Statistical diagnostics for cancer : analyzing high-dimensional data /

• Άλλοι συγγραφείς: Emmert-Streib, Frank (Επιμελητής έκδοσης), Dehmer, Matthias, 1968- (Επιμελητής έκδοσης)
• Μορφή: Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Weinheim, Germany : Wiley-Blackwell, [2013]
• Έκδοση: First edition.
• Σειρά: Quantitative and network biology ; v. 3.
• Θέματα: Cancer > Diagnosis.; Neoplasms > genetics.; Statistics as Topic > methods.; Electronic books.

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.

Πίνακας περιεχομένων:

• 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.