MicroRNA-disease association prediction by matrix tri-factorization
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RESEARCH
Open Access
MicroRNA-disease association prediction by matrix tri-factorization Huiran Li, Yin Guo, Menglan Cai and Limin Li* From The 18th Asia Pacific Bioinformatics Conference Seoul, Korea. 18-20 August 2020
Abstract Background: Biological evidence has shown that microRNAs(miRNAs) are greatly implicated in various biological progresses involved in human diseases. The identification of miRNA-disease associations(MDAs) is beneficial to disease diagnosis as well as treatment. Due to the high costs of biological experiments, it attracts more and more attention to predict MDAs by computational approaches. Results: In this work, we propose a novel model MTFMDA for miRNA-disease association prediction by matrix tri-factorization, based on the known miRNA-disease associations, two types of miRNA similarities, and two types of disease similarities. The main idea of MTFMDA is to factorize the miRNA-disease association matrix to three matrices, a feature matrix for miRNAs, a feature matrix for diseases, and a low-rank relationship matrix. Our model incorporates the Laplacian regularizers which force the feature matrices to preserve the similarities of miRNAs or diseases. A novel algorithm is proposed to solve the optimization problem. Conclusions: We evaluate our model by 5-fold cross validation by using known MDAs from HMDD V2.0 and show that our model could obtain the significantly highest AUCs among all the state-of-art methods. We further validate our method by applying it on colon and breast neoplasms in two different types of experiment settings. The new identified associated miRNAs for the two diseases could be verified by two other databases including dbDEMC and HMDD V3.0, which further shows the power of our proposed method. Keywords: micoRNA-disease association prediction, Matrix tri-factorization
Background MicroRNAs(miRNAs), a class of small, endogenous, noncoding RNAs including approximately 22 nucleotides, could regulate post-transcription of gene expression and RNA silencing by binding specific target messenger RNAs through base-pairing interactions [1, 2]. Since the first miRNA named lin-4 was found twenty years ago by Victor Ambros [3], with the development of technology, an increasing number of studies found that miRNAs play important roles in various stages of biological processes *Correspondence: [email protected] School of Mathematics and Statistics, Xi’an Jiaotong University, Xianning West 28, Xi’an, China
[3], such as cell development [4], proliferation [5] and viral infection [6]. Meanwhile, biological experiments indicate that miRNAs are involved in close relationships with the emergence and development processes of various human diseases [7]. For example, the study in [8] showed that a chromosomal translocation at 12q5 could influence the expression of let-7 and finally could cause the repress of the oncogene High Mobility Group A2(Hmga2). Another example is that mir-7 could influence epidermal growth factor receptor (EGFR) expression and protein kinase B activity in head and
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