologies amyloïdogéniques telles que les maladies de Parkinson ou d'Alzheimer. Il existe de fortes indications que les espèces oligomériques solubles, et non les fibrilles matures, sont la cause principale de la cytotoxicité et des dommages neuronaux. Cette observation souligne l'importance de caractériser les premiers stades des processus de fibrillation. Notre approche COSMiCS a permis d'étudier les processus amyloïdogéniques de l'insuline et du mutant familial E46K de l'α-synucléine, une protéine associée à la maladie de Parkinson. Cette analyse permet la caractérisation structurale des espèces présentes (y compris les espèces oligomériques) et la caractérisation cinétique de leurs transformations.La deuxième partie de la thèse est consacrée à l'utilisation de COSMiCS pour analyser des données de SEC-SAXS. Le SEC-SAXS est extrêmement populaire et a été implémenté sur plusieurs lignes de SAXS à travers le monde. En utilisant des données synthétiques, je démontre la capacité des approches chimiométriques à décomposer des profils chromatographiques complexes. À l'aide de cette approche, j'ai décomposé l’ensemble des données SEC-SAXS mesurés pour la Prolyl OligoPeptidase (POP).En résumé, cette thèse présente une nouvelle approche chimiométrique qui peut être généralement appliquée à tout mélange macromoléculaire pouvant subir une modifacation de son équilibre et pouvant être abordé par SAXS. Les complexes biomoleculaires transitoires, les processus de repliement, les réarrangements structuraux dépendants d’un ligand ou la formation de grands ensembles supramoleculaires peuvent être sondés de façon structurale en utilisant l'approche COSMiCS
Many biological systems are inherently polydisperse, presenting multiple coexisting species differing in size, shape or conformation (i.e. oligomeric mixtures, weakly bound complexes, and species appearing along amyloidogenic processes). The study of such complex systems is challenging due to the instability of the species involved, their low and interdependent relative concentrations, and the difficulties to isolate the pure components. In this thesis, I have developed methodological approaches to apply Small-Angle X-ray Scattering (SAXS), a low-resolution structural biology technique, to the study of polydisperse systems. As an additive technique, the SAXS pattern measured for a polydisperse sample corresponds to the concentration-weighted sum of the contributions from each of the individual components. However, decomposition of SAXS data into species-specific spectra and relative concentrations is laborious and burdened by ambiguity. In this thesis, I present an approach to decompose SAXS datasets into the individual components. This approach adapts the chemometrics Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) method to the specificities of SAXS data. Our method enables the rigorous and robust decomposition of SAXS data by simultaneously introducing different representations of these data and, consequently, emphasizing molecular changes at different time and structural resolution ranges. We have applied this approach, which we name COSMiCS (Complex Objective Structural analysis of Multi-Component Systems), to study two polydisperse systems: amyloid fibrillation by analysing time-dependent SAXSdata, and conformational fluctuations through the analysis of data obtained using on-line size-exclusion chromatography coupled to SAXS (SEC-SAXS). The importance of studying fibrillation processes lies in their implication in amyloidogenic pathologies such as Parkinson’s or Alzheimer’s diseases. There exist strong indications that soluble oligomeric species, and not mature fibrils, are the main cause of cytotoxicity and neuronal damage emphasizing the importance of characterizing early stages of fibrillation. The first application of our COSMiCS approach has allowed the study of the amyloidogenic mechanisms of insulin and the familial mutant E46K of ↵-synuclein, a Parkinson’s disease related protein. The analysis enables the structural characterization of all the species present as well as their kinetic transformations. The second part of the thesis is dedicated to the use of COSMiCS to analyze on-line SEC-SAXS experiments. Using synthetic data, I demonstrate the capacity of chemometric approaches to decompose complex chromatographic profiles. Using this approach, I have studied the conformational fluctuations in prolyl oligopeptidase (POP), a protein related to synaptic functions and neuronal development. In summary, this thesis presents a novel chemometrics approach that can be generally applied to any macromolecular mixture with a tuneable equilibrium that is amenableto SAXS. Transient biomolecular complexes, folding processes, or ligand-dependent structural rearrangements can be probed structurally using COSMiCS
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Vestner, Jochen. « New Chemometric Approaches to Non-targeted GCMS Fingerprinting Analysis of Wine Volatiles ». Thesis, Bordeaux, 2016. http://www.theses.fr/2016BORD0141/document.

