Scope

The Chemometrics specialty section of Frontiers in Analytical Science is devoted to publishing high quality theoretical, methodological and applied research across the field of chemometrics, with the possibility of also introducing newly developed software toolboxes. Chemometrics is the discipline involved with extracting information from chemical data through mathematical and statistical tools and, as such, it can be thought of as a chemical information science. Its development has been triggered by the parallel evolution of chemical instrumentation and increased availability of computing tools, and its inherent multidisciplinary nature has made so that its domain of application has extended, with years, to fields like system biology and/or the omic sciences in general, cultural heritage, food science or process analytical technology, just to cite a few.

This Chemometrics section welcomes the submission of impactful research on all fundamental (theoretical and methodological), applied and implementation/software aspects of chemometrics, with particular focus on its role within analytical sciences. In this respect, it is worth highlighting how, differently from other ambits of data mining, domain knowledge plays a key role in chemometrics, together with other fundamental aspects such as a solid experimental design and a proper validation. In particular, the section welcomes the submission of new and original research describing:

·       Applications of chemometrics to solve relevant problems in chemistry and related disciplines (e.g., environmental analysis, metabolomics/proteomics, process control and monitoring, cultural heritage, food science, forensic science, pharmaceutical analysis, process analytical technology)

·       Development of novel mathematical and statistical tools for the analysis of chemical data (in such cases, together with the possibility of benchmarking on simulated examples, the application to real data sets is encouraged).

·       New software toolboxes (preferentially available on freely accessible repositories or websites).

In all these contexts, the range of possible topics includes, but is not limited to:

·       Design of experiments and models for the analysis of designed data

·       Statistical theory of sampling

·       Data Pre-processing

·       Pattern recognition

·       Calibration

·       Multi-set, multi-block and/or multi-way data analysis

·       Multi-spectral and hyper-spectral image analysis

·       Non-linear modeling

·       Nature-inspired modeling (e.g., genetic algorithms, swarm intelligence or artificial neural networks

·       Mixture analysis

·       Model inversion

·       Validation

All contributions must represent an advancement with respect to the state of the art and demonstrate to have a clear and sound research background and justification. Reviews on hot topic are also encouraged and should cover the latest advances and most critical issues in chemometrics. 

Research Topics will enrich this specialty section with comprehensive overviews on specific fields of interest both from a methodological and an application standpoint.

Submission

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