Bioinformatics Methods : From Omics to Next Generation Sequencing

Shili Lin

ISBN 10: 1498765157 / ISBN 13: 9781498765152

Edité par Chapman And Hall/CRC, 2022

A propos de cet article

nach der Bestellung gedruckt Neuware - Printed after ordering - The past three decades have witnessed an explosion of what is now referred to as high-dimensional `omics' data. This book describes the statistical methods and analytic frameworks that are best equipped to interpret these complex data and how they apply to health-related research.

N° de réf. du vendeur 9781498765152

Détails bibliographiques

• Titre: Bioinformatics Methods : From Omics to Next Generation Sequencing
• Éditeur: Chapman And Hall/CRC
• Date de parution: 2022
• Langue: anglais
• ISBN à 10 chiffres: 1498765157
• ISBN à 13 chiffres: 9781498765152
• Reliure: Buch
• État de l'article: Neu

A propos de ce titre

Synopsis

The past three decades have witnessed an explosion of what is now referred to as high-dimensional `omics' data. This book describes the statistical methods and analytic frameworks that are best equipped to interpret these complex data and how they apply to health-related research.

À propos de l?auteur

Shili Lin, PhD is a Professor in the Department of Statistics and a faculty member in the Translational Data Analytics Institute at the Ohio State University. Her research interests are in statistical methodologies for high-dimensional and big data, with a focus on their applications in biomedical research, statistical genetics and genomics, and integration of multiple omics data.

Denise Scholtens, PhD is Professor and Chief of the Division of Biostatistics in the Department of Preventive Medicine at Northwestern University Feinberg School of Medicine. She is interested in the design and conduct of large-scale multi-center prospective health research studies, and in the integration of high-dimensional omics data analyses into these settings.

Sujay Datta, PhD is an Associate Professor and the Graduate Program Coordinator in the Department of Statistics at the University of Akron. His research interests include statistical analyses of high-dimensional and high-throughput data, graphical and network-based models, statistical models and methods for cancer data, as well as sequential/multistage sampling designs.