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Contrairement à l’analyse ciblée des composés volatils du vin par chromatographie en phase gazeuse couplée à la spectrométrie de masse (GC-MS), les approches par GC-MS non ciblées prennent en compte les composés connus et inconnus. Ces méthodes sont plus rapides et fournissent une représentation plus complète de la composition de l’échantillon. Bien que plusieurs approches non-ciblées aient été développées, il y a encore une forte demande d’outils automatisés pour le traitement des données, en particulier pour les données multidimensionnelles complexes telles que celles de multiples chromatogrammes GC-MS. Ce travail visait à développer deux nouvelles approches chimiométriques pour l’analyse des données GC-MS non ciblées. Ces approches prennent en considération les décalages de temps de rétention entre les échantillons et rendent inutile l’intégration des pics. Elles ont été testées avec un jeu de données GC-MS simulées et un jeu de données GC-MS réelles d’échantillons de vin. De plus, l’une des deux approches GC-MS non ciblée a été combinée à la technique d’analyse sensorielle rapide de "projective mapping". Cette méthodologie a été utilisée pour étudier l’impact de la fermentation malolactique sur des vins issus du cépage Pinotage ainsi que l’effet de l’âge de la vigne, de la turbidité du moût et de la souche de levure sur l’arôme de vins de Riesling expérimentaux
In contrast to targeted gas chromatography mass spectrometry (GC-MS) analysis of wine volatiles, non-targeted GC-MS approaches take information of known and unknown compounds into account, are faster, inherently more comprehensive and give a more holistic representation of the sample composition. Although several non-targeted approaches have been developed, there is still a great demand for automated data processing tools, especially for complex multi-way data such as chromatographic data obtained from multichannel detectors (e.g. GC-MS chromatograms of multiple samples). This work therefore aimed at the development of data processing procedures for non-targeted GC-MS analysis of volatile wine compounds. The two developed approaches use basic matrix manipulation of segmented GC-MS chromatograms and PCA or PARAFAC multi-way modelling. The approaches take retention time shifts between samples into account and avoid peak integration. A demonstration of the new fingerprinting approaches is presented using an artificial GC-MS data set and an experimental full-scan GC-MS data set obtained for a set of experimental wines. Results of the new approaches were also compared to a references method. Furthermore, the combination of one of the developed GC-MS fingerprinting approaches with the fast sensory screening technique projective mapping was exploited as a powerful approach to simultaneously study the volatile composition and the sensory characteristics of experimental wines. This methodology was used to study the impact of different malolactic fermentation scenarios on two different Pinotage wine styles and for a full factorial investigation of the impact of grape vine age, must turbidity and yeast strain on the aroma of Riesling experimental wines
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BACCOLO, GIACOMO. « Chemometrics approaches for the automatic analysis of metabolomics GC-MS data ». Doctoral thesis, Università degli Studi di Milano-Bicocca, 2022. http://hdl.handle.net/10281/374731.

