Gene-based Collaborative Filtering using recommender system

Hu, Jinyu, Sharma, Sugam, Gao, Zhiwei and Chang, Victor (2018) Gene-based Collaborative Filtering using recommender system. Computers & Electrical Engineering, 65. pp. 332-341. ISSN 0045-7906

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The recommender system (RS) has achieved substantial evolution in this information age of the twenty-first century, with no exception to biological domain. While RS has been effectively exploited in analysis of biological data for gene prediction, it has raised interesting research challenges such as how to explore the gene interest (Gi) and recommend the genes for individual patients. To meet these research challenges, we propose a novel TOP-N Gene-based Collaborative Filtering (GeneCF) algorithm based on Gi of patients. The GeneCF algorithm is aimed for matching more accurate recommendations about genes to the patients, with exceptional precision and coverage achieved. The GeneCF algorithm has been tested and evaluated on a hepatocellular carcinoma (HCC) gene expression database. We found that six genes could be the cause of liver cancer: AMP, SAA1, S100P, SPP1 and CY2A7 and AFP. The GeneCF algorithm contributes to help doctors provide smarter, customized care for cancer patients.

Item Type: Article
Uncontrolled Keywords: Big Data, GeneCF, GPC, HCC, Recommender systems, Collaborative filtering
Subjects: G400 Computer Science
H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: Ay Okpokam
Date Deposited: 02 May 2017 14:42
Last Modified: 11 Oct 2019 21:16

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