Comprehensive Chemometrics: Chemical and Biochemical Data Analysis. Questo articolo non è disponibile.Comprehensive Chemometrics: Chemical and Biochemical Data Analysis

Comprehensive Chemometrics, Second Edition features expanded and updated coverage, along with new content that covers advances in the field since the previous edition published in 2009. Subject of note include updates in the fields of multidimensional and megavariate data analysis, omics data analysis, big chemical and biochemical data analysis, data fusion and sparse methods. The book follows a similar structure to the previous edition, using the same section titles to frame articles. Many chapters from the previous edition are updated, but there are also many new chapters on the latest developments.

• Presents integrated reviews of each chemical and biological method, examining their merits and limitations through practical examples and extensive visuals
• Bridges a gap in knowledge, covering developments in the field since the first edition published in 2009
• Meticulously organized, with articles split into 4 sections and 12 sub-sections on key topics to allow students, researchers and professionals to find relevant information quickly and easily
• Written by academics and practitioners from various fields and regions to ensure that the knowledge within is easily understood and applicable to a large audience
• Presents integrated reviews of each chemical and biological method, examining their merits and limitations through practical examples and extensive visuals
• Bridges a gap in knowledge, covering developments in the field since the first edition published in 2009
• Meticulously organized, with articles split into 4 sections and 12 sub-sections on key topics to allow students, researchers and professionals to find relevant information quickly and easily
• Written by academics and practitioners from various fields and regions to ensure that the knowledge within is easily understood and applicable to a large audience

Expertise in chemical data analysis, including signal processing and detection, background removal, and transfer of multivariate calibrations. Data mining and knowledge discovery of chemical relationships involving multivariate data, including development of novel classifiers and hierarchical classification methods. Fusion of chemical sensor data for classification and calibration. Former EIC of Editor-in-Chief, Journal of Chemometrics (1994-2007), Editorial Board Member of Nature Scientific Reports and Journal of Chemometrics, Winner of Best Applied Chemometrics Paper 2015 (Wiley, Kowalski Award).

Romà Tauler graduated in Chemistry from the University of Barcelona (1977) and in 1984 obtained his Ph.D. degree in Analytical Chemistry at the University of Barcelona. He was Associate Professor at the University of Barcelona (Analytical Chemistry Dept) from 1987 to 2003. Since July 2003, he is Research Professor at the Institute of Environmental Assessment and Water Research (IDÆA) of the Spanish National Research Council (CSIC). During these years, he carried out postdoc stays at Institut für Anorg. u. Anal. Chemie - Univ. of Innsbruck (Innsbruck, Austria, 1985 and 1989) and a sabbatical leave as a research scientist at the Center for Process Analytical Chemistry (CPAC) - University of Washington (Seattle, US, 1992). Until now, he has published more than 360 papers in ISI journals (WoS gives 11.656 citations and h-index 51 at Sept 7th, 2017). Nowadays, he is the Chief Editor of the Chemometrics and Intelligent Laboratory Systems (Elsevier) journal and Chief Editor of the Major Reference Work: Comprehensive Chemometrics, Chemical and Biochemical Data Analysis (Elsevier). He has been awarded an ERC Advanced Grant (2012) for the project “CHEMometric and High-Throughput Omics Analytical Methods for Assessment of Global Change Effects on Environmental and Biological Systems”. Other academic awards are the Award for Achievements in Chemometrics (Eastern Analytical Symposium, 2009) and the Kowalski Prize (Journal of Chemometrics, 2009).
Main research interests are in Chemometrics, especially in the development of multivariate curve resolution methods for the analysis of multiway and multiset data, and for their applications to Omics Sciences, Environmental Chemistry, Analytical and Bioanalytical Chemistry (hyphenated chromatography, spectroscopy, imaging, mass spectrometry, sensor development), and Solution Chemistry (Equilibria and Kinetics).

Main research interests in Chemometrics, especially in the development of multivariate curve resolution methods for the analysis of multiway and muliset data, and for their applications to Omic Sciences, Environmental Chemistry, Analytical and Bioanalytical Chemistry (hyphenated chromatography, spectroscopy, imaging, mass spectrometry, sensor development), and Solution Chemistry (Equilibria and Kinetics). Winner of 2009 Award for Achievements in Chemometrics (Eastern Analytical Symposium) and 2009 Kowalski Prize from the Journal of Chemometrics. Former president of the Catalan Chemistry Society (2008-2013). He has published 354 papers in ISI journals and has an h-index of 53.

Professor Walczak has been working in the Institute of Chemistry, University of Silesia since 1979, where now she is the head of the Department of Analytical Chemistry. She has authored and co-authored around 165 scientific papers, 400 conference papers, and delivered many invited lectures at international chemistry meetings. Currently she acts as Editor of the journal Chemometrics and Intelligent Laboratory Systems and of ‘Data Handling in Chemistry and Technology’ (the Elsevier book series), and as a member of the editorial boards of Talanta, Analytical Letters, J. Chemometrics, and Acta Chromatographica. She has been involved in chemometrics since the early 1990s and her main scientific interests are in all aspects of data exploration and modelling (dealing with missing and censored data, dealing with outliers, data representatively, enhancement of instrumental signals, signal warping, data compression, linear and non-linear projections, development of modeling approaches, feature selection techniques etc.). She has an h-index of 40.