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Home / Resources / Presentations / Dataset Curation, Assessment of their Quality, and Prediction Model Developments for Safe and Sustainable Nanotechnology (S2NANO) / About

Dataset Curation, Assessment of their Quality, and Prediction Model Developments for Safe and Sustainable Nanotechnology (S2NANO)

By Tae Hyun Yoon

Hanyang University South Korea

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Abstract

Nano WG November 29, 2018: Tae Hyun Yoon, Prof./CEO/Ph.D., Yoon Idea Lab. Co. Ltd. & Hanyang University

In this presentation, I will introduce our recent research outcomes from S2NANO: PredictNANO project, which aimed to bridge the nanosafety knowledge gaps between R&D activities and Industrial applications, via providing a datawarehouse for nanotoxicity prediction.  S2NANO:PredictNano is a Korean government funded project to develop nanosafety database, curated datasets, prediction models, and user-friendly interface.  As outcomes of S2NANO:PredictNano project, 13 classification models on metallic, carbonaceous, and oxide NPs were developed from 16 datasets curated from literatures, which are currently available in S2NANO portal (Safe & Sustainable Nanotechnology, www.s2nano.org) and recently published as peer-reviewed journal articles. 

J.S. Choi, T.X. Trinh, T. H. Yoon, J. Kim*, H. G. Byun* (2019) Quasi-QSAR for predicting the cell viability of human lung and skin cells exposed to different metal oxide nanomaterialsChemosphere, 217, 243-249

J.S. Choi, M.K. Ha, T.X. Trinh, T.H.Yoon, H.G.Byun* (2018) "Towards a generalized toxicity prediction model for oxide nanomaterials using integrated data from different sources" Scientific Reports, 8, 6110

M.K. Ha, T.X. Trinh, J.S. Choi, D. Maulina, H.G. Byun, T.H.Yoon*,(2018) “Toxicity Classification of Oxide Nanomaterials: Effects of Data Gap Filling and PChem Score-based Screening Approaches.”Scientific Reports, 8, 3141

T.X. Trinh, M.K. Ha, J.S. Choi, H.G. Byun, T.H. Yoon*(2018) “Dataset Curation, Assessment of their Quality and Completeness, and nanoSAR Classification Model Development for Metallic Nanoparticles”Environmental Science: Nano5, 1902-1910

T.X. Trinh, J.S. Choi, H. Jeon, H.G. Byun, T.H.Yoon*, J.Kim*,(2018) “Quasi-SMILES based Nano-QSAR model to predict the cytotoxicity of multi-walled carbon nanotubes to human lung cells.”Chemical Research in Toxicolology,31(3), 183

Sunil Kr Jha*, TH Yoon, Zhaoqing Pan(2018) “Multivariate statistical analysis for selecting optimal descriptors in the toxicity modeling of nanomaterials”, Computers in Biology and Medicine, 99, 161

D.W. Boukhvalov*, T.H.Yoon, (2017)  “Development of Theoretical Descriptors for Cytotoxicity Evaluation of Metallic Nanoparticles.”Chemical Research in Toxicolology, 30 (8), 1549

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Researchers should cite this work as follows:

  • Tae Hyun Yoon (2018), "Dataset Curation, Assessment of their Quality, and Prediction Model Developments for Safe and Sustainable Nanotechnology (S2NANO)," https://nciphub.org/resources/2174.

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