{"title":"HDAT: web-based high-throughput screening data analysis tools","authors":"Rong Liu, Taimur Hassan, R. Rallo, Y. Cohen","doi":"10.1088/1749-4699/6/1/014006","DOIUrl":null,"url":null,"abstract":"The increasing utilization of high-throughput screening (HTS) in toxicity studies of engineered nano-materials (ENMs) requires tools for rapid and reliable processing and analyses of large HTS datasets. In order to meet this need, a web-based platform for HTS data analyses tools (HDAT) was developed that provides statistical methods suitable for ENM toxicity data. As a publicly available computational nanoinformatics infrastructure, HDAT provides different plate normalization methods, various HTS summarization statistics, self-organizing map (SOM)-based clustering analysis, and visualization of raw and processed data using both heat map and SOM. HDAT has been successfully used in a number of HTS studies of ENM toxicity, thereby enabling analysis of toxicity mechanisms and development of structure?activity relationships for ENM toxicity. The online approach afforded by HDAT should encourage standardization of and future advances in HTS as well as facilitate convenient inter-laboratory comparisons of HTS datasets.","PeriodicalId":89345,"journal":{"name":"Computational science & discovery","volume":"6 1","pages":"014006"},"PeriodicalIF":0.0000,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1088/1749-4699/6/1/014006","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational science & discovery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1088/1749-4699/6/1/014006","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
The increasing utilization of high-throughput screening (HTS) in toxicity studies of engineered nano-materials (ENMs) requires tools for rapid and reliable processing and analyses of large HTS datasets. In order to meet this need, a web-based platform for HTS data analyses tools (HDAT) was developed that provides statistical methods suitable for ENM toxicity data. As a publicly available computational nanoinformatics infrastructure, HDAT provides different plate normalization methods, various HTS summarization statistics, self-organizing map (SOM)-based clustering analysis, and visualization of raw and processed data using both heat map and SOM. HDAT has been successfully used in a number of HTS studies of ENM toxicity, thereby enabling analysis of toxicity mechanisms and development of structure?activity relationships for ENM toxicity. The online approach afforded by HDAT should encourage standardization of and future advances in HTS as well as facilitate convenient inter-laboratory comparisons of HTS datasets.