ArticleBMC bioinformatics2010
Global screening of potential Candida albicans biofilm-related transcription factors via network comparison.
Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 35 citations in OpenAlex.
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- Associations of Rap1 with Cell Wall Integrity, Biofilm Formation, and Virulence in Candida albicans.Microbiology spectrum · 2022Article
- Investigating Common Pathogenic Mechanisms betweenToxins · 2019Article
- The possible molecular mechanisms of farnesol on the antifungal resistance of C. albicans biofilms: the regulation of CYR1 and PDE2.BMC microbiology · 2018Article
- Statistical significance approximation in local trend analysis of high-throughput time-series data using the theory of Markov chains.BMC bioinformatics · 2015Article
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- Secretomes are a potential source of molecular targets for cancer therapies and indicate that APOE is a candidate biomarker for lung adenocarcinoma metastasis.Molecular biology reports · 2014Article
- The role of Mss11 in Candida albicans biofilm formation.Molecular genetics and genomics : MGG · 2014Article
- Essential functional modules for pathogenic and defensive mechanisms in Candida albicans infections.BioMed research international · 2014Article
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- Interspecies protein-protein interaction network construction for characterization of host-pathogen interactions: a Candida albicans-zebrafish interaction study.BMC systems biology · 2013Article
- Harnessing the complexity of gene expression data from cancer: from single gene to structural pathway methods.Biology direct · 2012Review
- Candida albicans: A Model Organism for Studying Fungal Pathogens.ISRN microbiology · 2012Article
- Prediction of phenotype-associated genes via a cellular network approach: a Candida albicans infection case study.PloS one · 2012Article
- Constructing gene regulatory networks for long term photosynthetic light acclimation in Arabidopsis thaliana.BMC bioinformatics · 2011Article
- A network-based biomarker approach for molecular investigation and diagnosis of lung cancer.BMC medical genomics · 2011Article
- Prediction of body fluids where proteins are secreted into based on protein interaction network.PloS one · 2011Article
- Modelling biochemical networks with intrinsic time delays: a hybrid semi-parametric approach.BMC systems biology · 2010Article
- Systems biology approaches to understanding mycobacterial survival mechanisms.Drug discovery today. Disease mechanisms · 2010Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCandida albicans is a commonly encountered fungal pathogen in humans. The formation of biofilm is a major virulence factor in C. albicans pathogenesis and is related to antidrug resistance of this organism. Although many factors affecting biofilm have been analyzed, molecular mechanisms that regulate biofilm formation still await to be elucidated.
resultsIn this study, from the gene regulatory network perspective, we developed an efficient computational framework, which integrates different kinds of data from genome-scale analysis, for global screening of potential transcription factors (TFs) controlling C. albicans biofilm formation. S. cerevisiae information and ortholog data were used to infer the possible TF-gene regulatory associations in C. albicans. Based on TF-gene regulatory associations and gene expression profiles, a stochastic dynamic model was employed to reconstruct the gene regulatory networks of C. albicans biofilm and planktonic cells. The two networks were then compared and a score of relevance value (RV) was proposed to determine and assign the quantity of correlation of each potential TF with biofilm formation. A total of twenty-three TFs are identified to be related to the biofilm formation; ten of them are previously reported by literature evidences.
conclusionsThe results indicate that the proposed screening method can successfully identify most known biofilm-related TFs and also identify many others that have not been previously reported. Together, this method can be employed as a pre-experiment screening approach that reveals new target genes for further characterization to understand the regulatory mechanisms in biofilm formation, which can serve as the starting point for therapeutic intervention of C. albicans infections.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.