Introduction

Participants

Papers

Links

Credits

REPORTS

First Year Report: Executive Summary

Full Report

NEWS:

(1) "Genome Wide Analysis of the Endothelial Transcriptome Under Short-Term Chronic Hypoxia". [abstract]

(2) "Identifying genes altered by a drug in temporal microarray data: A case study." Winnder, American Statistical Association 2003 Biopharm Student Paper Competition Award. [pdf]

(3) Influence of age, sex, and strength training on human muscle gene expression determined by microarray [abstract]

(4) Experiments on Accuracy of Algorithms for Inferring Structure of Regulatory Networks [pdf]

(5) Learning from SAGE Data [pdf]

(6) Analysis of Microarray Data for Treated Fat Cells [pdf]

Computational Systems Biology Group

Papers.

  • Chu, T. (2002) A Statistical Analysis of SAGE Data. [pdf]
  • Chu, T. (2002). Sampling, Amplifying, and Resampling. Technical Report, CMU-PHIL-133, Department of Philosophy, Carnegie Mellon University. [pdf]
  • Chu, T. (2003). Learning from SAGE Data. Ph.D. Dissertation. Philosophy Dept., Carnegie Mellon University, Jan., 2003. [pdf]
  • Chu, T, Glymour, C., Scheines, R., and Spirtes, P. (2003). A Statistical Problem for Inference to Regulatory Structure from Associations of Gene Expression Measurement with Microarrays. Bioinformatics, 19(9):1147-1152 . [pdf]
  • Chu, T. (2004). Invited Presentation: "Limitations of Statistical Learning from Gene Expression Data," Interface 2004:Computational Biology and Bioinformatics. [pdf]
  • Danks, D., Glymour, C., Spirtes, P. (2002). Inference and Experimental Design for the Discovery of Genetic Regulatory Structure through Experimental Interventions: Statistical Realism and Combinatorial Complexity. [pdf]
  • Danks, D., Glymour, C., Spirtes, P. (2002). Confirmation versus Search in Gene Regulation: The Complexity of Gene Perturbation Experimentation as a Search Method. IJCAI Bioinformatics Workshop. [pdf]
  • Handley D. Evaluating machine learning algorithms used to infer gene regulatory networks. Master's thesis. Philosophy Dept., Carnegie Mellon University, Nov. 2002. [pdf]
  • Handley, D., Serban, N., Peters, D., O'Doherty, R., Field, M., Wasserman, L., Spirtes, P., Scheines, R., and Glymour, C. (2002) Evidence of cross-hybridization artifact in expressed sequence tags (ESTs) on cDNA microarrays. Submitted to Genome Research. [mss pdf] [abstract]
  • Kassam, A., Chang, Y., O'Hare, E., and Peters, D. (2003). Endoglin Gene Variation and Expression in the Pathogenesis of Intracranial Aneurysms. Submitted, J.Neurosurgery.[pdf]
  • Kassam, A., Chang, Y., Ferrell, R., and Peters, D. (2003). A Functional Polymorphism in the Endothelial Nitric Oxide Synthase Gene is a Risk Factor for Subarachnoid Hemorrhage in Normotensive Patients with Intracranial Aneurysms. Submitted, J. Neurosurgery. [pdf]
  • Ning W., Chu, T. , Li, C.J., C hoi, A., and Peters, D. Genome Wide Analysis of the Endothelial Transcriptome Under Short-Term Chronic Hypoxia Physiol. Genomics (April 20, 2004). 10.1152. [abstract]
  • Ning, W. and 13 others. Comprehensive gene expression profile of Human Chronic Obstructive Pulmonary Disease (COPD) by Serial Analysis of Gene Expression (SAGE) and microarray analysis reveal novel pathways related to the pathogenesis of COPD. Under review. [data]
  • Peters, D., Chu, T., and Glymour, C. (2003). Serial Analysis of the Vascular Endothelial Transcriptome Under Static and Shear Stress Conditions. Submitted, Physiological Genomics. [pdf]
  • Peters DG, Zhang XC, Benos PV, Heidrich-O'Hare E, Ferrell RE. (2002) Genomic analysis of the immediate/early response to shear stress in human coronary artery endothelial cells. Physiol Genomics 2002 Oct 29. [abstract]
  • Roth SM, Ferrell RE, Peters DG, Metter EJ, Hurley BF, Rogers MA. (2002) Influence of age, sex, and strength training on human muscle gene expression determined by microarray. Physiol Genomics 2002 Sep 3;10(3):181-90. [abstract]
  • Scheines, R. and Ramsey, J (2001). Simulating Genetic Regulatory Networks. Technical Report, CMU-PHIL-124, Department of Philosophy, Carnegie Mellon University. [pdf]
  • Serban, N., Wasserman, L., Peters, D., Spirtes, P., O'Doherty, R., Handley, D., Scheines, R. and Glymour, C. Analysis of microarray data for treated fat cells. Technical Report, Department of Statistics, Carnegie Mellon University. [pdf]
  • Serban, N. and Wasserman, L. "Identifying genes altered by a drug in temporal microarray data: A case study." Joint Statistical Meeting 2003. Winner, American Stastical Association 2003 Biopharm Student Paper Competition Award.
  • Spirtes, P., Glymour, G., Kauffman, S., Scheines, R., Aimalie, V., and Wimberly, F. (2000). Constructing Bayesian Network Models of Gene Expression Networks from Microarray Data. To appear in the Proceedings of the Atlantic Symposium on Computational Biology, Genome Information Systems & Technology. [pdf]
  • Wimberly, F., Heiman, T., Ramsey, J. and Glymour, C. (2003) Experiments on the Accuracy of Algorithms for Inferring the Structure of Genetic Regulatory Networks from Microarray Expression Levels. [pdf]
    • Data [zip (7.54 MB)]
  • Yoo, C. and Cooper, G. (2002) Discovery of Gene-Regulation Pathways using Local Causal Search. AMIA Symposium 2002, San Antonio, TX. [pdf]
  • Yoo, C. and Cooper, F. (2003) An Evaluation of a System that Recommends Microarray Experiments to Perform to Discover Gene-Regulation Pathways. In press, Journal Artificial Intelligence in Medicine. [pdf]
  • Yoo, C., Thorsson, V., and Cooper, G. (2002). Discovery of Causal Relationships in Gene Regulation Pathways from a Mixture of Experimental and Observational DNA Microarray Data. [pdf]
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jdramsey@andrew.cmu.edu