TMMGdb - Tumor Metastasis Mechanism-associated Gene Database-Reference-Cited by-同舟云学术

TMMGdb - Tumor Metastasis Mechanism-associated Gene Database

Published:2023-01 Issue:1 Volume:18 Page:63-75
ISSN:1574-8936
Container-title:Current Bioinformatics
language:en
Short-container-title:CBIO

Author:

Ng Ka-Lok¹²³,Liu Hsueh-Chuan⁴,Mekala Venugopala Reddy⁵^ORCID,Huang Chien-Hung⁶

Affiliation:

1. Department of Bioinformatics and Medical Engineering, Asia University, Taichung, Taiwan

2. Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan

3. Center for Artificial Intelligence and Precision Medicine Research, Asia University, Huwei, Taiwan

4. Department of Biomedical Sciences and Engineering, National Central University, Taoyuan City, Taiwan

5. Department of Bioinformatics and Medical Engineering, Asia University, Taichung, Taiwan

6. Department of Computer Science and Information Engineering, National Formosa University, Huwei, Taiwan

Abstract

Background: At present, all or the majority of published databases report metastasis genes based on the concept of using cancer types or hallmarks of cancer/metastasis. Since tumor metastasis is a dynamic process involving many cellular and molecular processes, those databases cannot provide information on the sequential relations and cellular and molecular mechanisms among different metastasis stages. Objective: We incorporate the concept of tumor metastasis mechanism to construct a tumor metastasis mechanism-associated gene (TMMG) database based on using the metastasis mechanism concept. Methods: We utilized the text mining tool, BioBERT to mine the titles and abstracts of the papers and identify TMMGs. Results: This tumor metastasis mechanism-associated gene database (TMMGdb) contains a wealth of annotations.To check the reliability of TMMGdb, we compared the proportions of housekeeping genes (HKGs) in TMMGdb, HCMDB, and CMgene, the results showed that around 20% of the TMMGs are HKGs, and the proportions are highly consistent among the three databases. Compared with the HCMDB and CMgene databases, TMMGdb is able to find a more recent (on or after 2017) collection of publications and TMMGs. We provided six case studies to illustrate the uniqueness of the TMMGdb database. Conclusion: TMMGdb is a comprehensive resource for the biomedical community to understand the dynamic process, molecular features, and cellular processes involved in tumor metastasis. TMMGdb provides four interfaces; ‘Browse’, ‘Search’, ‘DEG Search’ and ‘Download’, for users to investigate the causal effects among different metastasis stages; the database is freely accessible at http://hmg.asia.edu.tw/ TMMGdb.

Funder

Taiwan Ministry of Science and Technology

Asia University

Publisher

Bentham Science Publishers Ltd.

Subject

Computational Mathematics,Genetics,Molecular Biology,Biochemistry

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