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Zhao Q, Zhou X, Wu J, Cai J, Bao X, Tang L, Wang C, Liu C, Wang Y, Teng Y, Zheng M, Mu W, Zuo Z, Xie Y, Luo X, Ren J. BioTreasury: a community-based repository enabling indexing and rating of bioinformatics tools. SCIENCE CHINA. LIFE SCIENCES 2024; 67:221-229. [PMID: 38157107 DOI: 10.1007/s11427-023-2509-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Accepted: 12/12/2023] [Indexed: 01/03/2024]
Abstract
The exponential growth of bioinformatics tools in recent years has posed challenges for scientists in selecting the most suitable one for their data analysis assignments. Therefore, to aid scientists in making informed choices, a community-based platform that indexes and rates bioinformatics tools is urgently needed. In this study, we introduce BioTreasury ( http://biotreasury.rjmart.cn ), an integrated community-based repository that provides an interactive platform for users and developers to share their experiences in various bioinformatics tools. BioTreasury offers a comprehensive collection of well-indexed bioinformatics software, tools, and databases, totaling over 10,000 entries. In the past two years, we have continuously improved and maintained BioTreasury, adding several exciting features, including creating structured homepages for every tool and user, a hierarchical category of bioinformatics tools and classifying tools using large language model (LLM). BioTreasury streamlines the tool submission process with intelligent auto-completion. Additionally, BioTreasury provides a wide range of social features, for example, enabling users to participate in interactive discussions, rate tools, build and share tool collections for the public. We believe BioTreasury can be a valuable resource and knowledge-sharing platform for the biomedical community. It empowers researchers to effectively discover and evaluate bioinformatics tools, fostering collaboration and advancing bioinformatics research.
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Affiliation(s)
- Qi Zhao
- School of Life Sciences, State Key Laboratory of Oncology in South China, Cancer Center, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University, Guangzhou, 510060, China
| | - Xin Zhou
- School of Life Sciences, State Key Laboratory of Oncology in South China, Cancer Center, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University, Guangzhou, 510060, China
| | - Jingxing Wu
- School of Life Sciences, State Key Laboratory of Oncology in South China, Cancer Center, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University, Guangzhou, 510060, China
| | - Jieyi Cai
- School of Life Sciences, State Key Laboratory of Oncology in South China, Cancer Center, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University, Guangzhou, 510060, China
| | - Xiaoqiong Bao
- School of Life Sciences, State Key Laboratory of Oncology in South China, Cancer Center, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University, Guangzhou, 510060, China
| | - Lin Tang
- School of Life Sciences, State Key Laboratory of Oncology in South China, Cancer Center, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University, Guangzhou, 510060, China
| | - Chaoye Wang
- School of Life Sciences, State Key Laboratory of Oncology in South China, Cancer Center, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University, Guangzhou, 510060, China
| | - Chunlei Liu
- Institute of Precision Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yukai Wang
- School of Life Sciences, State Key Laboratory of Oncology in South China, Cancer Center, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University, Guangzhou, 510060, China
| | - Yuyan Teng
- School of Life Sciences, State Key Laboratory of Oncology in South China, Cancer Center, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University, Guangzhou, 510060, China
| | - Mohan Zheng
- School of Life Sciences, State Key Laboratory of Oncology in South China, Cancer Center, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University, Guangzhou, 510060, China
| | - Weiping Mu
- School of Life Sciences, State Key Laboratory of Oncology in South China, Cancer Center, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University, Guangzhou, 510060, China
| | - Zhixiang Zuo
- School of Life Sciences, State Key Laboratory of Oncology in South China, Cancer Center, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University, Guangzhou, 510060, China
| | - Yubin Xie
- Institute of Precision Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, China
| | - Xiaotong Luo
- Guangdong Institute of Gastroenterology, Department of General Surgery, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510275, China.
| | - Jian Ren
- School of Life Sciences, State Key Laboratory of Oncology in South China, Cancer Center, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University, Guangzhou, 510060, China.
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Noor A. Improving bioinformatics software quality through incorporation of software engineering practices. PeerJ Comput Sci 2022; 8:e839. [PMID: 35111923 PMCID: PMC8771759 DOI: 10.7717/peerj-cs.839] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 12/13/2021] [Indexed: 06/14/2023]
Abstract
BACKGROUND Bioinformatics software is developed for collecting, analyzing, integrating, and interpreting life science datasets that are often enormous. Bioinformatics engineers often lack the software engineering skills necessary for developing robust, maintainable, reusable software. This study presents review and discussion of the findings and efforts made to improve the quality of bioinformatics software. METHODOLOGY A systematic review was conducted of related literature that identifies core software engineering concepts for improving bioinformatics software development: requirements gathering, documentation, testing, and integration. The findings are presented with the aim of illuminating trends within the research that could lead to viable solutions to the struggles faced by bioinformatics engineers when developing scientific software. RESULTS The findings suggest that bioinformatics engineers could significantly benefit from the incorporation of software engineering principles into their development efforts. This leads to suggestion of both cultural changes within bioinformatics research communities as well as adoption of software engineering disciplines into the formal education of bioinformatics engineers. Open management of scientific bioinformatics development projects can result in improved software quality through collaboration amongst both bioinformatics engineers and software engineers. CONCLUSIONS While strides have been made both in identification and solution of issues of particular import to bioinformatics software development, there is still room for improvement in terms of shifts in both the formal education of bioinformatics engineers as well as the culture and approaches of managing scientific bioinformatics research and development efforts.
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