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La metabolomica, che consiste nella identificazione di tutti i metaboliti presenti all’interno dei campioni biologici analizzati, è un approccio ampiamente applicato in diversi campi di ricerca quali: identificazione di biomarcatori, sviluppo di nuovi farmaci, scienze alimentari e ambientali. La metabolomica è strettamente legata alla capacità di tecniche analitiche fra queste una delle più applicate è la gas cromatografia accoppiata alla spettrometria di massa. Moderne piattaforme analitiche possono generare centinaia di migliaia di spettri, rilevando una quantità impressionante di molecole distinte. Nonostante i progressi tecnici raggiunti sul lato sperimentale, la conversione dei segnali misurati dagli strumenti in informazioni utili non è un passaggio scontato in studi metabolomici. Per ogni composto identificato, l’obbiettivo è ottenere la concentrazione relativa tra tutti i campioni analizzati e lo spettro di massa associato al composto, necessario per l’identificazione della molecola stessa. I software disponibili per l’analisi dei dati sperimentali sono stati ripetutamente indicati come una fonte importante di incertezza, limitando fortemente sia la quantità che la qualità delle informazioni estratte. Gli strumenti più applicati richiedono l’impostazione di diversi parametri da parte dell’operatore, influenzando il risultato dell’analisi. In questa tesi è descritto un nuovo approccio, chiamato AutoDise, per l’analisi dei dati GC-MS. L’elaborazione dei segnali sperimentali si basa su PARAFAC2. PARAFAC2 è un modello che scompone dati multidimensionali, discriminando tra i diversi segnali nei campioni. Grazie alle sue proprietà, PARAFAC2 non ha bisogno che i dati siano pretrattati e non richiede di impostare parametri, mentre software utilizzati in questo ambito richiedono di definire diversi parametri e un laborioso pretrattamento dei dati, richiedendo l’intervento di un utente esperto, inoltre la riproducibilità dei risultati è limitata, dipendendo i parametri scelti dall’utente. Tuttavia, il fitting di modelli PARAFAC2 coinvolge diverse fasi ed è necessario un esperto analista per l’analisi e l’interpretazione dei modelli. AutoDise è un sistema esperto in grado di gestire tutti i passaggi riguardanti la modellazione e di generare una tabella dei picchi in cui ogni composto è identificato in modo univoco, con risultati completamente riproducibili. Questo è possibile grazie alla combinazione di diversi strumenti diagnostici e grazie all’ applicazione di modelli d’intelligenza artificiale. Le prestazioni dell’approccio sono state testate su un complesso dataset di oli d’oliva ottenuto tramite analisi GC-MS. I dati sono stati analizzati sia manualmente, da utenti esperti, sia automaticamente con il metodo AutoDise proposto e le tabelle dei picchi risultanti sono state confrontate. I risultati mostrano che AutoDise supera l’analisi manuale sia in termini di numero di composti identificati che di qualità dell’identificazione e della quantificazione. Inoltre, è stata sviluppata una GUI per rendere l’algoritmo più accessibile a persone non esperte nel linguaggio di programmazione. La tesi include un tutorial che mostra le caratteristiche principali e come utilizzare l’interfaccia grafica. Un’altra parte importante della tesi è stata dedicata al test e allo sviluppo di nuove reti neurali artificiali da implementare nel software AutoDise per rilevare quali componenti PARAFAC2 stanno fornendo informazioni chimicamente utili. A tal fine, più di 170.000 profili sono stati etichettati manualmente, al fine di addestrare, validare e testare una rete neurale convoluzionale e una rete bilineare con memoria a breve termine e un modello k-nearest neighbour. I risultati suggeriscono che le reti di deep learning possono essere efficacemente applicate per la classificazione automatica dei profili cromatografici.
Metabolomics, which consists of identifying all the metabolites present in the biological samples analysed, is an approach widely applied in various research fields such as biomarker identification, new drug development, food and environmental sciences. Metabolomics is closely linked to the ability of analytical techniques, one of the most widely applied being gas chromatography coupled to mass spectrometry. Modern analytical platforms can generate hundreds of thousands of spectra, detecting an impressive number of distinct molecules. Despite the technical progress achieved on the experimental side, the conversion of signals measured by instruments into useful information is not an obvious step in metabolomic studies. For each identified compound, the goal is to obtain the relative concentration among all analysed samples and the mass spectrum associated with the compound needed to identify the molecule itself. The software available for analysing experimental data has repeatedly been cited as a major source of uncertainty, severely limiting both the quantity and quality of the information extracted. The most applied tools are based on univariate data analysis, considering each sample separately from the others and requiring the operator to set several parameters, affecting the result of the analysis. In this thesis, a new approach, called AutoDise, for the analysis of GC-MS data is described. The processing of the experimental signals is based on PARAFAC2. PARAFAC2 is a model that decomposes multidimensional data, discriminating between different signals in the samples. Due to its properties, PARAFAC2 does not need the data to be pre-processed and does not require parameters to be set, whereas software used in this field requires several parameters to be defined and laborious pre-processing of the data, requiring the intervention of an expert user, and the reproducibility of the results is limited, depending on the parameters chosen by the user. However, fitting PARAFAC2 models involves several steps and an experienced analyst is needed to analyse and interpret the models. AutoDise is an expert system capable of handling all modelling steps and generating a peak table in which each compound is uniquely identified, with fully reproducible results. This is possible thanks to the combination of different diagnostic tools and the application of artificial intelligence models. The performance of the approach was tested on a complex dataset of olive oils obtained by GC-MS analysis. The data were analysed both manually, by experienced users, and automatically with the proposed AutoDise method and the resulting peak tables were compared. The results show that AutoDise outperforms manual analysis both in terms of the number of compounds identified and the quality of identification and quantification. In addition, a GUI was developed to make the algorithm more accessible to people not skilled in the programming language. The thesis includes a tutorial showing the main features and how to use the GUI. Another important part of the thesis was devoted to testing and developing new artificial neural networks to be implemented in the AutoDise software to detect which PARAFAC2 components are providing chemically useful information. To this end, more than 170,000 profiles were manually labelled in order to train, validate and test a convolutional neural network and a bilinear network with short-term memory and a k-nearest neighbour model. The results suggest that deep learning networks can be effectively applied for the automatic classification of chromatographic profiles.
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Ryabchykov, Oleg [Verfasser], Jürgen [Gutachter] Popp et Thomas Wilhelm [Gutachter] Bocklitz. « Investigations on chemometric approaches for diagnostic applications utilizing various combinations of spectral and image data types / Oleg Ryabchykov ; Gutachter : Jürgen Popp, Thomas Wilhelm Bocklitz ». Jena : Friedrich-Schiller-Universität Jena, 2019. http://d-nb.info/1206604719/34.

