TY  - BOOK
AU  - Emmert-Streib,Frank
AU  - Dehmer,Matthias
TI  - Statistical diagnostics for cancer: analyzing high-dimensional data 
T2  - Quantitative and network biology
SN  - 9783527665471
AV  - RC270 .S73 2013eb
U1  - 616.99/4075 23
PY  - 2013///]
CY  - Weinheim, Germany
PB  - Wiley-Blackwell
KW  - Cancer
KW  - Diagnosis
KW  - Neoplasms
KW  - genetics
KW  - Statistics as Topic
KW  - methods
KW  - fast
KW  - Electronic books
KW  - local
N1  - Edition statement from running title area; Includes bibliographical references and index; Part one: General overview. Control of type I error rates for oncology biomarker discovery with high-throughput platforms -- Overview of public cancer databases, resources, and visualization tools -- Part two: Bayesian methods. Discovery of expression signatures in chronic myeloid leukemia by Bayesian model averaging -- Bayesian ranking and selection methods in microarray studies -- Multiclass classification via Bayesian variable selection with gene expression data -- Semisupervised methods for analyzing high-dimensional genomic data -- Part three: Network-based approaches -- Colorectal cancer and its molecular subsystems: construction, interpretation, and validation -- Network medicine: disease genes in molecular networks -- Inference of gene regulatory networks in breast and ovarian cancer by integrating different genomic data -- Network-module-based approaches in cancer data analysis -- Discriminant and network analysis to study origin of cancer -- Intervention and control of gene regulatory networks: theoretical framework and application to human melanoma gene regulation -- Part four: Phenotype influence of DNA copy number aberrations. Identification of recurrent DNA copy number aberrations in tumors -- The cancer cell, its entropy, and high-dimensional molecular data; ls
N2  - This title discusses different methods for statistically analyzing and validating data created with high-throughput methods. It focuses on systems approaches, meaning that no single gene or protein forms the basis of the analysis but rather a more or less complex biological network
UR  - http://dx.doi.org/10.1002/9783527665471
ER  -