Statistical Methods at the Forefront of Biomedical Advances

ISBN-13: 9783031327285 / Angielski / Twarda / 2023

Opis

This book presents novel statistics methods and reproducible software that helps to solve challenging problems in biomedicine. Specifically, it consists of a collection of 11 chapters contributed by some of the leading experts in the mathematical and statistical field which address new challenges in very disparate biomedical areas, such as genomics, cancer, circadian biology, microbiome, mental disorders, and more. The mathematical rigor is written in a user-friendly way to serve a general biomedical audience ranging from trainees or students to doctors, as well as scientific researchers, university departments, and PhD students.

Spis treści

1. “Forecasting of SARS-COV-2 dynamic: beyond the classical SIR model”.         

Javier Álvarez-Liébana, Universidad Complutense de Madrid, Spain javalv09@ucm.es

 2. “Derivation of OED methods for applications in cytogenetic biodosimetry”.

Manuel Higueras, Universidad de la Rioja, Spain manuel.higueras@unirioja.es

Jesús López-Fidalgo, Universidad de Navarra, Spain

3. “Minimum Phi-divergence tests for ophthalmological data grouped in clusters”.

Juana M. Alonso-Revenga, Universidad Complutense de Madrid, Spain

Aida Calvino, Universidad Complutense de Madrid, Spain aida.calvino@ucm.es

Leandro Pardo, Universidad Complutense de Madrid, Spain

4. “Multimodality test for determining which genes distinguish oncological patients”.

Jose Ameijeiras-Alonso, Universidad de Santiago de Compostela, Spain jose.ameijeiras@usc.es

Rosa M. Crujeiras, Universidad de Santiago de Compostela, Spain

 5. “Exploring the relationship between different cancer sites using disease mapping models”

Aritz Adin, Universidad Pública de Navarra, Spain aritz.adin@unavarra.es

Tomás Goicoa, Universidad Pública de Navarra, Spain

Gonzalo Vicente, Universidad Pública de Navarra, Spain

Ugarte, M.D., Universidad Pública de Navarra, Spain

 6. “Advances in flow cytometry gating based on distances and divergences in probability spaces”.

Hristo Inouzhe, Basque Center for Applied Mathematics, Spain hinouzhe@bcamath.org

Eustasio del Barrio, Universidad de Valladolid, Spain

Carlos Matrán, Universidad de Valladolid, Spain

 7. “Application of quantile regression models for biomedical data”.

Mercedes Conde-Amboage, Universidad de Santiago de Compostela, Spain mercedes.amboage@usc.es

Ingrid Van Keilegom, Katholieke Universiteit te Leuven, KU Leuven

Wenceslao González Manteiga, Universidad de Santiago de Compostela, Spain

 8. “Hippocampus shape analysis via skeletal models and kernel smoothing”.

Eduardo García-Portugués, Carlos III University of Madrid, Spain

edgarcia@est-econ.uc3m.es

Andrea Meilán Vila, Carlos III University of Madrid, Spain

 9. ”Methods for analysis of microbiome count data with applications”

Shyamal D. Peddada, Biostatistics and Bioinformatics Branch, NICHD, NIH, Bethesda, MD, USA shyamal.peddada@nih.gov

Huang Lin, Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA.

Jamie Morton, Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, USA

 10. “The FMM model as a classifier of cardiovascular pathologies”.

Alejandro Rodríguez-Collado, University of Valladolid, Spain alejandro.rodriguez.collado@uva.es

Christian Canedo, University of Valladolid, Spain

Itziar Fernández, University of Valladolid, Spain

Cristina Rueda, University of Valladolid, Spain

 11. “A novel statistical insight of the circadian markers that govern cardiac rhythms”.

Yolanda Larriba, University of Valladolid, Spain yolanda.larriba@uva.es

Cristina Rueda, University of Valladolid , Spain

 12. “Sleep and circadian synchronization assessment from multivariate recordings”:

M. Ángeles Bonmatí, Universidad de Murcia, Spain

mabonmati@um.es

O autorze

Yolanda Larriba is an Assistant Professor at the Department of Statistics and Operations Research of the University of Valladolid (Spain). Her research mainly concerns the development of statistical methodologies in the field of order restricted inference with applications to medical science.