IDEAS home Printed from https://ideas.repec.org/a/hin/complx/2498957.html
   My bibliography  Save this article

miRNA-Disease Association Prediction with Collaborative Matrix Factorization

Author

Listed:
  • Zhen Shen
  • You-Hua Zhang
  • Kyungsook Han
  • Asoke K. Nandi
  • Barry Honig
  • De-Shuang Huang

Abstract

As one of the factors in the noncoding RNA family, microRNAs (miRNAs) are involved in the development and progression of various complex diseases. Experimental identification of miRNA-disease association is expensive and time-consuming. Therefore, it is necessary to design efficient algorithms to identify novel miRNA-disease association. In this paper, we developed the computational method of Collaborative Matrix Factorization for miRNA-Disease Association prediction (CMFMDA) to identify potential miRNA-disease associations by integrating miRNA functional similarity, disease semantic similarity, and experimentally verified miRNA-disease associations. Experiments verified that CMFMDA achieves intended purpose and application values with its short consuming-time and high prediction accuracy. In addition, we used CMFMDA on Esophageal Neoplasms and Kidney Neoplasms to reveal their potential related miRNAs. As a result, 84% and 82% of top 50 predicted miRNA-disease pairs for these two diseases were confirmed by experiment. Not only this, but also CMFMDA could be applied to new diseases and new miRNAs without any known associations, which overcome the defects of many previous computational methods.

