Literature DB >> 18086872

Extracting global system dynamics of corticosteroid genomic effects in rat liver.

E Yang1, R R Almon, D C Dubois, W J Jusko, I P Androulakis.   

Abstract

One of the challenges in constructing biological models involves resolving meaningful data patterns from which the mathematical models will be generated. For models that describe the change of mRNA in response to drug administration, questions exist whether the correct genes have been selected given the myriad transcriptional effects that may occur. Oftentimes, different algorithms will select or cluster different groups of genes from the same data set. A new approach was developed that focuses on identifying the underlying global dynamics of the system instead of selecting individual genes. The procedure was applied to microarray genomic data obtained from rat liver after a large single dose of methylprednisolone in 52 adrenalectomized rats. Twelve clusters of at least 30 genes each were selected, reflecting the major changes over time. This method along with isolating the underlying dynamics of the system also extracts and clusters the genes that make up this global dynamic for further analysis as to the contributions of specific mechanisms affected by the drug.

Entities:  

Mesh:

Substances:

Year:  2007        PMID: 18086872      PMCID: PMC3725546          DOI: 10.1124/jpet.107.133074

Source DB:  PubMed          Journal:  J Pharmacol Exp Ther        ISSN: 0022-3565            Impact factor:   4.030


  18 in total

1.  Genome-wide expression analysis reveals 100 adrenal gland-dependent circadian genes in the mouse liver.

Authors:  Katsutaka Oishi; Noriko Amagai; Hidenori Shirai; Koji Kadota; Naoki Ohkura; Norio Ishida
Journal:  DNA Res       Date:  2005       Impact factor: 4.458

2.  Comparison of four basic models of indirect pharmacodynamic responses.

Authors:  N L Dayneka; V Garg; W J Jusko
Journal:  J Pharmacokinet Biopharm       Date:  1993-08

3.  A microarray analysis of the temporal response of liver to methylprednisolone: a comparative analysis of two dosing regimens.

Authors:  Richard R Almon; Debra C DuBois; William J Jusko
Journal:  Endocrinology       Date:  2007-02-15       Impact factor: 4.736

4.  Dose-dependence and repeated-dose studies for receptor/gene-mediated pharmacodynamics of methylprednisolone on glucocorticoid receptor down-regulation and tyrosine aminotransferase induction in rat liver.

Authors:  Y N Sun; D C DuBois; R R Almon; N A Pyszczynski; W J Jusko
Journal:  J Pharmacokinet Biopharm       Date:  1998-12

5.  Cluster analysis and display of genome-wide expression patterns.

Authors:  M B Eisen; P T Spellman; P O Brown; D Botstein
Journal:  Proc Natl Acad Sci U S A       Date:  1998-12-08       Impact factor: 11.205

6.  A comparison of DNA copy number profiling platforms.

Authors:  Joel Greshock; Bin Feng; Cristina Nogueira; Elena Ivanova; Ilana Perna; Katherine Nathanson; Alexei Protopopov; Barbara L Weber; Lynda Chin
Journal:  Cancer Res       Date:  2007-10-29       Impact factor: 12.701

7.  Systematic survey reveals general applicability of "guilt-by-association" within gene coexpression networks.

Authors:  Cecily J Wolfe; Isaac S Kohane; Atul J Butte
Journal:  BMC Bioinformatics       Date:  2005-09-14       Impact factor: 3.169

8.  STEM: a tool for the analysis of short time series gene expression data.

Authors:  Jason Ernst; Ziv Bar-Joseph
Journal:  BMC Bioinformatics       Date:  2006-04-05       Impact factor: 3.169

9.  Bioinformatics analysis of the early inflammatory response in a rat thermal injury model.

Authors:  Eric Yang; Timothy Maguire; Martin L Yarmush; Francois Berthiaume; Ioannis P Androulakis
Journal:  BMC Bioinformatics       Date:  2007-01-10       Impact factor: 3.169

10.  How to decide? Different methods of calculating gene expression from short oligonucleotide array data will give different results.

Authors:  Frank F Millenaar; John Okyere; Sean T May; Martijn van Zanten; Laurentius A C J Voesenek; Anton J M Peeters
Journal:  BMC Bioinformatics       Date:  2006-03-15       Impact factor: 3.169

View more
  7 in total

1.  A new symbolic representation for the identification of informative genes in replicated microarray experiments.

Authors:  Jeremy D Scheff; Richard R Almon; Debra C DuBois; William J Jusko; Ioannis P Androulakis
Journal:  OMICS       Date:  2010-06

Review 2.  Transitioning from Basic toward Systems Pharmacodynamic Models: Lessons from Corticosteroids.

Authors:  Vivaswath S Ayyar; William J Jusko
Journal:  Pharmacol Rev       Date:  2020-04       Impact factor: 25.468

Review 3.  Moving from basic toward systems pharmacodynamic models.

Authors:  William J Jusko
Journal:  J Pharm Sci       Date:  2013-05-16       Impact factor: 3.534

4.  Pathway-level analysis of genome-wide circadian dynamics in diverse tissues in rat and mouse.

Authors:  Alison Acevedo; Panteleimon D Mavroudis; Debra DuBois; Richard R Almon; William J Jusko; Ioannis P Androulakis
Journal:  J Pharmacokinet Pharmacodyn       Date:  2021-03-25       Impact factor: 2.745

5.  Understanding Physiology in the Continuum: Integration of Information from Multiple -Omics Levels.

Authors:  Kubra Kamisoglu; Alison Acevedo; Richard R Almon; Susette Coyle; Siobhan Corbett; Debra C Dubois; Tung T Nguyen; William J Jusko; Ioannis P Androulakis
Journal:  Front Pharmacol       Date:  2017-02-27       Impact factor: 5.810

6.  Pathway-Based Analysis of the Liver Response to Intravenous Methylprednisolone Administration in Rats: Acute Versus Chronic Dosing.

Authors:  Alison Acevedo; Ana Berthel; Debra DuBois; Richard R Almon; William J Jusko; Ioannis P Androulakis
Journal:  Gene Regul Syst Bio       Date:  2019-04-15

Review 7.  Nutritional systems biology modeling: from molecular mechanisms to physiology.

Authors:  Albert A de Graaf; Andreas P Freidig; Baukje De Roos; Neema Jamshidi; Matthias Heinemann; Johan A C Rullmann; Kevin D Hall; Martin Adiels; Ben van Ommen
Journal:  PLoS Comput Biol       Date:  2009-11-26       Impact factor: 4.475

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.