Slides on the Duke ICBP
Publications and Manuscripts
-
Tools for exploration and annotation of pathway data
-
J.T. Chang and J.R. Nevins (2006)
GATHER: a systems approach to interpreting genomic signatures.
Bioinformatics, 22, 2926-2933.
The related software/GATHER system is available under the Software link.
-
M. DeLong, G. Yao, Q. Wang, A. Dobra, E.P. Black, J.T. Chang, A. Bild, M. West, J.R. Nevins and H.K. Dressman (2005)
DIG - A system for gene annotation and functional discover.
Bioinformatics, 21, 2957-2959.
The related software/DIG system is available under the Sharing link.
-
Biological pathway analysis and cancer genomics applications
-
J.Y. Leung, G.L. Ehmann, P.H. Giangrande and J.R. Nevins (2008)
A role for Myc in facilitating transcription activation by E2F1.
Oncogene, Mar 17. [Epub ahead of print].
-
S. Mori, R.E. Rempel, J.T. Chang, G. Yao, A.S. Lagoo, A. Potti and J.R. Nevins (2008)
Dissecting the heterogeneity of B lymphoma with expression signatures.
Submitted.
-
E.J. Edelman, J. Guinney, J.T. Chi, P.G. Febbo and S. Mukherjee (2008)
Modeling cancer progression via pathway dependencies.
PLoS Comput Biol., 4, e28.
-
G. Yao, T.J. Lee, S. Mori, J.R. Nevins and L. You (2008)
A bistable Myc-Rb-E2F switch: a model for the restriction point.
Nat Cell Biol., 10, 476-482.
-
J.L. Chen, J.E. Lucas, T. Schroeder, S. Mori, J.R. Nevins, M. Dewhirst, M. West and J.T. A. Chi (2008)
Genomic analysis of response to lactic acidosis in human cancers.
Submitted.
- A. Potti and J.R. Nevins (2008)
Utilization of genomic signatures to direct use of primary chemotherapy.
Curr Opin Genet Dev, Mar 11. [Epub ahead of print].
- T.C. Hallstrom, S. Mori and J.R. Nevins (2008)
An E2F1-dependent gene expression program that determines the balance between proliferation and cell death.
Cancer Cell, 13, 11-22.
- J.R. Nevins (2007)
New breast cancer genes-discovery at the intersection of complex data sets.
Cancer Cell, 12, 497-499.
-
D.S. Hsu, B.S. Balakamaran, C.R. Acharya, V. Vlahovic, K.S. Walters, K. Garman, C. Anders, R.F. Riedel, J. Lancaster, D. Harpole, H.K. Dressman, J.R. Nevins, P. Febbo and A. Potti (2007)
Pharmocogenomic strategies provide a rational approach to the treatment of cisplatin-resistant patients with advanced cancer.
J Clin Oncol., 25, 4350-4357.
-
J.R. Nevins and A. Potti (2007)
Mining gene expression profiles: expression signatures as cancer phenotypes.
Nat Rev Genet., 8, 601-609.
-
H.K. Dressman, G. Chan, J. Zhai, A. Bild, J. Cragun, R. Sayer, J. Clarke, R. Whitaker, J. Gray, J. Marks, G. Ginsburg, A. Potti, M. West, A. Berchuck, J.R. Nevins and J.M. Lancaster (2007)
An integrated genomic-based approach to individualized treatment of patients with advanced-stage ovarian cancer.
J Clin Oncol., 25, 517-525.
-
L.J. Kong, J.T. Chang and J.R. Nevins (2007)
Compensation and specificity of function within the E2F family.
Oncogene, 26, 321-327.
-
T.C. Hallstrom and J.R. Nevins (2006)
Jab1 is a specificity factor for E2F1-induced apoptosis.
Genes Dev., 20, 613-623.
-
A. Bild, A. Potti and J.R. Nevins (2006)
Linking oncogenic pathways with therapeutic opportunities.
Nat Rev Cancer, 6, 735-741.
-
A. Potti, H.K. Dressman, A. Bild, R.F. Riedel, G. Chan,
R. Sayer, J. Cragun,
H. Cottrill, M.J. Kelley, R. Petersen, D. Harpole,
J. Marks, A. Berchuck,
G.S. Ginsburg, P. Febbo, J. Lancaster and J.R. Nevins (2006)
Genomic signatures to guide the use of chemotherapeutics.
Nat Med., 12, 1294-1300.
-
A. Potti, S. Mukherjee, R. Prince, H.K. Dressman, A. Bild, J. Koontz,
R. Kratzke, M.A. Watson, M. Kelley, G. Ginsburg, M. West, D.H. Harpole and J.R. Nevins (2006)
A genomic strategy to refine prognosis in early-stage non-small-cell lung cancer.
N Engl J Med., 355, 570-580.
- A.H. Bild, G. Yao, J.T. Chang, Q. Wang, A. Potti, D. Chasse, M. Joshi, D. Harpole,
J.M. Lancaster, A. Berchuck, J.A. Olson, J.R. Marks, H.K. Dressman, M.West and J.R. Nevins (2006)
Oncogenic pathway signatures in human cancers as a guide to targeted therapies.
