A Web Repository System for Data Mining in Drug Discovery

Jiali Tang, Jack Wang, A. Hadaegh
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引用次数: 1

Abstract

This project is to produce a repository database system of drugs, drug features (properties), and drug targets where data can be mined and analyzed. Drug targets are different proteins that drugs try to bind to stop the activities of the protein. Users can utilize the database to mine useful data to predict the specific chemical properties that will have the relative efficacy of a specific target and the coefficient for each chemical property. This database system can be equipped with different data mining approaches/algorithms such as linear, non-linear, and classification types of data modelling. The data models have enhanced with the Genetic Evolution (GE) algorithms. This paper discusses implementation with the linear data models such as Multiple Linear Regression (MLR), Partial Least Square Regression (PLSR), and Support Vector Machine (SVM).
面向药物发现数据挖掘的Web存储库系统
本项目旨在建立一个药物、药物特征(属性)、药物靶点的资源库数据库系统,用于数据的挖掘和分析。药物靶标是药物试图结合以阻止蛋白质活动的不同蛋白质。用户可以利用数据库挖掘有用的数据来预测特定的化学性质,这些化学性质将具有特定目标的相对功效,以及每种化学性质的系数。该数据库系统可以配备不同的数据挖掘方法/算法,如线性,非线性和分类类型的数据建模。采用遗传进化(GE)算法对数据模型进行了增强。本文讨论了线性数据模型的实现,如多元线性回归(MLR),偏最小二乘回归(PLSR)和支持向量机(SVM)。
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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