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PyBioMed: a python library for various molecular representations of chemicals, proteins and DNAs and their interactions

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成果类型:
期刊论文
作者:
Dong, Jie;Yao, Zhi-Jiang;Zhang, Lin;Luo, Feijun;Lin, Qinlu;...
通讯作者:
Cao, Dong-Sheng
作者机构:
[Dong, Jie; Yao, Zhi-Jiang; Cao, Dong-Sheng] Cent S Univ, Xiangya Sch Pharmaceut Sci, 172 Tongzipo Rd, Changsha, Hunan, Peoples R China.
[Dong, Jie; Luo, Feijun; Zhang, Lin; Lin, Qinlu] Cent South Univ Forestry & Technol, Coll Food Sci & Engn, Natl Engn Lab Deep Proc Rice & Byprod, Changsha, Hunan, Peoples R China.
[Cao, Dong-Sheng; Lu, Ai-Ping] Hong Kong Baptist Univ, Sch Chinese Med, Inst Adv Translat Med Bone & Joint Dis, Hong Kong, Hong Kong, Peoples R China.
[Chen, Alex F.; Cao, Dong-Sheng] Cent S Univ, Xiangya Hosp 3, Ctr Vasc Dis & Translat Med, Changsha, Hunan, Peoples R China.
通讯机构:
[Cao, Dong-Sheng] C
[Cao, Dong-Sheng] H
Cent S Univ, Xiangya Sch Pharmaceut Sci, 172 Tongzipo Rd, Changsha, Hunan, Peoples R China.
Hong Kong Baptist Univ, Sch Chinese Med, Inst Adv Translat Med Bone & Joint Dis, Hong Kong, Hong Kong, Peoples R China.
Cent S Univ, Xiangya Hosp 3, Ctr Vasc Dis & Translat Med, Changsha, Hunan, Peoples R China.
语种:
英文
关键词:
Molecular representation;Molecular descriptors;Python library;Chemoinformatics;Data integration;Bioinformatics
期刊:
Journal of Cheminformatics
ISSN:
1758-2946
年:
2018
卷:
10
期:
1
页码:
1-11
基金类别:
JD, ZJY and DSC wrote the code; JD, ZJY and DSC released the package and manual; DSC, AFC and APL wrote and checked the manuscript. FJL, QLL and LZ helped in preparing figures and tables, testing and validating the results. FJL, QLL, AFC and APL helped in giving suggestions to improve the software package. All authors contributed into design of the study. All authors read and approved the final manuscript. The authors declare that they have no competing interests. Project name: PyBioMed. Project home page: Source code is available at http://projects.scbdd.com/pybiomed.html or https://github.com/gadsbyfly/PyBioMed. Operating system(s): Windows, Linux. Programming language: Python. License: BSD 3-Clause License. Any restrictions to use by non-academics: none. Not applicable. This work is financially supported by the National Natural Science Foundation of China (Grant No. 81402853and 81501619), grants from the Project of Innovation-driven Plan in Central South University, the Postdoctoral Science Foundation of Central South University, the Chinese Postdoctoral Science Foundation (2014T70794, 2014M562142) and the Key Laboratory of Special Medicine Food Process in Hunan Province (2017TP1021). The studies meet with the approval of the university’s review board. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This work is financially supported by the National Natural Science Founda‑ tion of China (Grant No. 81402853 and 81501619), grants from the Project of Innovation‑driven Plan in Central South University, the Postdoctoral Science Foundation of Central South University, the Chinese Postdoctoral Science Foundation (2014T70794, 2014M562142) and the Key Laboratory of Special Medicine Food Process in Hunan Province (2017TP1021). The studies meet with the approval of the university’s review board.
机构署名:
本校为其他机构
院系归属:
食品科学与工程学院
摘要:
Background: With the increasing development of biotechnology and informatics technology, publicly available data in chemistry and biology are undergoing explosive growth. Such wealthy information in these data needs to be extracted and transformed to useful knowledge by various data mining methods. Considering the amazing rate at which data are accumulated in chemistry and biology fields, new tools that process and interpret large and complex interaction data are increasingly important. So far, there are no suitable toolkits that can effectivel...

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