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Ceci, Adriana Teresa. « Measuring the nutritional quality of local plant-based EUREGIO foods ». Doctoral thesis, Università degli studi di Trento, 2022. https://hdl.handle.net/11572/355331.

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In the recent years, the consumer choices have been focused on health-promoting plant-based food and their preferences are oriented towards regional foodstuff from local productions. Therefore, an important factor for vegetables grown Trentino-Alto Adige (Italy) is to point out the added value of alpine farming to evaluate the nutritional values of farming products. Omics technologies (e.g. genomics, transcriptomics, proteomics and metabolomics) are aimed at investigating the assessment of different pools of molecules and how they are translated into the structure, function, and dynamics of a biological system or systems in order to provide a comprehensive characterization of a specific organism. Research use the omics techniques to exhaustively understand the functionality of food components. Several sophisticated chromatographic methods, spectroscopic techniques and chemometric tools are applied to give an insight into a comprehensive overview of the intrinsic quality, typicality and regionality of specific plant-based foods in the present PhD thesis: apples and potatoes. The quality of these foods is evaluated by quantifying the secondary metabolites to investigate their nutraceutical values. The aim of this PhD project is to use several analytical techniques (LC-MS, UV-VIS) that are capable of comprehensively characterizing the food metabolome with particular emphasis on those components with high nutritional values. The data analysis and data handling of omics data requires advanced bioinformatic, statistical, and chemometric tools. Potatoes and apples are chosen as target matrices for these studies for their relevance in the local economy and for the peculiar chemical composition of particular interest for their health-promoting proprieties. The information is acquired using several sophisticated chromatographic and spectroscopic techniques, such as ultra-high performance liquid chromatography coupled with triple quadrupole mass spectrometry (UHPLC– MS/MS) and UV/VIS. It is integrated to chemometric approaches (principal component analysis (PCA), partial least square regression (PLS), and data fusion) to achieve a comprehensive targeted chemical characterization. The sampling procedures gathers, in the case of the potatoes study, reference cultivars that may be found in the common retailers of Trentino/Alto-Adige and different production areas, the apples of 22 cultivars were harvest from the fields of the Laimburg Research Centre (Vadena, Italy) to guaranty comparability of the obtained data. Our results may be used as solid foundation for a reliable evaluation of apples and potatoes healthy "potential" value based on cutting-edge techniques, which are capable of providing comprehensive data regarding the alpine food quality parameters with high efficiency and reliability
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Mörén, Lina. « Metabolomics and proteomics studies of brain tumors : a chemometric bioinformatics approach ». Doctoral thesis, Umeå universitet, Kemiska institutionen, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-111309.

