Juwen Shen

Protein-protein interactions (PPIs) are central to most biological processes. Although efforts have been devoted to the development of methodology for predicting PPIs and protein interaction networks, the application of most existing methods is limited because they need information about protein homology or the interaction marks of the protein partners. In the present work, we propose a method for PPI prediction using only the information of protein sequences. This method was developed based on a learning algorithm-support vector machine combined with a kernel function and a conjoint triad feature for describing amino acids. More than 16,000 diverse PPI pairs were used to construct the universal model. The prediction ability of our approach is better than that of other sequence-based PPI prediction methods because it is able to predict PPI networks. Different types of PPI networks have been effectively mapped with our method, suggesting that, even with only sequence information, this method could be applied to the exploration of networks for any newly discovered protein with unknown biological relativity. In addition, such supplementary experimental information can enhance the prediction ability of the method.

ADVERTISEMENT RETURN TO ISSUEPREVReviewNEXTRecent Development of Sandwich Assay Based on the Nanobiotechnologies for Proteins, Nucleic Acids, Small Molecules, and IonsJuwen Shen||, Yuebin Li†§, Haoshuang Gu§, Fan Xia*†, and Xiaolei Zuo*‡View Author Information† Key Laboratory for Large-Format Battery Materials and System, Ministry of Education, School of Chemistry and Chemical Engineering, Huazhong University of Science and Technology (HUST), Wuhan 430074, China‡ Division of Physical Biology and Bioimaging Center, Shanghai Synchrotron Radiation Facility, Shanghai Institute of Applied Physics, Chinese Academy of Science, Shanghai 201800, China§ Hubei Collaborative Innovation Center for Advanced Organic Chemical Materials, Faculty of Physical and Electronic Sciences, Hubei University, Wuhan 430062, China|| Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China*E-mail: [email protected]*E-mail: [email protected]Cite this: Chem. Rev. 2014, 114, 15, 7631–7677Publication Date (Web):June 19, 2014Publication History Received18 June 2012Published online19 June 2014Published inissue 13 August 2014https://pubs.acs.org/doi/10.1021/cr300248xhttps://doi.org/10.1021/cr300248xreview-articleACS PublicationsCopyright © 2014 American Chemical SocietyRequest reuse permissionsArticle Views10757Altmetric-Citations225LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose SUBJECTS:Assays,Genetics,Metal nanoparticles,Peptides and proteins,Probes Get e-Alerts

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