Suggested Citation

  • Zhen Shen & You-Hua Zhang & Kyungsook Han & Asoke K. Nandi & Barry Honig & De-Shuang Huang, 2017. "miRNA-Disease Association Prediction with Collaborative Matrix Factorization," Complexity, Hindawi, vol. 2017, pages 1-9, September.
  • Handle: RePEc:hin:complx:2498957
    DOI: 10.1155/2017/2498957
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2017/2498957.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/8503/2017/2498957.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2017/2498957?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Xing Chen & Ming-Xi Liu & Qing-Hua Cui & Gui-Ying Yan, 2012. "Prediction of Disease-Related Interactions between MicroRNAs and Environmental Factors Based on a Semi-Supervised Classifier," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-10, August.
    2. Lin Zhu & Zhu-Hong You & De-Shuang Huang & Bing Wang, 2013. "t-LSE: A Novel Robust Geometric Approach for Modeling Protein-Protein Interaction Networks," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-13, April.
    3. Yunpeng Liu & Daniel A Tennant & Zexuan Zhu & John K Heath & Xin Yao & Shan He, 2014. "DiME: A Scalable Disease Module Identification Algorithm with Application to Glioma Progression," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-17, February.
    4. Brenda J. Reinhart & Frank J. Slack & Michael Basson & Amy E. Pasquinelli & Jill C. Bettinger & Ann E. Rougvie & H. Robert Horvitz & Gary Ruvkun, 2000. "The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditis elegans," Nature, Nature, vol. 403(6772), pages 901-906, February.
    5. Gunter Meister & Thomas Tuschl, 2004. "Mechanisms of gene silencing by double-stranded RNA," Nature, Nature, vol. 431(7006), pages 343-349, September.
    6. Victor Ambros, 2004. "The functions of animal microRNAs," Nature, Nature, vol. 431(7006), pages 350-355, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xing Chen & Jun Yin & Jia Qu & Li Huang, 2018. "MDHGI: Matrix Decomposition and Heterogeneous Graph Inference for miRNA-disease association prediction," PLOS Computational Biology, Public Library of Science, vol. 14(8), pages 1-24, August.
    2. Xing Chen & Li Huang, 2017. "LRSSLMDA: Laplacian Regularized Sparse Subspace Learning for MiRNA-Disease Association prediction," PLOS Computational Biology, Public Library of Science, vol. 13(12), pages 1-28, December.
    3. Thuc Duy Le & Junpeng Zhang & Lin Liu & Jiuyong Li, 2015. "Ensemble Methods for MiRNA Target Prediction from Expression Data," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-19, June.
    4. José María Galván-Román & Ángel Lancho-Sánchez & Sergio Luquero-Bueno & Lorena Vega-Piris & Jose Curbelo & Marcos Manzaneque-Pradales & Manuel Gómez & Hortensia de la Fuente & Mara Ortega-Gómez & Javi, 2020. "Usefulness of circulating microRNAs miR-146a and miR-16-5p as prognostic biomarkers in community-acquired pneumonia," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-13, October.
    5. Kshitij Srivastava & Anvesha Srivastava, 2012. "Comprehensive Review of Genetic Association Studies and Meta-Analyses on miRNA Polymorphisms and Cancer Risk," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-1, November.
    6. Yanyan Wang & Yujie Zhang & Chi Pan & Feixia Ma & Suzhan Zhang, 2015. "Prediction of Poor Prognosis in Breast Cancer Patients Based on MicroRNA-21 Expression: A Meta-Analysis," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-13, February.
    7. Jun Meng & Lin Shi & Yushi Luan, 2014. "Plant microRNA-Target Interaction Identification Model Based on the Integration of Prediction Tools and Support Vector Machine," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-12, July.
    8. J. Fulneček, 2007. "Isolation and detection of small RNA molecules," Plant, Soil and Environment, Czech Academy of Agricultural Sciences, vol. 53(10), pages 451-455.
    9. Charlotte Glinge & Sebastian Clauss & Kim Boddum & Reza Jabbari & Javad Jabbari & Bjarke Risgaard & Philipp Tomsits & Bianca Hildebrand & Stefan Kääb & Reza Wakili & Thomas Jespersen & Jacob Tfelt-Han, 2017. "Stability of Circulating Blood-Based MicroRNAs – Pre-Analytic Methodological Considerations," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-16, February.
    10. Hossain Ahmed & Beyene Joseph, 2013. "Estimation of weighted log partial area under the ROC curve and its application to MicroRNA expression data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 12(6), pages 743-755, December.
    11. Emilie Estrabaud & Kevin Appourchaux & Ivan Bièche & Fabrice Carrat & Martine Lapalus & Olivier Lada & Michelle Martinot-Peignoux & Nathalie Boyer & Patrick Marcellin & Michel Vidaud & Tarik Asselah, 2015. "IFI35, mir-99a and HCV Genotype to Predict Sustained Virological Response to Pegylated-Interferon Plus Ribavirin in Chronic Hepatitis C," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-19, April.
    12. Hai Lian & Lei Wang & Jingmin Zhang, 2012. "Increased Risk of Breast Cancer Associated with CC Genotype of Has-miR-146a Rs2910164 Polymorphism in Europeans," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-7, February.
    13. Le Thi Truc Linh, 2018. "The Microrna 29 family and its regulation," HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE - ENGINEERING AND TECHNOLOGY, HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE, HO CHI MINH CITY OPEN UNIVERSITY, vol. 8(1), pages 18-27.
    14. Seyedehsadaf Asfa & Halil Ibrahim Toy & Reza Arshinchi Bonab & George P. Chrousos & Athanasia Pavlopoulou & Styliani A. Geronikolou, 2023. "Soft Tissue Ewing Sarcoma Cell Drug Resistance Revisited: A Systems Biology Approach," IJERPH, MDPI, vol. 20(13), pages 1-17, July.
    15. Li Li & Yunjian Sheng & Lin Lv & Jian Gao, 2013. "The Association between Two MicroRNA Variants (miR-499, miR-149) and Gastrointestinal Cancer Risk: A Meta-Analysis," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-1, November.
    16. Blanca Elena Castro-Magdonel & Manuela Orjuela & Diana E Alvarez-Suarez & Javier Camacho & Lourdes Cabrera-Muñoz & Stanislaw Sadowinski-Pine & Aurora Medina-Sanson & Citlali Lara-Molina & Daphne Garcí, 2020. "Circulating miRNome detection analysis reveals 537 miRNAS in plasma, 625 in extracellular vesicles and a discriminant plasma signature of 19 miRNAs in children with retinoblastoma from which 14 are al," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-19, April.
    17. Adam Emmer, 2019. "The careers behind and the impact of solo author articles in Nature and Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 825-840, August.
    18. Juan Roa & Miguel Ruiz-Cruz & Francisco Ruiz-Pino & Rocio Onieva & Maria J. Vazquez & Maria J. Sanchez-Tapia & Jose M. Ruiz-Rodriguez & Veronica Sobrino & Alexia Barroso & Violeta Heras & Inmaculada V, 2022. "Dicer ablation in Kiss1 neurons impairs puberty and fertility preferentially in female mice," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    19. Junpeng Zhang & Taosheng Xu & Lin Liu & Wu Zhang & Chunwen Zhao & Sijing Li & Jiuyong Li & Nini Rao & Thuc Duy Le, 2020. "LMSM: A modular approach for identifying lncRNA related miRNA sponge modules in breast cancer," PLOS Computational Biology, Public Library of Science, vol. 16(4), pages 1-22, April.
    20. Hisakazu Iwama & Kiyohito Kato & Hitomi Imachi & Koji Murao & Tsutomu Masaki, 2018. "Human microRNAs preferentially target genes with intermediate levels of expression and its formation by mammalian evolution," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-20, May.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:complx:2498957. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.