Nature, 439, 353-357.
The related cell line gene expression data sets are available under the Data link.
The related software tools (binary regression prediction)
are available under the Software link.
-
E. Edelman, A. Porrello, J. Guinney, B. Balakumaran, A. Bild, P.G. Febbo and S. Mukherjee (2006)
Analysis of sample set enrichment scores: assaying the enrichment of sets of genes for individual samples in genome-wide expression profiles.
Bioinformatics, 22, e108-116.
- E.P. Black, T. Hallstrom, H.K. Dressman, M. West and J.R. Nevins (2005)
Distinctions in the specificity of E2F function revealed by gene expression signatures.
Proc. Natl. Acad. Sci. USA, 102, 15948-15953.
- W. Zhu, P.H. Giangrande and J.R. Nevins (2004)
E2Fs link the control of G1/S and G2/M transcription.
EMBO J., 23, 4615-4626.
-
Promoter sequence analysis
-
Sparse statistical modelling for genomics and pathway analysis: Gene expression factor models and related analyses
-
J.E. Lucas, C.M. Carvalho, D. Merl and M. West (2008)
In-vitro to In-vivo factor profiling in expression genomics.
In Bayesian Modelling in Bioinformatics,
(Eds. D. Dey, S. Ghosh and B. Mallick), Taylor-Francis, in press.
-
D. Merl, J.E. Lucas, H. Shen and M. West (2008)
Trans-study projection of genomic biomarkers using sparse factor
regression models.
In The Handbook of Applied Bayesian Analysis,
Oxford University Press, in press.
-
H. Shen and M. West (2008)
Bayesian modeling for biological pathway annotation of genomic signatures.
Submitted.
-
J. Lucas, C. Carvalho, J.T.A. Chi and M. West (2007)
Bench-to-bedside and cross-study projection of genomic markers: An evaluation in breast cancer genomics.
Submitted.
-
J.L. Chen, J.E. Lucas, M. West and J.T. Chi (2007)
Genomic analysis of response to lactic acidosis in human cancers.
- J.T. Chang, C. Carvalho, S. Mori, A. Bild, Q. Wang, M. West and J.R. Nevins (2007)
Decomposing cellular signalling pathways into functional units: A
genomic strategy.
-
P. Goldschmidt, D. Seo and M. West (2007)
Of Mice and Men: Sparse Statistical Modelling in Cardiovascular Genomics.
-
C. Carvalho, J.T. Chang, J. Lucas, Q. Wang, J.R. Nevins and M. West (2006)
High-Dimensional Sparse Factor Modelling: Applications in Gene Expression Genomics.
Journal of the American Statistical Association, in press.
-
J. Lucas, C. Carvalho, Q. Wang, A. Bild, J.R. Nevins and M. West (2006)
Sparse statistical modelling in gene expression genomics.
In Bayesian Inference for Gene Expression and Proteomics, (Eds. K.A. Do, P. Mueller and M. Vannucci),
Cambridge University Press, pp155-176.
The related comprehrensive software package BFRM is also available under the Software link.
-
Image analysis
-
Graphical models of gene expression networks
- M. Xu, M.J. Kao, J. Nunez_Iglesias, J.R. Nevins, M. West and X.J. Zhou (2008)
An integrative approach to characterize disease-specific pathways and their coordination: a case study in cancer.
BMC Genomics, 9, Suppl 1:S12.
- Y. Huang, H. Li, H. Hu, X. Yan, M.S. Waterman, H. Huang and X.J. Zhou (2007)
Systematic Discovery of Functional Modules and Context-Specific Functional Annotation of Human Genome.
Bioinformatics (ISMB 2007), 23, i222-i229.
- X. Yan, M. Mehan, Y. Huang, M.S. Waterman, P.S. Yu and X.J. Zhou (2007)
A Graph-based Approach to Systematically Reconstruct Human Transcriptional Regulatory Modules.
Bioinformatics (ISMB 2007), 23, i577-i586.
- H. Hu, X. Yan, Y. Huang, J. Han and X.J. Zhou (2005)
Mining coherent dense subgraphs across massive biological networks for functional discovery.
Bioinformatics (ISMB 2005), 21, i213-i221.
The related software tools CODENSE and iARRAY ANALYZER can be found under the Software link.
-
Protein interaction network models
- M.A. Pujana,J.D. Han, L.M. Starita, K.N. Stevens, M. Tewari, J.S. Ahn, G. Rennert,
V. Moreno, T. Kirchhoff, B. Gold, V. Assmann, W.M. ElShamy, J.F. Rual, D. Levine,
L.S. Rozek, R.S. Gelman, K.C. Gunsalus, R.A. Greenberg, B. Sobhian, N. Bertin,
K. Venkatesan, N. Ayivi-Guedehoussou, X. Sole, P. Hernandez, C. Lazaro, K.L. Nathanson, B.L. Weber, M.E. Cusick, D.E. Hill, K. Offit, D.M. Livingston, S.B. Gruber, J.D. Parvin and M. Vidal (2007)
Network modeling links breast cancer susceptibility and
centrosome dysfunction.
Nat Genet., 39, 1338-1349.
|
| |
|