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Survival Analysis: A Self-Learning Text David G. Kleinbaum, Mitchel Klein
Publisher: Springer

Our method for discovering prognostic signatures builds on top of a human protein functional interaction (FI) network constructed by combining curated and uncurated data sources using a machine learning technique [24]. New material has been added to the second edition and. Kleinbaum DG, Klein M (2005) Survival Analysis, a Self-Learning Text, 2nd edition. This FI network covers roughly each tissue in the series. He has also taught over 150 short courses over the past 30 years throughout the world. This study addressed this issue by using daily surveys of road-killed vertebrates and survival analysis to describe carcass persistence along four sections of roads with different characteristics. Survival analysis: a self-learning text By David G. Kleinbaum DG, Klein M: Survival analysis: a self-learning text. There are also some reported cases of carcass removal by regular persons or road crews, although in our study it is incidental and directed to certain species (see text above). We then apply this expression matrix for the superpc analysis [23] to search for linear combinations of network modules that are significantly correlated with patient survival or other clinically relevant criteria. Cancer: Survival Analysis: A Self-Learning Text (Statistics for Biology and Health). His popular text "Survival Analysis - A Self Learning Text" is the text for this course. Product DescriptionAn excellent introduction for all those coming to the subject for the first time. Loading Saturday, May 21, 2011. Aly C: Filtration rates of mosquito larvae in suspensions of latex microspheres and yeast cells.