例如:"lncRNA", "apoptosis", "WRKY"

Selection of reliable biomarkers from PCR array analyses using relative distance computational model: methodology and proof-of-concept study.

PLoS ONE. 2013 Dec 12;8(12):e83954. eCollection 2013
{{ author.authorName }}{{getOrganisationIndexOf(author)}} {{ author.authorName }}{{getOrganisationIndexOf(author)}}
{{ author.authorName }}{{getOrganisationIndexOf(author)}} {{ author.authorName }}{{getOrganisationIndexOf(author)}}
+ et al

[No authors listed]

Author information
  • {{index+1}} {{ organisation }}

摘要


It is increasingly evident about the difficulty to monitor chemical exposure through biomarkers as almost all the biomarkers so far proposed are not specific for any individual chemical. In this proof-of-concept study, adult male zebrafish (Danio rerio) were exposed to 5 or 25 µg/L 17β-estradiol (E2), 100 µg/L lindane, 5 nM 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) or 15 mg/L arsenic for 96 h, and the expression profiles of 59 genes involved in 7 pathways plus 2 well characterized biomarker genes, vtg1 (vitellogenin1) and cyp1a1 (cytochrome P450 1A1), were examined. Relative distance (RD) computational model was developed to screen favorable genes and generate appropriate gene sets for the differentiation of chemicals/concentrations selected. Our results demonstrated that the known biomarker genes were not always good candidates for the differentiation of pair of chemicals/concentrations, and other genes had higher potentials in some cases. Furthermore, the differentiation of 5 chemicals/concentrations examined were attainable using expression data of various gene sets, and the best combination was the set consisting of 50 genes; however, as few as two genes (e.g. vtg1 and hspa5 [heat shock protein 5]) were sufficient to differentiate the five chemical/concentration groups in the present test. These observations suggest that multi-parameter arrays should be more reliable for biomonitoring of chemical exposure than traditional biomarkers, and the RD computational model provides an effective tool for the selection of parameters and generation of parameter sets.

KEYWORDS: {{ getKeywords(articleDetailText.words) }}

基因功能


  • {{$index+1}}.{{ gene }}

图表


原始数据


 保存测序数据
Sample name
Organism Experiment title Sample type Library instrument Attributes
{{attr}}
{{ dataList.sampleTitle }}
{{ dataList.organism }} {{ dataList.expermentTitle }} {{ dataList.sampleType }} {{ dataList.libraryInstrument }} {{ showAttributeName(index,attr,dataList.attributes) }}

文献解读