An ontology-based search engine for protein-protein interactions

被引:3
作者
Park, Byungkyu [1 ]
Han, Kyungsook [1 ]
机构
[1] Inha Univ, Sch Engn & Comp Sci, Inchon 402751, South Korea
来源
BMC BIOINFORMATICS | 2010年 / 11卷
基金
新加坡国家研究基金会;
关键词
INFORMATION; EXTRACTION; DATABASE;
D O I
10.1186/1471-2105-11-S1-S23
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Background: Keyword matching or ID matching is the most common searching method in a large database of protein-protein interactions. They are purely syntactic methods, and retrieve the records in the database that contain a keyword or ID specified in a query. Such syntactic search methods often retrieve too few search results or no results despite many potential matches present in the database. Results: We have developed a new method for representing protein-protein interactions and the Gene Ontology (GO) using modified Godel numbers. This representation is hidden from users but enables a search engine using the representation to efficiently search protein-protein interactions in a biologically meaningful way. Given a query protein with optional search conditions expressed in one or more GO terms, the search engine finds all the interaction partners of the query protein by unique prime factorization of the modified Godel numbers representing the query protein and the search conditions. Conclusion: Representing the biological relations of proteins and their GO annotations by modified Godel numbers makes a search engine efficiently find all protein-protein interactions by prime factorization of the numbers. Keyword matching or ID matching search methods often miss the interactions involving a protein that has no explicit annotations matching the search condition, but our search engine retrieves such interactions as well if they satisfy the search condition with a more specific term in the ontology.
引用
收藏
页数:10
相关论文
共 50 条
  • [41] InterPred: A pipeline to identify and model protein-protein interactions
    Mirabello, Claudio
    Wallner, Bjorn
    PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2017, 85 (06) : 1159 - 1170
  • [42] A computational framework for modeling functional protein-protein interactions
    Pal, Abantika
    Pal, Debnath
    Mitra, Pralay
    PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2021, 89 (10) : 1353 - 1364
  • [43] An atlas of protein-protein interactions across mouse tissues
    Skinnider, Michael A.
    Scott, Nichollas E.
    Prudova, Anna
    Kerr, Craig H.
    Stoynov, Nikolay
    Stacey, R. Greg
    Chan, Queenie W. T.
    Rattray, David
    Gsponer, Jorg
    Foster, Leonard J.
    CELL, 2021, 184 (15) : 4073 - +
  • [44] Modulators targeting protein-protein interactions in Mycobacterium tuberculosis
    Luo, Guofeng
    Ming, Tianqi
    Yang, Luchuan
    He, Lei
    Tao, Tao
    Wang, Yanmei
    MICROBIOLOGICAL RESEARCH, 2024, 284
  • [45] Structural biology and drug discovery for protein-protein interactions
    Jubb, Harry
    Higueruelo, Alicia P.
    Winter, Anja
    Blundell, Tom L.
    TRENDS IN PHARMACOLOGICAL SCIENCES, 2012, 33 (05) : 241 - 248
  • [46] Prediction of Protein-Protein Interactions by Evidence Combining Methods
    Chang, Ji-Wei
    Zhou, Yan-Qing
    Ul Qamar, Muhammad Tahir
    Chen, Ling-Ling
    Ding, Yu-Duan
    INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2016, 17 (11)
  • [47] PRIMOS: AN INTEGRATED PLATFORM FOR EXPLORING PROTEIN-PROTEIN INTERACTIONS
    Kern, Thomas
    Kommenda, Michael
    Dorfer, Viktoria
    Bauer, Johann W.
    Oender, Kamil
    EMSS 2009: 21ST EUROPEAN MODELING AND SIMULATION SYMPOSIUM, VOL II, 2009, : 199 - +
  • [48] Revealing protein-protein interactions at the transcriptome scale by sequencing
    Johnson, Kara L.
    Qi, Zhijie
    Yan, Zhangming
    Wen, Xingzhao
    Nguyen, Tri C.
    Zaleta-Rivera, Kathia
    Chen, Chien-Ju
    Fan, Xiaochen
    Sriram, Kiran
    Wan, Xueyi
    Chen, Zhen Bouman
    Zhong, Sheng
    MOLECULAR CELL, 2021, 81 (19) : 4091 - +
  • [49] Studying protein-protein interactions: progress, pitfalls and solutions
    Hayes, Sheri
    Malacrida, Beatrice
    Kiely, Maeve
    Kiely, Patrick A.
    BIOCHEMICAL SOCIETY TRANSACTIONS, 2016, 44 : 994 - 1004
  • [50] Sequence Representations and Their Utility for Predicting Protein-Protein Interactions
    Kimothi, Dhananjay
    Biyani, Pravesh
    Hogan, James M.
    Davis, Melissa J.
    IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 2023, 20 (01) : 646 - 657