Registro completo de metadatos
| Campo DC | Valor | Lengua/Idioma |
|---|---|---|
| dc.creator | Perez, Luis Orlando | - |
| dc.creator | González José, Rolando | - |
| dc.creator | Peral Garcia, Pilar | - |
| dc.date | 2018-03-23T16:31:34Z | - |
| dc.date | 2018-03-23T16:31:34Z | - |
| dc.date | 2016-06 | - |
| dc.date | 2018-03-12T14:25:48Z | - |
| dc.date.accessioned | 2019-04-29T15:27:52Z | - |
| dc.date.available | 2019-04-29T15:27:52Z | - |
| dc.date.issued | 2018-03-23T16:31:34Z | - |
| dc.date.issued | 2018-03-23T16:31:34Z | - |
| dc.date.issued | 2016-06 | - |
| dc.date.issued | 2018-03-12T14:25:48Z | - |
| dc.identifier | Perez, Luis Orlando; González José, Rolando; Peral Garcia, Pilar; Prediction of non-genotoxic carcinogenicity based on genetic profiles of short term exposure assays; Korean Society of Toxicology; Toxicological Research; 32; 4; 6-2016; 289-300 | - |
| dc.identifier | 1976-8257 | - |
| dc.identifier | http://hdl.handle.net/11336/39786 | - |
| dc.identifier | 2234-2753 | - |
| dc.identifier | CONICET Digital | - |
| dc.identifier | CONICET | - |
| dc.identifier.uri | http://rodna.bn.gov.ar:8080/jspui/handle/bnmm/294626 | - |
| dc.description | Non-genotoxic carcinogens are substances that induce tumorigenesis by non-mutagenic mechanisms and long term rodent bioassays are required to identify them. Recent studies have shown that transcription profiling can be applied to develop early identifiers for long term phenotypes. In this study, we used rat liver expression profiles from the NTP (National Toxicology Program, Research Triangle Park, USA) DrugMatrix Database to construct a gene classifier that can distinguish between non-genotoxic carcinogens and other chemicals. The model was based on short term exposure assays (3 days) and the training was limited to oxidative stressors, peroxisome proliferators and hormone modulators. Validation of the predictor was performed on independent toxicogenomic data (TG-GATEs, Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System, Osaka, Japan). To build our model we performed Random Forests together with a recursive elimination algorithm (VarSelRF). Gene set enrichment analysis was employed for functional interpretation. A total of 770 microarrays comprising 96 different compounds were analyzed and a predictor of 54 genes was built. Prediction accuracy was 0.85 in the training set, 0.87 in the test set and increased with increasing concentration in the validation set: 0.6 at low dose, 0.7 at medium doses and 0.81 at high doses. Pathway analysis revealed gene prominence of cellular respiration, energy production and lipoprotein metabolism. The biggest target of toxicogenomics is accurately predict the toxicity of unknown drugs. In this analysis, we presented a classifier that can predict non-genotoxic carcinogenicity by using short term exposure assays. In this approach, dose level is critical when evaluating chemicals at early time points. | - |
| dc.description | Fil: Perez, Luis Orlando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto Patagónico para el Estudio de los Ecosistemas Continentales; Argentina | - |
| dc.description | Fil: González José, Rolando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto Patagónico para el Estudio de los Ecosistemas Continentales; Argentina | - |
| dc.description | Fil: Peral Garcia, Pilar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico CONICET- La Plata. Instituto de Genética Veterinaria ; Argentina | - |
| dc.format | application/pdf | - |
| dc.format | application/pdf | - |
| dc.format | application/pdf | - |
| dc.format | application/pdf | - |
| dc.language | eng | - |
| dc.publisher | Korean Society of Toxicology | - |
| dc.relation | info:eu-repo/semantics/altIdentifier/url/http://www.toxicolres.org/journal/view.html?doi=10.5487/TR.2016.32.4.289 | - |
| dc.relation | info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.5487/TR.2016.32.4.289 | - |
| dc.rights | info:eu-repo/semantics/openAccess | - |
| dc.rights | https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ | - |
| dc.source | reponame:CONICET Digital (CONICET) | - |
| dc.source | instname:Consejo Nacional de Investigaciones Científicas y Técnicas | - |
| dc.source | instacron:CONICET | - |
| dc.subject | toxicología | - |
| dc.subject | carcinogenicidad | - |
| dc.subject | perfiles genéticos | - |
| dc.subject | líneas celulares | - |
| dc.subject | toxicogenomics | - |
| dc.subject | non-genotoxic carcinogen | - |
| dc.subject | random forest | - |
| dc.subject | Otras Biotecnologías de la Salud | - |
| dc.subject | Biotecnología de la Salud | - |
| dc.subject | CIENCIAS MÉDICAS Y DE LA SALUD | - |
| dc.title | Prediction of non-genotoxic carcinogenicity based on genetic profiles of short term exposure assays | - |
| dc.type | info:eu-repo/semantics/article | - |
| dc.type | info:eu-repo/semantics/publishedVersion | - |
| dc.type | info:ar-repo/semantics/articulo | - |
| Aparece en las colecciones: | CONICET | |
Ficheros en este ítem:
No hay ficheros asociados a este ítem.