Prediction of Anti-Inflammatory Activity of a Series of Pyrimidine Derivatives, by Multiple Linear Regression and Artificial Neural Networks

IF 2.4 Q3 Computer Science

Journal of Theoretical & Computational Chemistry Pub Date : 2022-01-01 DOI:10.4236/cc.2022.104009

Yafigui Traoré, Jean Missa Ehouman, M. Koné, D. Diabaté, N. Ziao

引用次数: 0

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用多元线性回归和人工神经网络预测一系列嘧啶衍生物的抗炎活性

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Theoretical & Computational Chemistry 化学-化学综合

CiteScore

1.70

自引率

0.00%

发文量

审稿时长

3 months

期刊介绍： The Journal of Theoretical and Computational Chemistry (JTCC) is an international interdisciplinary journal aimed at providing comprehensive coverage on the latest developments and applications of research in the ever-expanding field of theoretical and computational chemistry. JTCC publishes regular articles and reviews on new methodology, software, web server and database developments. The applications of existing theoretical and computational methods which produce significant new insights into important problems are also welcomed. Papers reporting joint computational and experimental investigations are encouraged. The journal will not consider manuscripts reporting straightforward calculations of the properties of molecules with existing software packages without addressing a significant scientific problem. Areas covered by the journal include molecular dynamics, computer-aided molecular design, modeling effects of mutation on stability and dynamics of macromolecules, quantum mechanics, statistical mechanics and other related topics.