| Chapter title |
Curating and Preparing High-Throughput Screening Data for Quantitative Structure-Activity Relationship Modeling
|
|---|---|
| Chapter number | 17 |
| Book title |
High-Throughput Screening Assays in Toxicology
|
| Published in |
Methods in molecular biology, January 2016
|
| DOI | 10.1007/978-1-4939-6346-1_17 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-6344-7, 978-1-4939-6346-1
|
| Authors |
Marlene T. Kim, Wenyi Wang, Alexander Sedykh, Hao Zhu, Kim, Marlene T., Wang, Wenyi, Sedykh, Alexander, Zhu, Hao |
| Abstract |
Publicly available bioassay data often contains errors. Curating massive bioassay data, especially high-throughput screening (HTS) data, for Quantitative Structure-Activity Relationship (QSAR) modeling requires the assistance of automated data curation tools. Using automated data curation tools are beneficial to users, especially ones without prior computer skills, because many platforms have been developed and optimized based on standardized requirements. As a result, the users do not need to extensively configure the curation tool prior to the application procedure. In this chapter, a freely available automatic tool to curate and prepare HTS data for QSAR modeling purposes will be described. |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 15 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 20% |
| Researcher | 3 | 20% |
| Student > Bachelor | 1 | 7% |
| Professor | 1 | 7% |
| Student > Doctoral Student | 1 | 7% |
| Other | 4 | 27% |
| Unknown | 2 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 4 | 27% |
| Computer Science | 4 | 27% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 13% |
| Arts and Humanities | 1 | 7% |
| Medicine and Dentistry | 1 | 7% |
| Other | 1 | 7% |
| Unknown | 2 | 13% |