Phenotype prediction by integrative network analysis of SNP and gene expression microarrays

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

Volumn , Issue , 2011, Pages 6849-6852

  Chang, Hsun Hsien ^a   McGeachie, Michael ^b  

^a HARVARD MIT DIVISION OF HEALTH SCIENCES AND TECHNOLOGY   (United States)

^b BRIGHAM AND WOMEN S HOSPITAL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACUTE LYMPHOBLASTIC LEUKEMIA; BIOMEDICAL RESEARCH; CLINICAL PRACTICES; DATA SETS; DISEASE ETIOLOGY; EXPRESSION MICROARRAY; GENE EXPRESSION MICROARRAY; GENE TRANSCRIPTS; GENETIC PROCESS; LONG-TERM GOALS; MICROARRAY TECHNOLOGIES; NETWORK LEARNING; NETWORK MODELS; NETWORK-BASED APPROACH; SINGLE NUCLEOTIDE POLYMORPHISMS; VARIABLE SELECTION;

BAYESIAN NETWORKS; MICROARRAYS; RNA;

GENE EXPRESSION;

ACUTE LYMPHOBLASTIC LEUKEMIA; ALGORITHM; ARTICLE; BAYES THEOREM; BIOLOGICAL MODEL; BIOLOGY; DNA MICROARRAY; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENETICS; GENOTYPE; HUMAN; METHODOLOGY; PHENOTYPE; QUANTITATIVE TRAIT LOCUS; REPRODUCIBILITY; SINGLE NUCLEOTIDE POLYMORPHISM; STATISTICAL MODEL;

ALGORITHMS; BAYES THEOREM; COMPUTATIONAL BIOLOGY; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION, LEUKEMIC; GENOTYPE; HUMANS; MODELS, GENETIC; MODELS, STATISTICAL; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PHENOTYPE; POLYMORPHISM, SINGLE NUCLEOTIDE; PRECURSOR CELL LYMPHOBLASTIC LEUKEMIA-LYMPHOMA; QUANTITATIVE TRAIT LOCI; REPRODUCIBILITY OF RESULTS;

EID: 84864615989     PISSN: 1557170X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IEMBS.2011.6091689     Document Type: Conference Paper

References (14)

1. T. A. Manolio, "Genomewide association studies and assessment of the risk of disease," N Engl J Med, vol. 363, no. 2, pp. 166-76, Jul 8, 2010.
2. H. H. Chang, J. M. Dreyfuss, and M. F. Ramoni, "A transcriptional network signature characterizes lung cancer subtypes," Cancer, vol. 117, no. 2, pp. 353-60, Jan 15, 2011.
3. H. H. Chang, and M. F. Ramoni, "Transcriptional network classifiers," BMC Bioinformatics, vol. 10 Suppl 9, pp. S1, 2009.
4. A. C. Nica, and E. T. Dermitzakis, "Using gene expression to investigate the genetic basis of complex disorders," Hum Mol Genet, vol. 17, no. R2, pp. R129-R134, Oct, 2008.
5. T. F. C. Mackay, E. A. Stone, and J. F. Ayroles, "The genetics of quantitative traits: challenges and prospects," Nat Rev Genet, vol. 10, no. 8, pp. 565-577, Aug, 2009.
6. H. H. Chang, M. McGeachie, G. Alterovitz et al., "Mapping transcription mechanisms from multimodal genomic data," BMC Bioinformatics, vol. 11 Suppl 9, pp. S2, 2010.
7. B. H. Junker, and F. Schreiber, Analysis of biological networks, Hoboken, N.J.: Wiley-Interscience, 2008.
8. S. Kim, J. Kim, and K. H. Cho, "Inferring gene regulatory networks from temporal expression profiles under time-delay and noise," Comput Biol Chem, vol. 31, no. 4, pp. 239-45, Aug, 2007.
9. M. Zou, and S. D. Conzen, "A new dynamic Bayesian network (DBN) approach for identifying gene regulatory networks from time course microarray data," Bioinformatics, vol. 21, no. 1, pp. 71-9, Jan 1, 2005.
10. F. Ferrazzi, P. Sebastiani, M. F. Ramoni et al., "Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks," BMC Bioinformatics, vol. 8 Suppl 5, pp. S2, 2007.
11. R. G. Cowell, "Local propagation in conditional Gaussian Bayesian networks," Journal of Machine Learning Research, vol. 6, pp. 1517-1550, 2005.
12. S. Bungaro, M. C. Dell'Orto, A. Zangrando et al., "Integration of genomic and gene expression data of childhood ALL without known aberrations identifies subgroups with specific genetic hallmarks," Genes Chromosomes Cancer, vol. 48, no. 1, pp. 22-38, Jan, 2009.
13. L. J. Russell, T. Akasaka, A. Majid et al., "t(6;14)(p22;q32): a new recurrent IGH@ translocation involving ID4 in B-cell precursor acute lymphoblastic leukemia (BCP-ALL)," Blood, vol. 111, no. 1, pp. 387-91, Jan 1, 2008.
14. L. Milani, A. Lundmark, A. Kiialainen et al., "DNA methylation for subtype classification and prediction of treatment outcome in patients with childhood acute lymphoblastic leukemia," Blood, vol. 115, no. 6, pp. 1214-25, Feb 11, 2010.