A computational model to define the molecular causes of type 2 diabetes mellitus.
暂无分享,去创建一个
Steve Hoberman | Atul J Butte | Jack Pollard | A. Butte | S. Hoberman | J. Pollard | Monica Joshi | Josh Levy | J. Pappo | Monica Joshi | Josh Levy | Jacques Pappo | M. Joshi | Jack Pollard
[1] Benno Schwikowski,et al. Discovering regulatory and signalling circuits in molecular interaction networks , 2002, ISMB.
[2] John J. Rice,et al. Making the most of it: pathway reconstruction and integrative simulation using the data at hand , 2004 .
[3] Bertram L Kasiske,et al. Diabetes Mellitus after Kidney Transplantation in the United States , 2003, American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons.
[4] D. Botstein,et al. Cluster analysis and display of genome-wide expression patterns. , 1998, Proceedings of the National Academy of Sciences of the United States of America.
[5] Tommi S. Jaakkola,et al. Using Graphical Models and Genomic Expression Data to Statistically Validate Models of Genetic Regulatory Networks , 2000, Pacific Symposium on Biocomputing.
[6] P. Mertz,et al. Calcineurin: form and function. , 2000, Physiological reviews.
[7] F. Dumont,et al. Down-regulation of cell surface CXCR6 expression during T cell activation is predominantly mediated by calcineurin. , 2003, Cellular immunology.
[8] Joshua M. Stuart,et al. MICROARRAY EXPERIMENTS : APPLICATION TO SPORULATION TIME SERIES , 1999 .
[9] H. Kirchner,et al. Sensitivity of whole-blood T lymphocytes in individual patients to tacrolimus (FK 506): impact of interleukin-2 mRNA expression as surrogate measure of immunosuppressive effect. , 2004, Clinical chemistry.
[10] Daniel E. Zak,et al. Importance of input perturbations and stochastic gene expression in the reverse engineering of genetic regulatory networks: insights from an identifiability analysis of an in silico network. , 2003, Genome research.
[11] A. Butte,et al. Coordinated reduction of genes of oxidative metabolism in humans with insulin resistance and diabetes: Potential role of PGC1 and NRF1 , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[12] I S Kohane,et al. Mutual information relevance networks: functional genomic clustering using pairwise entropy measurements. , 1999, Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing.
[13] Lyle H. Ungar,et al. Using prior knowledge to improve genetic network reconstruction from microarray data , 2004, Silico Biol..
[14] Jiandie D. Lin,et al. An autoregulatory loop controls peroxisome proliferator-activated receptor gamma coactivator 1alpha expression in muscle. , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[15] Ross Ihaka,et al. Gentleman R: R: A language for data analysis and graphics , 1996 .
[16] F. Cosio,et al. Patient survival after renal transplantation: IV. Impact of post-transplant diabetes. , 2002, Kidney international.
[17] S Fuhrman,et al. Reveal, a general reverse engineering algorithm for inference of genetic network architectures. , 1998, Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing.
[18] John Quackenbush,et al. Open source software for the analysis of microarray data. , 2003, BioTechniques.
[19] Jiahuai Han,et al. Calcineurin Enhances MAPK Phosphatase-1 Expression and p38 MAPK Inactivation in Cardiac Myocytes* , 2001, The Journal of Biological Chemistry.
[20] J. Mesirov,et al. Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation. , 1999, Proceedings of the National Academy of Sciences of the United States of America.
[21] M. Daly,et al. PGC-1α-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes , 2003, Nature Genetics.
[22] T. Jenssen,et al. A literature network of human genes for high-throughput analysis of gene expression , 2001, Nature Genetics.
[23] Nir Friedman,et al. Inferring subnetworks from perturbed expression profiles , 2001, ISMB.
[24] Patrik D'haeseleer,et al. Genetic network inference: from co-expression clustering to reverse engineering , 2000, Bioinform..
[25] Jiandie D. Lin,et al. An autoregulatory loop controls peroxisome proliferator-activated receptor γ coactivator 1α expression in muscle , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[26] F. Doyle,et al. Insights From an Identifiability Analysis of an In Silico Network in the Reverse Engineering of Genetic Regulatory Networks : Importance of Input Perturbations and Stochastic Gene Expression data , 2003 .
[27] R. Balshaw,et al. New Onset Diabetes Mellitus in Patients Receiving Calcineurin Inhibitors: A Systematic Review and Meta‐Analysis , 2004, American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons.
[28] M. Schnitzler. Diabetes Mellitus After Kidney Transplantation in the United States , 2003, American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons.