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pro vyhledávání: '"ARMSTRONG, MICHAEL"'
Autor:
Camacho, José, Armstrong, Michael Sorochan, García-Martínez, Luz, Díaz, Caridad, Gómez-Llorente, Carolina
Over the past few years, technological advances have allowed for measurement of omics data at the cell level, creating a new type of data generally referred to as single-cell (sc) omics. On the other hand, the so-called spatial omics are a family of
Externí odkaz:
http://arxiv.org/abs/2412.13591
This paper introduces a novel deconvolution algorithm, shift-invariant multi-linearity (SIML), which significantly enhances the analysis of data from a comprehensive two-dimensional gas chromatograph coupled to a mass spectrometric detector (GC$\time
Externí odkaz:
http://arxiv.org/abs/2412.12114
Chemical separations data are typically analysed in the time domain using methods that integrate the discrete elution bands. Integrating the same chemical components across several samples must account for retention time drift over the course of an e
Externí odkaz:
http://arxiv.org/abs/2410.08733
Autor:
Merchanskaya, Oliver Polushkina, Armstrong, Michael D. Sorochan, Llorente, Carolina Gómez, Ferrer, Patricia, Fernandez-Gonzalez, Sergi, Perez-Cruz, Miriam, Gómez-Roig, María Dolores, Camacho, José
Multifactorial experimental designs allow us to assess the contribution of several factors, and potentially their interactions, to one or several responses of interests. Following the principles of the partition of the variance advocated by Sir R.A.
Externí odkaz:
http://arxiv.org/abs/2408.06739
Publikováno v:
Journal of Chemometrics, 2024
In this paper, we revisit the Power Curves in ANOVA Simultaneous Component Analysis (ASCA) based on permutation testing, and introduce the Population Curves derived from population parameters describing the relative effect among factors and interacti
Externí odkaz:
http://arxiv.org/abs/2403.00429