George Tseng, Debashis Ghosh, Xianghong Jasmine Zhou

Integrating Omics Data

• Gebundenes Buch

Produktbeschreibung

Tutorial chapters by leaders in the field introduce state-of-the-art methods to handle information integration problems of omics data.

Produktdetails

• Verlag: Cambridge University Press
• Seitenzahl: 476
• Erscheinungstermin: 23. September 2015
• Englisch
• Abmessung: 233mm x 154mm x 32mm
• Gewicht: 804g
• ISBN-13: 9781107069114
• ISBN-10: 1107069114
• Artikelnr.: 42091495

Autorenporträt

George Tseng completed his Sc.D. in biostatistics with a concentration in genomics from the Harvard School of Public Health. He is currently a Professor of Biostatistics, Human Genetics, and Computational and Systems Biology at the University of Pittsburgh. His research interests focus on statistical and computational method development for analyzing high-throughput omics data.

Inhaltsangabe

1. Meta-analysis of genome-wide association studies: a practical guide Wei
Chen, Dajiang Liu and Lars Fritsche; 2. Integrating omics data: statistical
and computational methods Sunghwan Kim, Zhiguang Huo, Yongseok Park and
George C. Tseng; 3. Integrative analysis of many biological networks to
study gene regulation Wenyuan Li, Chao Dai and Xianghong Jasmine Zhou; 4.
Network integration of genetically regulated gene expression to study
complex diseases Zhidong Tu, Bin Zhang and Jun Zhu; 5. Integrative analysis
of multiple ChIP-X data sets using correlation motifs Hongkai Ji and
Yingying Wei; 6. Identify multi-dimensional modules from diverse cancer
genomics data Shihua Zhang, Wenyuan Li and Xianghong Jasmine Zhou; 7. A
latent variable approach for integrative clustering of multiple genomic
data types Ronglai Shen; 8. Penalized integrative analysis of
high-dimensional omics data Jin Liu, Xingjie Shi, Jian Huang and Shuangge
Ma; 9. A Bayesian graphical model for integrative analysis of TCGA data:
BayesGraph for TCGA integration Yanxun Xu, Yitan Zhu and Yuan Ji; 10.
Bayesian models for integrative analysis of multi-platform genomics data
Veera Baladandayuthapani; 11. Exploratory methods to integrate multi-source
data Eric F. Lock and Andrew B. Nobel; 12. eQTL and Directed Graphical
Model Wei Sun and Min Jin Ha; 13. microRNAs: target prediction and
involvement in gene regulatory networks Panayiotis V. Benos; 14.
Integration of cancer omics data on a whole-cell pathway model for
patient-specific interpretation Charles Vaske, Sam Ng, Evan Paull and
Joshua Stuart; 15. Analyzing combinations of somatic mutations in cancer
genomes Mark D. M. Leiserson and Benjamin J. Raphael; 16. A mass
action-based model for gene expression regulation in dynamic systems
Guoshou Teo, Christine Vogel, Debashis Ghosh, Sinae Kim and Hyungwon Choi;
17. From transcription factor binding and histone modification to gene
expression: integrative quantitative models Chao Cheng; 18. Data
integration on non-coding RNA studies Zhou Du, Teng Fei, Myles Brown, X.
Shirley Liu and Yiwen Chen; 19. Drug-pathway association analysis:
integration of high-dimensional transcriptional and drug sensitivity
profile Cong Li, Can Yang, Greg Hather, Ray Liu and Hongyu Zhao.