186798

A Survey of Computational Toxicology Approaches

Article

Last updated: 03 Jan 2025

Subjects

-

Tags

Bioinformatics

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.

DOI

10.21608/kjis.2021.41013.1008

Keywords

Computational Toxicology, In Silico Modeling, Expert Systems, Machine-Learning Approaches

Authors

First Name

Amena

Last Name

Mahmoud

MiddleName

-

Affiliation

Computer Sciences, Faculty of Computers and Information, Kafr El Sheikh University

Email

amena_mahmoud@fci.kfs.edu.eg

City

Mansoura

Orcid

-

Volume

2

Article Issue

1

Related Issue

26932

Issue Date

2021-08-01

Receive Date

2020-08-29

Publish Date

2021-08-01

Page Start

1

Page End

7

Print ISSN

2537-0677

Online ISSN

2535-1478

Link

https://kjis.journals.ekb.eg/article_186798.html

Detail API

https://kjis.journals.ekb.eg/service?article_code=186798

Order

4

Type

Survey Article

Type Code

464

Publication Type

Journal

Publication Title

Kafrelsheikh Journal of Information Sciences

Publication Link

https://kjis.journals.ekb.eg/

MainTitle

A Survey of Computational Toxicology Approaches

Details

Type

Article

Created At

22 Jan 2023