Chromatographic_Retention_Time_Prediction_Models_TALANTA_Data
This paper compares the relative predictive ability and applicability to NTA workflows of three RT prediction models: (1) a logP (octanol-water partition coefficient)-based model using EPI SuiteTM logP predictions; (2) a commercially available ACD/ChromGenius model; and, (3) a newly developed Quantitative Structure Retention Relationship model called OPERA-RT.
This dataset is associated with the following publication:
McEachran, A., K. Mansouri, S. Newton, B. Beverly, J. Sobus, and A. Williams. (TALANTA) A comparison of three liquid chromatography (LC) retention time prediction models. TALANTA. Elsevier Science Ltd, New York, NY, USA, 182: 371-379, (2018).
Complete Metadata
| accessLevel | public |
|---|---|
| bureauCode |
[
"020:00"
]
|
| contactPoint |
{
"fn": "Antony Williams",
"hasEmail": "mailto:williams.antony@epa.gov"
}
|
| description | This paper compares the relative predictive ability and applicability to NTA workflows of three RT prediction models: (1) a logP (octanol-water partition coefficient)-based model using EPI SuiteTM logP predictions; (2) a commercially available ACD/ChromGenius model; and, (3) a newly developed Quantitative Structure Retention Relationship model called OPERA-RT. This dataset is associated with the following publication: McEachran, A., K. Mansouri, S. Newton, B. Beverly, J. Sobus, and A. Williams. (TALANTA) A comparison of three liquid chromatography (LC) retention time prediction models. TALANTA. Elsevier Science Ltd, New York, NY, USA, 182: 371-379, (2018). |
| distribution |
[
{
"title": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/McEachran_A/RT_Prediction_2018/",
"accessURL": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/McEachran_A/RT_Prediction_2018/"
}
]
|
| identifier | https://doi.org/10.23719/1407009 |
| keyword |
[
"Chemistry Dashboard",
"DSSTox",
"Quantitative Structure-Retention Relationship (QSRR)",
"dashboards",
"high-performance liquid chromatography (HPLC)",
"non-targeted analysis (NTA)",
"retention time(RT)"
]
|
| license | https://pasteur.epa.gov/license/sciencehub-license.html |
| modified | 2017-10-03 |
| programCode |
[
"020:095"
]
|
| publisher |
{
"name": "U.S. EPA Office of Research and Development (ORD)",
"subOrganizationOf": {
"name": "U.S. Environmental Protection Agency",
"subOrganizationOf": {
"name": "U.S. Government"
}
}
}
|
| references |
[
"https://doi.org/10.1016/j.talanta.2018.01.022"
]
|
| rights |
null
|
| title | Chromatographic_Retention_Time_Prediction_Models_TALANTA_Data |