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The WHO classification of brain tumors is based on histological features and the aggressiveness of the tumor is classified from grade I to IV, where grade IV is the most aggressive. Today, the correlation between prognosis and tumor grade is the most important component in tumor classification. High grade gliomas, glioblastomas, are associated with poor prognosis and a median survival of 14 months including all available treatments. Low grade meningiomas, usually benign grade I tumors, are in most cases cured by surgical resection. However despite their benign appearance grade I meningiomas can, without any histopathological signs, in some cases develop bone invasive growth and become lethal. Thus, it is necessary to improve conventional treatment modalities, develop new treatment strategies and improve the knowledge regarding the basic pathophysiology in the classification and treatment of brain tumors. In this thesis, both proteomics and metabolomics have been applied in the search for biomarkers or biomarker patterns in two different types of brain tumors, gliomas and meningiomas. Proteomic studies were carried out mainly by surface enhanced laser desorption ionization time of flight mass spectrometry (SELDI-TOF-MS). In one of the studies, isobaric tags for relative and absolute quantitation (iTRAQ) labeling in combination with high-performance liquid chromatography (HPLC) was used for protein detection and identification. For metabolomics, gas-chromatography time-of-flight mass spectrometry (GC-TOF-MS) has been the main platform used throughout this work for generation of robust global metabolite profiles in tissue, blood and cell cultures. To deal with the complexity of the generated data, and to be able to extract relevant biomarker patters or latent biomarkers, for interpretation, prediction and prognosis, bioinformatic strategies based on chemometrics were applied throughout the studies of the thesis. In summary, we detected differentiating protein profiles between invasive and non-invasive meningiomas, in both fibrous and meningothelial tumors. Furthermore, in a different study we discovered treatment induce protein pattern changes in a rat glioma model treated with an angiogenesis inhibitor. We identified a cluster of proteins linked to angiogenesis. One of those proteins, HSP90, was found elevated in relation to treatment in tumors, following ELISA validation. An interesting observation in a separate study was that it was possible to detect metabolite pattern changes in the serum metabolome, as an effect of treatment with radiotherapy, and that these pattern changes differed between different patients, highlighting a possibility for monitoring individual treatment response.  In the fourth study of this work, we investigated tissue and serum from glioma patients that revealed differences in the metabolome between glioblastoma and oligodendroglioma, as well as between oligodendroglioma grade II and grade III. In addition, we discovered metabolite patterns associated to survival in both glioblastoma and oligodendroglioma. In our final work, we identified metabolite pattern differences between cell lines from a subgroup of glioblastomas lacking argininosuccinate synthetase (ASS1) expression, (ASS1 negative glioblastomas), making them auxotrophic for arginine, a metabolite required for tumor growth and proliferation, as compared to glioblastomas with normal ASS1 expression (ASS1 positive). From the identified metabolite pattern differences we could verify the hypothesized alterations in the arginine biosynthetic pathway. We also identified additional interesting metabolites that may provide clues for future diagnostics and treatments. Finally, we were able to verify the specific treatment effect of ASS1 negative cells by means of arginine deprivation on a metabolic level.
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Livres sur le sujet "Chemometric approaches"

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1949-, Morgan Stephen L., dir. Experimental design : A chemometric approach. Amsterdam : Elsevier, 1987.

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Deming, Stanley N. Experimental design : A chemometric approach. Amsterdam : Elsevier, 1987.

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Deming, Stanley N. Experimental design : A chemometric approach. 2e éd. Amsterdam : Elsevier, 1993.

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Structure and retention in chromatography : A chemometric approach. Amsterdam, Netherlands : Harwood Academic Publishers, 1997.

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Vladimír, Štěpánek, dir. Analytical measurement and information : Advances in the information theoretic approach to chemical analyses. Letchworth, Hertfordshire, England : Research Studies Press, 1985.

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Experimental design : a chemometric approach. Elsevier, 1993. http://dx.doi.org/10.1016/s0922-3487(08)x7001-7.

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Experimental Design : A Chemometric Approach. Elsevier, 1987. http://dx.doi.org/10.1016/s0922-3487(08)x7012-1.

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Morgan, S. L., et S. N. Deming. Experimental Design : A Chemometric Approach. Elsevier Science & Technology Books, 1993.

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Morgan, S. L., et S. N. Deming. Experimental Design : A Chemometric Approach. Elsevier Science & Technology Books, 1987.

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Chapitres de livres sur le sujet "Chemometric approaches"

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Morita, Kae, et Tetsuo Aishima. « Sensometric and Chemometric Approaches to Seafood Flavour ». Dans Handbook of Seafood Quality, Safety and Health Applications, 39–49. Oxford, UK : Wiley-Blackwell, 2010. http://dx.doi.org/10.1002/9781444325546.ch4.

