A Web Repository System for Data Mining in Drug Discovery

Jiali Tang, Jack Wang and Ahmad Reza Hadaegh, California State University San Marcos, USA

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).

KEYWORDS

Data Mining, Drug Discovery, Drug Description, Chemoinformatics, and Web Application

Original Source URL: https://aircconline.com/ijdkp/V10N1/10120ijdkp01.pdf

https://airccse.org/journal/ijdkp/vol10.html

Academia: https://www.academia.edu/128966411/Call_for_Papers_International_Journal_of_Data_Mining_and_Knowledge_Management_Process_IJDKP_H_Index_35

#Datamining #Drugdiscovery #Drugdescription #Chemoinformatics #Webapplication

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