103
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Navigating Traditional Chinese Medicine Network Pharmacology and Computational Tools

      review-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The concept of “network target” has ushered in a new era in the field of traditional Chinese medicine (TCM). As a new research approach, network pharmacology is based on the analysis of network models and systems biology. Taking advantage of advancements in systems biology, a high degree of integration data analysis strategy and interpretable visualization provides deeper insights into the underlying mechanisms of TCM theories, including the principles of herb combination, biological foundations of herb or herbal formulae action, and molecular basis of TCM syndromes. In this study, we review several recent developments in TCM network pharmacology research and discuss their potential for bridging the gap between traditional and modern medicine. We briefly summarize the two main functional applications of TCM network models: understanding/uncovering and predicting/discovering. In particular, we focus on how TCM network pharmacology research is conducted and highlight different computational tools, such as network-based and machine learning algorithms, and sources that have been proposed and applied to the different steps involved in the research process. To make network pharmacology research commonplace, some basic network definitions and analysis methods are presented.

          Related collections

          Most cited references236

          • Record: found
          • Abstract: found
          • Article: not found

          Quantitative monitoring of gene expression patterns with a complementary DNA microarray.

          A high-capacity system was developed to monitor the expression of many genes in parallel. Microarrays prepared by high-speed robotic printing of complementary DNAs on glass were used for quantitative expression measurements of the corresponding genes. Because of the small format and high density of the arrays, hybridization volumes of 2 microliters could be used that enabled detection of rare transcripts in probe mixtures derived from 2 micrograms of total cellular messenger RNA. Differential expression measurements of 45 Arabidopsis genes were made by means of simultaneous, two-color fluorescence hybridization.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            DIP, the Database of Interacting Proteins: a research tool for studying cellular networks of protein interactions.

            I Xenarios (2002)
            The Database of Interacting Proteins (DIP: http://dip.doe-mbi.ucla.edu) is a database that documents experimentally determined protein-protein interactions. It provides the scientific community with an integrated set of tools for browsing and extracting information about protein interaction networks. As of September 2001, the DIP catalogs approximately 11 000 unique interactions among 5900 proteins from >80 organisms; the vast majority from yeast, Helicobacter pylori and human. Tools have been developed that allow users to analyze, visualize and integrate their own experimental data with the information about protein-protein interactions available in the DIP database.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Network-based prediction of protein function

              Functional annotation of proteins is a fundamental problem in the post-genomic era. The recent availability of protein interaction networks for many model species has spurred on the development of computational methods for interpreting such data in order to elucidate protein function. In this review, we describe the current computational approaches for the task, including direct methods, which propagate functional information through the network, and module-assisted methods, which infer functional modules within the network and use those for the annotation task. Although a broad variety of interesting approaches has been developed, further progress in the field will depend on systematic evaluation of the methods and their dissemination in the biological community.
                Bookmark

                Author and article information

                Journal
                Evid Based Complement Alternat Med
                Evid Based Complement Alternat Med
                ECAM
                Evidence-based Complementary and Alternative Medicine : eCAM
                Hindawi Publishing Corporation
                1741-427X
                1741-4288
                2013
                31 July 2013
                31 July 2013
                : 2013
                : 731969
                Affiliations
                1Longhua Hospital Affiliated to Shanghai University of TCM, Shanghai 200032, China
                2Institute of Digestive Disease, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200032, China
                Author notes

                Academic Editor: Ai-ping Lu

                Author information
                http://orcid.org/0000-0002-4445-1546
                http://orcid.org/0000-0003-0842-3676
                Article
                10.1155/2013/731969
                3747450
                23983798
                87b64cdb-2bf4-48ff-9188-e13b157525e6
                Copyright © 2013 Ming Yang et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 6 June 2013
                : 4 July 2013
                Funding
                Funded by: http://dx.doi.org/10.13039/501100001809 National Natural Science Foundation of China
                Award ID: 81273727
                Categories
                Review Article

                Complementary & Alternative medicine
                Complementary & Alternative medicine

                Comments

                Comment on this article