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Bocklitz, Thomas, Michael Schmitt et Jürgen Popp. « Image Processing-Chemometric Approaches to Analyze Optical Molecular Images ». Dans Ex-vivo and In-vivo Optical Molecular Pathology, 215–48. Weinheim, Germany : Wiley-VCH Verlag GmbH & Co. KGaA, 2014. http://dx.doi.org/10.1002/9783527681921.ch7.

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Halder, Amit Kumar, Ana S. Moura et M. Natália D. S. Cordeiro. « Advanced Chemometric Modeling Approaches for the Design of Multitarget Drugs Against Neurodegenerative Diseases ». Dans Methods in Pharmacology and Toxicology, 155–86. New York, NY : Springer New York, 2018. http://dx.doi.org/10.1007/7653_2018_14.

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Adami, G., F. Aleffi, P. Barbieri, A. Favretto, S. Predonzani et E. Reisenhofer. « Bivalves and Heavy Metals in Polluted Sediments : A Chemometric Approach ». Dans The Interactions Between Sediments and Water, 615–22. Dordrecht : Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-011-5552-6_62.

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Vasić, Milica V., Zagorka Radojević et Lato Pezo. « Application of Organic and Inorganic Wastes in Clay Brick Production : A Chemometric Approach ». Dans Advanced Ceramic Materials, 300–335. Hoboken, NJ, USA : John Wiley & Sons, Inc., 2016. http://dx.doi.org/10.1002/9781119242598.ch8.

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Kookana, Rai S., Riaz Ahmad et Annemieke Farenhorst. « Sorption of Pesticides and its Dependence on Soil Properties : Chemometrics Approach for Estimating Sorption ». Dans ACS Symposium Series, 221–40. Washington, DC : American Chemical Society, 2014. http://dx.doi.org/10.1021/bk-2014-1174.ch012.

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Tomassetti, Mauro, Federico Marini, Riccardo Angeloni, Mauro Castrucci et Luigi Campanella. « New Chemometric Approach Using Data Obtained by a DMFC Device to Qualitatively and Quantitatively Determine Organic Molecules ». Dans Lecture Notes in Electrical Engineering, 21–27. Cham : Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-37558-4_4.

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Rutledge, D. N., C. Chararas et C. J. Ducauze. « Investigating the Hypothesis of Primary Attraction in Conifer-Specific Scolytidae Using a Chemometrical Approach ». Dans Mechanisms of Woody Plant Defenses Against Insects, 391–409. New York, NY : Springer New York, 1988. http://dx.doi.org/10.1007/978-1-4612-3828-7_27.

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Tong, Weida, Huixiao Hong, Hong Fang, Qian Xie, Roger Perkins et John D. Walker. « From Decision Tree to Heterogeneous Decision Forest : A Novel Chemometrics Approach for Structure-Activity Relationship Modeling ». Dans ACS Symposium Series, 173–85. Washington, DC : American Chemical Society, 2005. http://dx.doi.org/10.1021/bk-2005-0894.ch012.

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van der Veer, Grishja, Saskia M. van Ruth et Jos A. Hageman. « An integral approach to validation of analytical fingerprinting methods in combination with chemometric modelling for food quality assurance ». Dans Mathematical and Statistical Methods in Food Science and Technology, 449–70. Chichester, UK : John Wiley & Sons, Ltd, 2013. http://dx.doi.org/10.1002/9781118434635.ch23.

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Actes de conférences sur le sujet "Chemometric approaches"

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Meade, A. D., C. Clarke, F. Bonnier, K. Poon, A. Garcia, P. Knief, K. Ostrowska et al. « Functional and pathological analysis of biological systems using vibrational spectroscopy with chemometric and heuristic approaches ». Dans 2009 First Workshop on Hyperspectral Image and Signal Processing : Evolution in Remote Sensing (WHISPERS). IEEE, 2009. http://dx.doi.org/10.1109/whispers.2009.5288989.

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Tzimas, P. S., E. A. Petrakis, A. Papadimitriou, S. Beteinakis, M. Halabalaki et A. L. Skaltsounis. « Analytical and chemometric approaches for quality characterization of Cannabis sativa L. with focus on cannabinoids ». Dans GA – 69th Annual Meeting 2021, Virtual conference. Georg Thieme Verlag, 2021. http://dx.doi.org/10.1055/s-0041-1736858.

