Identifying regulatory targets of cell cycle transcription factors using gene expression and ChIP-chip data

Wu, Wei; Li, Wen-Hsiung; Chen, Bor Sen

doi:10.1186/1471-2105-8-188

Cited by 38 publications

(46 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…It has been shown that TF binding usually affects gene expression in a nonlinear fashion: below some level it has no effect, while above a certain level the effect may become saturated [29,30]. Thus, the regulation function z j [ t ] was modeled as the sigmoid function, which is one kind of Hill function, of y j [ t ] (the protein activity profiles of transcription factor j ) [3,16,30-33]…”

Section: Resultsmentioning

confidence: 99%

Integrated cellular network of transcription regulations and protein-protein interactions

Wang

Chen

2010

BMC Syst Biol

Self Cite

View full text Add to dashboard Cite

BackgroundWith the accumulation of increasing omics data, a key goal of systems biology is to construct networks at different cellular levels to investigate cellular machinery of the cell. However, there is currently no satisfactory method to construct an integrated cellular network that combines the gene regulatory network and the signaling regulatory pathway.ResultsIn this study, we integrated different kinds of omics data and developed a systematic method to construct the integrated cellular network based on coupling dynamic models and statistical assessments. The proposed method was applied to S. cerevisiae stress responses, elucidating the stress response mechanism of the yeast. From the resulting integrated cellular network under hyperosmotic stress, the highly connected hubs which are functionally relevant to the stress response were identified. Beyond hyperosmotic stress, the integrated network under heat shock and oxidative stress were also constructed and the crosstalks of these networks were analyzed, specifying the significance of some transcription factors to serve as the decision-making devices at the center of the bow-tie structure and the crucial role for rapid adaptation scheme to respond to stress. In addition, the predictive power of the proposed method was also demonstrated.ConclusionsWe successfully construct the integrated cellular network which is validated by literature evidences. The integration of transcription regulations and protein-protein interactions gives more insight into the actual biological network and is more predictive than those without integration. The method is shown to be powerful and flexible and can be used under different conditions and for different species. The coupling dynamic models of the whole integrated cellular network are very useful for theoretical analyses and for further experiments in the fields of network biology and synthetic biology.

show abstract

Section: Resultsmentioning

confidence: 99%

Integrated cellular network of transcription regulations and protein-protein interactions

Wang

Chen

2010

BMC Syst Biol

Self Cite

View full text Add to dashboard Cite

show abstract

“…In patients with chronic illnesses, depression may occur due to adverse circumstances including loss of role in the workplace and family, decreased mobility, decreased physical and cognitive competence and loss of sexual function [1]. Elevated proinflammatory cytokines in patients with chronic illness may be a product of the disease itself and associations between elevated cytokine levels and increased depression among patients with chronic medical illnesses may, in fact, be unrelated.…”

Section: Discussionmentioning

confidence: 99%

“…Depression is the most common psychological problem encountered among patients with chronic kidney disease (CKD) and end-stage renal disease (ESRD) [1, 2], and is associated with increased morbidity and mortality in these patients [3]. Depressive disorders and medical illnesses are linked by several mechanisms [4].…”

Section: Introductionmentioning

confidence: 99%

Depressive Symptoms and Proinflammatory Cytokine Levels in Chronic Renal Failure Patients

Dervişoğlu¹,

Kır²,

Kalender³

et al. 2008

Nephron Clin Pract

View full text Add to dashboard Cite

Background/Aims: Cytokine secretion is known to play an important role in the pathophysiology of depression, and levels of proinflammatory cytokines are increased in chronic renal failure (CRF) patients. The objective of this study was to examine the correlation between levels of proinflammatory cytokines in CRF patients and degree of depression. Methods: 31 patients on hemodialysis, 31 patients on continuous ambulatory peritoneal dialysis, and 31 conservatively managed chronic kidney disease (CKD) patients were enrolled in this study. Depressive symptoms were measured with the Beck Depression Inventory (BDI), and ‘elevated symptoms of depression’ were defined as a BDI score ≧17. IL-6 and TNFα cytokine levels were measured by ELISA. Results: ‘Elevated symptoms of depression’ occurred in 37 of 93 patients (40%). IL-6 and TNFα levels were not significantly different among CRF patients with and without elevated depressive symptoms (p = 0.937 and p = 0.414, respectively). When analyzed by treatment subgroup, proinflammatory cytokine levels were not significantly different in patients with and without elevated symptoms of depression. Conclusion: In patients with CRF, elevated symptoms of depression were not associated with increased cytokine levels.

show abstract

“…To identify the intercellular PPIs between pathogen and host during infection of zebrafish with C. albicans , we utilized the Temporal Relationship Identification Algorithm (TRIA), which uses gene expression data to identify a given transcription factor's regulatory targets from its binding targets as inferred from ChIP-chip data [22]. The first step was to build a pool of C. albicans cell surface proteins.…”

Section: Methodsmentioning

confidence: 99%

Identification of Infection- and Defense-Related Genes via a Dynamic Host-Pathogen Interaction Network Using a Candida Albicans-Zebrafish Infection Model

Kuo¹,

Chuang²,

Chao³

et al. 2013

J Innate Immun

Self Cite

View full text Add to dashboard Cite

Candida albicans infections and candidiasis are difficult to treat and create very serious therapeutic challenges. In this study, based on interactive time profile microarray data of C. albicans and zebrafish during infection, the infection-related protein-protein interaction (PPI) networks of the two species and the intercellular PPI network between host and pathogen were simultaneously constructed by a dynamic interaction model, modeled as an integrated network consisting of intercellular invasion and cellular defense processes during infection. The signal transduction pathways in regulating morphogenesis and hyphal growth of C. albicans were further investigated based on significant interactions found in the intercellular PPI network. Two cellular networks were also developed corresponding to the different infection stages (adhesion and invasion), and then compared with each other to identify proteins from which we can gain more insight into the pathogenic role of hyphal development in the C. albicans infection process. Important defense-related proteins in zebrafish were predicted using the same approach. The hyphal growth PPI network, zebrafish PPI network and host-pathogen intercellular PPI network were combined to form an integrated infectious PPI network that helps us understand the systematic mechanisms underlying the pathogenicity of C. albicans and the immune response of the host, and may help improve medical therapies and facilitate the development of new antifungal drugs.

show abstract

Identifying regulatory targets of cell cycle transcription factors using gene expression and ChIP-chip data

Cited by 38 publications

References 41 publications

Integrated cellular network of transcription regulations and protein-protein interactions

Integrated cellular network of transcription regulations and protein-protein interactions

Depressive Symptoms and Proinflammatory Cytokine Levels in Chronic Renal Failure Patients

Identification of Infection- and Defense-Related Genes via a Dynamic Host-Pathogen Interaction Network Using a Candida Albicans-Zebrafish Infection Model

Contact Info

Product

Resources

About