ArticlePloS one2012
Prediction of phenotype-associated genes via a cellular network approach: a Candida albicans infection case study.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
7 citing papers in PubMed, 14 citations in OpenAlex.
- Emerging antifungal strategies against Candida albicans using metal-organic frameworks and novel therapeutics: Opportunities and challenges.Journal of food and drug analysis · 2026Review
- Extracellular vesicle production: A bidirectional effect in the interplay between host andCurrent research in microbial sciences · 2024Review
- Regulatory network controls microbial biofilm development, withBioengineered · 2022Review
- Identifying novel protein phenotype annotations by hybridizing protein-protein interactions and protein sequence similarities.Molecular genetics and genomics : MGG · 2016Article
- Sulfone derivatives reduce growth, adhesion and aspartic protease SAP2 gene expression.World journal of microbiology & biotechnology · 2014Article
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Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Candida albicans is the most prevalent opportunistic fungal pathogen in humans causing superficial and serious systemic infections. The infection process can be divided into three stages: adhesion, invasion, and host cell damage. To enhance our understanding of these C. albicans infection stages, this study aimed to predict phenotype-associated genes involved during these three infection stages and their roles in C. albicans-host interactions. In light of the principles that proteins that lie closer to one another in a protein interaction network are more likely to have similar functions, and that genes regulated by the same transcription factors tend to have similar functions, a cellular network approach was proposed to predict the phenotype-associated genes in this study. A total of 4, 12, and 3 genes were predicted as adhesion-, invasion-, and damage-associated genes during C. albicans infection, respectively. These predicted genes highlight the facts that cell surface components are critical for cell adhesion, and that morphogenesis is crucial for cell invasion. In addition, they provide targets for further investigations into the mechanisms of the three C. albicans infection stages. These results give insights into the responses elicited in C. albicans during interaction with the host, possibly instrumental in identifying novel therapies to treat C. albicans infection.
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Registered trials
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