000			03404cam a2200337 a 4500
008			100313s2010 maua b 001 0 eng
010			_a 2009009810
020			_a 9780763758080 (pbk. : alk. paper)
020			_a 0763758086 (pbk. : alk. paper)
035			_a(Sirsi) u4794
040			_aEG-CaNU _cEG-CaNU _dEG-CaNU
042			_ancode
082	0	0	_a 610.285 _2 22
100	1		_a Lewis, Paul D., _d 1969- _99537
245	1	0	_a R for medicine and biology / _c Paul D. Lewis.
260			_aSudbury, Mass. : _b Jones and Bartlett Publishers, _c c2010.
300			_axix, 399 p. : _b ill. ; _c 26 cm.
490			_aJones and Bartlett series in biomedical informatics
504			_aIncludes bibliographical references (p. 363-366) and index.
505	0		_aChapter 1. R Installation and Getting Help -- Chapter 2. The R Environment and Packages -- Chapter 3. Basic Fundamentals of R -- Chapter 4. Plotting Data -- Chapter 5. Example Datasets -- Chapter 6. Importing and Exporting Data in R -- Chapter 7. R, SQL, and Database Connectivity -- Chapter 8. Using R to Build a Biomedical Database in MySQL -- Chapter 9. Creating Heterogeneous Datasets for Analysis in R -- Chapter 10. Descriptive Statistics in R -- Chapter 11. R and Basic Inferential Statistical Analysis -- Chapter 12. Writing Functions in R -- Chapter 13. Multivariate Analysis in R -- Chapter 14. Survival Analysis -- Chapter 15. Data Mining and Predictive Modeling with R and Weka -- Chapter 16. Surveillance of Infectious Disease -- Chapter 17. Medical Imaging and R -- ter 18. Retrieving Public Microarray Datasets -- Chapter 19. Working with Microarray Data -- Chapter 20. Annotating Microarray Gene Lists -- Chapter 21. Array CGH Analysis -- Chapter 22. XML for Storing and Sharing Data.
520			_aR is quickly becoming the number one choice for users in the fields of biology, medicine, and bioinformatics as their main means of storing, processing, sharing, and analyzing biomedical data. R for Medicine and Biology is a step-by-step guide through the use of the statistical environment R, as used in a biomedical domain. Ideal for healthcare professionals, scientists, informaticists, and statistical experts, this resource will provide even the novice programmer with the tools necessary to process and analyze their data using the R environment.
520			_aIntroductory chapters guide readers in how to obtain, install, and become familiar with R and provide a clear introduction to the programming language using numerous worked examples. Later chapters outline how R can be used, not just for biomedical data analysis, but also as an environment for the processing, storing, reporting, and sharing of data and results. The remainder of the book explores areas of R application to common domains of biomedical informatics, including imaging, statistical analysis, data mining/modeling, pathology informatics, epidemiology, clinical trials, and metadata usage. R for Medicine and Biology will provide you with a single desk reference for the R environment and its many capabilities.
650		0	_aMedical informatics. _9431
650		0	_aR (Computer program language) _92301
650		0	_aBioinformatics. _99538
650		0	_aMedical statistics _v Software. _9431
650	1	2	_aMedical Informatics Applications. _9431
650	1	2	_aSoftware. _99539
650	2	2	_aProgramming Languages. _99540
596			_a1
999			_c3793 _d3793