A Survey of Computational Toxicology Approaches | ||||
| Kafrelsheikh Journal of Information Sciences | ||||
| Article 4, Volume 2, Issue 1, August 2021, Page 1-7 PDF (187.57 K) | ||||
| Document Type: Survey Article | ||||
| DOI: 10.21608/kjis.2021.41013.1008 | ||||
 View on SCiNiTO | ||||
| Author | ||||
Amena Mahmoud 
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| Computer Sciences, Faculty of Computers and Information, Kafr El Sheikh University | ||||
| Abstract | ||||
| Medications are a particular kind of chemicals that are considered essential for toxicity screening in contrast to those substances that contribute to the environment. In the development and production phases, toxicity is still the reason for a great number of candidate failures for new medicines. In-vivo work on the pharmaceutical industry, the in-vitro and animal trends of incompetence for correctly forecasting certain human toxicity, and the lack of accurate, high-thrown in vitro testing was obstructive in calculating toxicity. the development of computational toxicology structures has been encouraged by developing numerous "omics" techniques that have grown into several scientific areas, including genomics, proteomics, metabolomics, and transcriptomics. Computational toxicology is highly interdisciplinary. Researchers in the field have backgrounds and training in toxicology, biochemistry, chemistry, environmental sciences, mathematics, statistics, medicine, engineering, biology, computer science, and many other disciplines. This paper offers a historical perspective and current status for the computational approaches used at the assessment of toxicity. It presents examples of the expert systems, machine-learning approaches and web-based toxicity predictors. | ||||
| Keywords | ||||
| Computational Toxicology; In Silico Modeling; Expert Systems; Machine-Learning Approaches | ||||
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