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Marchesi, C., M. Rani, S. Federici, M. Lancini et L. E. Depero. « COMPARATIVE STUDY OF CHEMOMETRIC APPROACHES AND MACHINE LEARNING FOR MINIATURIZED NEAR-INFRARED (MICRONIR) SPECTROSCOPY IN PLASTICWASTE SORTING ». Dans Joint IMEKO TC11 and TC24 Hybrid Conference. Budapest : IMEKO, 2023. http://dx.doi.org/10.21014/tc24-2022.01.

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Roy, Kunal, et Kazi Hossain. « Chemometric modeling of toxicity of contaminants of emerging concern to Dugesia japonica and its interspecies correlation with daphnia and fish : QSTR and i-QSTTR approaches ». Dans MOL2NET 2018, International Conference on Multidisciplinary Sciences, 4th edition. Basel, Switzerland : MDPI, 2018. http://dx.doi.org/10.3390/mol2net-04-05266.

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Sikka, Raghav, Maths Halstensen et Joachim Lundberg. « Spray drop size characterization in an external-mixing bluff-body atomizer based on acoustics and Multivariate Analysis ». Dans 63rd International Conference of Scandinavian Simulation Society, SIMS 2022, Trondheim, Norway, September 20-21, 2022. Linköping University Electronic Press, 2022. http://dx.doi.org/10.3384/ecp192027.

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Air-assist atomizers have been widely used in various applications such as the aerospace industry, internal combustion engines, molten metal, food processing, etc. The mean drop size for these atomizers was obtained through the Shadowgraph imaging technique. This study aims to assess the feasibility of the acoustic chemometrics approach for classifying the atomizer types and predicting the mean drop size, such as Sauter mean diameter (SMD), for a two-phase spray atomizer employed. The droplet size measurements were carried out at three radial locations and one axial location for various air and liquid (water) flow rates. The acoustic signals were recorded through two different sensors: accelerometers and microphones. The main objective of this work is to implement prediction models for the mean drop sizes (SMD) measured at various locations. The model prediction is based on the dimensionless number B, whose unique values correspond to different two-phase flow working conditions. This analysis will further cater to the question that whether the acoustics chemometrics approach, including Principal Component Analysis (PCA) and Partial Least Squares Regression (PLS-R), is suitable for extracting valuable information such as predicting mean drop size (SMD) in two-phase flows through recorded acoustic signals.
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Togkalidou, T., M. Fujiwara, S. Patel et R. D. Braatz. « A robust chemometrics approach to inferential estimation of supersaturation ». Dans Proceedings of 2000 American Control Conference (ACC 2000). IEEE, 2000. http://dx.doi.org/10.1109/acc.2000.879498.

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Sikorska, Celina. « Efficient Chemometric Approach Supporting the Design of Fullerene Derivatives for Solar Cells ». Dans The 3rd World Congress on Recent Advances in Nanotechnology. Avestia Publishing, 2018. http://dx.doi.org/10.11159/icnnfc18.146.

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Roy, Kunal, Pathan Mohsin Khan et Bakhtiyor Rasulev. « Chemometric modeling of refractive index of polymers using 2D descriptors : A QSPR approach ». Dans MOL2NET 2018, International Conference on Multidisciplinary Sciences, 4th edition. Basel, Switzerland : MDPI, 2018. http://dx.doi.org/10.3390/mol2net-04-05267.

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Paulus, C., S. Bonnet, L. Gerfault, E. Mery, G. Strubel, F. Ricoul et P. Grangeat. « Chromatographic alignment combined with chemometrics profile reconstruction approaches applied to LC-MS data ». Dans 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2007. http://dx.doi.org/10.1109/iembs.2007.4353711.

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Silva, Maria Fátima das Graças Fernandes. « Essential oil variation of twenty two genotypes ofCitrusin Brazil — chemometric approach and repellency againstDiaphorina citriKuwayama ». Dans 2016 International Congress of Entomology. Entomological Society of America, 2016. http://dx.doi.org/10.1603/ice.2016.110998.

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Rapports d'organisations sur le sujet "Chemometric approaches"

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Ivanova, Miroslava, Lilko Dospatliev et Penko Papazov. Application of ICP-OES Method of Determination of K, P, Mg, Na and Ca in Nine Wild Edible Mushrooms with a Chemometric Approach. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, février 2019. http://dx.doi.org/10.7546/crabs.2019.02.06.

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