FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2114372600> ?p ?o ?g. }

• W2114372600 abstract "Reverse engineering of gene regulatory networks can be used to predict regulatory interactions of an organism faced with environmental changes, but can prove problematic, especially when focusing on complicated multi-factorial processes. Candida albicans is a major human fungal pathogen. During the infection process, this fungus is able to adapt to conditions of very low iron availability. Such adaptation is an important virulence attribute of virtually all pathogenic microbes. Understanding the regulation of iron acquisition genes will extend our knowledge of the complex regulatory changes during the infection process and might identify new potential drug targets. Thus, there is a need for efficient modelling approaches predicting key regulatory events of iron acquisition genes during the infection process.This study deals with the regulation of C. albicans iron uptake genes during adhesion to and invasion into human oral epithelial cells. A reverse engineering strategy is presented, which is able to infer regulatory networks on the basis of gene expression data, making use of relevant selection criteria such as sparseness and robustness. An exhaustive use of available knowledge from different data sources improved the network prediction. The predicted regulatory network proposes a number of new target genes for the transcriptional regulators Rim101, Hap3, Sef1 and Tup1. Furthermore, the molecular mode of action for Tup1 is clarified. Finally, regulatory interactions between the transcription factors themselves are proposed. This study presents a model describing how C. albicans may regulate iron acquisition during contact with and invasion of human oral epithelial cells. There is evidence that some of the proposed regulatory interactions might also occur during oral infection.This study focuses on a typical problem in Systems Biology where an interesting biological phenomenon is studied using a small number of available experimental data points. To overcome this limitation, a special modelling strategy was used which identifies sparse and robust networks. The data is augmented by an exhaustive search for additional data sources, helping to make proposals on regulatory interactions and to guide the modelling approach. The proposed modelling strategy is capable of finding known regulatory interactions and predicts a number of yet unknown biologically relevant regulatory interactions." @default.
• W2114372600 created "2016-06-24" @default.
• W2114372600 creator A5000809255 @default.
• W2114372600 creator A5011368040 @default.
• W2114372600 creator A5019017859 @default.
• W2114372600 creator A5030839081 @default.
• W2114372600 date "2010-11-04" @default.
• W2114372600 modified "2023-09-27" @default.
• W2114372600 title "Regulatory network modelling of iron acquisition by a fungal pathogen in contact with epithelial cells" @default.
• W2114372600 cites W1541663010 @default.
• W2114372600 cites W1546952499 @default.
• W2114372600 cites W1596515083 @default.
• W2114372600 cites W1849807599 @default.
• W2114372600 cites W1963522244 @default.
• W2114372600 cites W1965201359 @default.
• W2114372600 cites W1966022765 @default.
• W2114372600 cites W1968519358 @default.
• W2114372600 cites W1976261248 @default.
• W2114372600 cites W1979833590 @default.
• W2114372600 cites W1982612096 @default.
• W2114372600 cites W1983730914 @default.
• W2114372600 cites W1986956276 @default.
• W2114372600 cites W1994113926 @default.
• W2114372600 cites W2006641684 @default.
• W2114372600 cites W2007345698 @default.
• W2114372600 cites W2012050459 @default.
• W2114372600 cites W2017189230 @default.
• W2114372600 cites W2025269616 @default.
• W2114372600 cites W2025803032 @default.
• W2114372600 cites W2029946148 @default.
• W2114372600 cites W2031000707 @default.
• W2114372600 cites W2041611856 @default.
• W2114372600 cites W2044525257 @default.
• W2114372600 cites W2047625457 @default.
• W2114372600 cites W2063616227 @default.
• W2114372600 cites W2073461422 @default.
• W2114372600 cites W2074775779 @default.
• W2114372600 cites W2081098333 @default.
• W2114372600 cites W2088645589 @default.
• W2114372600 cites W2100169396 @default.
• W2114372600 cites W2103017472 @default.
• W2114372600 cites W2103890028 @default.
• W2114372600 cites W2105190386 @default.
• W2114372600 cites W2108556965 @default.
• W2114372600 cites W2110062742 @default.
• W2114372600 cites W2111728249 @default.
• W2114372600 cites W2113654344 @default.
• W2114372600 cites W2114382052 @default.
• W2114372600 cites W2114565252 @default.
• W2114372600 cites W2116142653 @default.
• W2114372600 cites W2120024428 @default.
• W2114372600 cites W2121738871 @default.
• W2114372600 cites W2126602684 @default.
• W2114372600 cites W2127851875 @default.
• W2114372600 cites W2138867568 @default.
• W2114372600 cites W2142415307 @default.
• W2114372600 cites W2142847871 @default.
• W2114372600 cites W2143226173 @default.
• W2114372600 cites W2145646735 @default.
• W2114372600 cites W2149669479 @default.
• W2114372600 cites W2150543962 @default.
• W2114372600 cites W2152663489 @default.
• W2114372600 cites W2153208554 @default.
• W2114372600 cites W2158005927 @default.
• W2114372600 cites W2158345992 @default.
• W2114372600 cites W2160042020 @default.
• W2114372600 cites W2161755882 @default.
• W2114372600 cites W2166106382 @default.
• W2114372600 cites W2169993696 @default.
• W2114372600 cites W2611370172 @default.
• W2114372600 cites W3099289621 @default.
• W2114372600 doi "https://doi.org/10.1186/1752-0509-4-148" @default.
• W2114372600 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/3225834" @default.
• W2114372600 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/21050438" @default.
• W2114372600 hasPublicationYear "2010" @default.
• W2114372600 type Work @default.
• W2114372600 sameAs 2114372600 @default.
• W2114372600 citedByCount "37" @default.
• W2114372600 countsByYear W21143726002012 @default.
• W2114372600 countsByYear W21143726002013 @default.
• W2114372600 countsByYear W21143726002014 @default.
• W2114372600 countsByYear W21143726002015 @default.
• W2114372600 countsByYear W21143726002016 @default.
• W2114372600 countsByYear W21143726002017 @default.
• W2114372600 countsByYear W21143726002018 @default.
• W2114372600 countsByYear W21143726002019 @default.
• W2114372600 countsByYear W21143726002020 @default.
• W2114372600 crossrefType "journal-article" @default.
• W2114372600 hasAuthorship W2114372600A5000809255 @default.
• W2114372600 hasAuthorship W2114372600A5011368040 @default.
• W2114372600 hasAuthorship W2114372600A5019017859 @default.
• W2114372600 hasAuthorship W2114372600A5030839081 @default.
• W2114372600 hasBestOaLocation W21143726001 @default.
• W2114372600 hasConcept C104317684 @default.
• W2114372600 hasConcept C145081991 @default.
• W2114372600 hasConcept C150194340 @default.
• W2114372600 hasConcept C152662350 @default.
• W2114372600 hasConcept C165864922 @default.
• W2114372600 hasConcept C2780917455 @default.
• W2114372600 hasConcept C33498276 @default.

• next