AN ALGORITHM FOR DATA QUALITY ASSESSMENT IN PREDICTIVE TOXICOLOGY

Lack of the quality of the information that is integrated from heterogeneous sources is an important issue in many scientific domains. In toxicology the importance is even greater since the data is used for Quantitative Structure Activity Relationship (QSAR) modeling for prediction of chemical toxi...

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Main Authors: LADAN MALAZIZI, DANIEL NEAGU, QASIM CHAUDHRY
Format: Article
Language:English
Published: Gdańsk University of Technology 2007-01-01
Series:TASK Quarterly
Subjects:
Online Access:https://journal.mostwiedzy.pl/TASKQuarterly/article/view/2082
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author LADAN MALAZIZI
DANIEL NEAGU
QASIM CHAUDHRY
author_facet LADAN MALAZIZI
DANIEL NEAGU
QASIM CHAUDHRY
author_sort LADAN MALAZIZI
collection DOAJ
description Lack of the quality of the information that is integrated from heterogeneous sources is an important issue in many scientific domains. In toxicology the importance is even greater since the data is used for Quantitative Structure Activity Relationship (QSAR) modeling for prediction of chemical toxicity of new compounds. Much work has been done on QSARs but little attention has been paid to the quality of the data used. The underlying concept points to the absence of the quality criteria framework in this domain. This paper presents a review on some of the existing data quality assessment methods in various domains and their relevance and possible application to predictive toxicology, highlights number of data quality deficiencies from experimental work on internal data and also proposes some quality metrics and an algorithm for assessing data quality concluded from the results.
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spelling doaj.art-432a3a327b504fdeba7e764aa6c9bb142022-12-22T02:24:25ZengGdańsk University of TechnologyTASK Quarterly1428-63942007-01-01111-2AN ALGORITHM FOR DATA QUALITY ASSESSMENT IN PREDICTIVE TOXICOLOGYLADAN MALAZIZI0DANIEL NEAGU1QASIM CHAUDHRY2University of Bradford, Department of Computing, School of InformaticsUniversity of Bradford, Department of Computing, School of InformaticsCentral Science Laboratory Lack of the quality of the information that is integrated from heterogeneous sources is an important issue in many scientific domains. In toxicology the importance is even greater since the data is used for Quantitative Structure Activity Relationship (QSAR) modeling for prediction of chemical toxicity of new compounds. Much work has been done on QSARs but little attention has been paid to the quality of the data used. The underlying concept points to the absence of the quality criteria framework in this domain. This paper presents a review on some of the existing data quality assessment methods in various domains and their relevance and possible application to predictive toxicology, highlights number of data quality deficiencies from experimental work on internal data and also proposes some quality metrics and an algorithm for assessing data quality concluded from the results. https://journal.mostwiedzy.pl/TASKQuarterly/article/view/2082QSAR modelsdata qualitydata cleaning
spellingShingle LADAN MALAZIZI
DANIEL NEAGU
QASIM CHAUDHRY
AN ALGORITHM FOR DATA QUALITY ASSESSMENT IN PREDICTIVE TOXICOLOGY
TASK Quarterly
QSAR models
data quality
data cleaning
title AN ALGORITHM FOR DATA QUALITY ASSESSMENT IN PREDICTIVE TOXICOLOGY
title_full AN ALGORITHM FOR DATA QUALITY ASSESSMENT IN PREDICTIVE TOXICOLOGY
title_fullStr AN ALGORITHM FOR DATA QUALITY ASSESSMENT IN PREDICTIVE TOXICOLOGY
title_full_unstemmed AN ALGORITHM FOR DATA QUALITY ASSESSMENT IN PREDICTIVE TOXICOLOGY
title_short AN ALGORITHM FOR DATA QUALITY ASSESSMENT IN PREDICTIVE TOXICOLOGY
title_sort algorithm for data quality assessment in predictive toxicology
topic QSAR models
data quality
data cleaning
url https://journal.mostwiedzy.pl/TASKQuarterly/article/view/2082
work_keys_str_mv AT ladanmalazizi analgorithmfordataqualityassessmentinpredictivetoxicology
AT danielneagu analgorithmfordataqualityassessmentinpredictivetoxicology
AT qasimchaudhry analgorithmfordataqualityassessmentinpredictivetoxicology
AT ladanmalazizi algorithmfordataqualityassessmentinpredictivetoxicology
AT danielneagu algorithmfordataqualityassessmentinpredictivetoxicology
AT qasimchaudhry algorithmfordataqualityassessmentinpredictivetoxicology