Mathematical and Computational Modeling in Complex Biological Systems
The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and ma...
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doaj-37f4e0d48562458f882f94f1d01af1cb2020-11-24T21:47:40ZengHindawi LimitedBioMed Research International2314-61332314-61412017-01-01201710.1155/2017/59583215958321Mathematical and Computational Modeling in Complex Biological SystemsZhiwei Ji0Ke Yan1Wenyang Li2Haigen Hu3Xiaoliang Zhu4School of Information & Electronic Engineering, Zhejiang Gongshang University, 18 Xuezheng Road, Hangzhou 310018, ChinaCollege of Information Engineering, China Jiliang University, 258 Xueyuan Street, Hangzhou 310018, ChinaChongqing Key Laboratory of Oral Diseases and Biomedical Sciences and College of Stomatology, Chongqing Medical University, Chongqing 400016, ChinaInstitute of Computer Vision, College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, ChinaSchool of Information & Electronic Engineering, Zhejiang Gongshang University, 18 Xuezheng Road, Hangzhou 310018, ChinaThe biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology.http://dx.doi.org/10.1155/2017/5958321 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zhiwei Ji Ke Yan Wenyang Li Haigen Hu Xiaoliang Zhu |
spellingShingle |
Zhiwei Ji Ke Yan Wenyang Li Haigen Hu Xiaoliang Zhu Mathematical and Computational Modeling in Complex Biological Systems BioMed Research International |
author_facet |
Zhiwei Ji Ke Yan Wenyang Li Haigen Hu Xiaoliang Zhu |
author_sort |
Zhiwei Ji |
title |
Mathematical and Computational Modeling in Complex Biological Systems |
title_short |
Mathematical and Computational Modeling in Complex Biological Systems |
title_full |
Mathematical and Computational Modeling in Complex Biological Systems |
title_fullStr |
Mathematical and Computational Modeling in Complex Biological Systems |
title_full_unstemmed |
Mathematical and Computational Modeling in Complex Biological Systems |
title_sort |
mathematical and computational modeling in complex biological systems |
publisher |
Hindawi Limited |
series |
BioMed Research International |
issn |
2314-6133 2314-6141 |
publishDate |
2017-01-01 |
description |
The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology. |
url |
http://dx.doi.org/10.1155/2017/5958321 |
work_keys_str_mv |
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