Mastering Scientific Computing with R

Paul Gerrard · Radia M. Johnson

იან. 2015 · Packt Publishing Ltd

ამ ელწიგნის შესახებ

If you want to learn how to quantitatively answer scientific questions for practical purposes using the powerful R language and the open source R tool ecosystem, this book is ideal for you. It is ideally suited for scientists who understand scientific concepts, know a little R, and want to be able to start applying R to be able to answer empirical scientific questions. Some R exposure is helpful, but not compulsory.

ავტორის შესახებ

Paul Gerrard is a physician and healthcare researcher who is based out of Portland, Maine, where he currently serves as the medical director of the cardiopulmonary rehabilitation program at New England Rehabilitation Hospital of Portland. He studied business economics in college. After completing medical school, he did a residency in physical medicine and rehabilitation at Harvard Medical School and Spaulding Rehabilitation Hospital, where he served as chief resident and stayed on as faculty at Harvard before moving to Portland. He continues to collaborate on research projects with researchers at other academic institutions within the Boston area and around the country. He has published and presented research on a range of topics, including traumatic brain injury, burn rehabilitation, health outcomes, and the epidemiology of disabling medical conditions.; Radia M. Johnson has a doctorate degree in immunology and currently works as a research scientist at the Institute for Research in Immunology and Cancer at the Université de Montréal, where she uses genomics and bioinformatics to identify and characterize the molecular changes that contribute to cancer development. She routinely uses R and other computer programming languages to analyze large data sets from ongoing collaborative projects. Since obtaining her PhD at the University of Toronto, she has also worked as a research associate at the University of Cambridge in Hematology, where she gained experience using system biology to study blood cancer.