Inbunden, Engelska, 2016
Statistical Analysis of Proteomics, Metabolomics, and Lipidomics Data Using Mass Spectrometry
Av Susmita Datta, Bart J. A. Mertens
Del i serien Frontiers in Probability and the Statistical Sciences
1835 kr
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Beskrivning
Produktinformation
- Utgivningsdatum: 2016-12-22
- Mått: 155 x 235 x 22 mm
- Vikt: 614 g
- Format: Inbunden
- Språk: Engelska
- Serie: Frontiers in Probability and the Statistical Sciences
- Antal sidor: 295
- Upplaga: 16001
- Förlag: Springer International Publishing AG
- ISBN: 9783319458076
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Mer om författaren
Susmita Datta received her PhD in statistics from the University of Georgia. She is a tenured professor in the Department of Biostatistics at the University of Florida. Before joining the University of Florida she was a professor in the Department of Bioinformatics and Biostatistics and a distinguished university scholar at the University of Louisville. She is a Fellow of the American Association for the Advancement of Science (AAAS), American Statistical Association (ASA), and an elected member of the International Statistical Institute (ISI). Her research interests include bioinformatics, genomics, proteomics, clustering and classification techniques, infectious disease modeling, statistical issues in population biology, systems biology, survival analysis, and multi state models. She is past president of the Caucus for Women in Statistics, and she actively supports research and education for women in STEM fields.Bart Mertens received his PhD in statistical sciences from University College London, Department of Statistical Sciences, on statistical analysis methods for spectrometry data. He is currently Associate Professor at the Department of Medical Statistics and Bioinformatics of the Leiden University Medical Centre, where he has been working in both research and consulting for statistical analysis methodology with mass spectrometry proteomic data for more than 10 years.
Recensioner i media
“This book provides a comprehensive overview on statistical analyses of mass spectrometric data. The book aggregates cutting-edge methods developed by established researchers and offers readers opportunities of utilizing mass spectrometry to advance biomedical studies. Statisticians, computer scientists, computational biologists, analytical chemists, and data scientists can benefit from reading this book.” (Hsun-Hsien Chang, Computing Reviews, January, 17 , 2018)
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