RFLMDA: A Novel Reinforcement Learning-Based Computational Model for Human MicroRNA-Disease Association Prediction
Abstract
:1. Introduction
2. Materials and Methods
2.1. Human miRNA-Disease Associations
2.2. MiRNA Functional Similarity
2.3. Disease Semantic Similarity
2.4. Method Models
2.4.1. Collaborative Matrix Factorization
2.4.2. Neighborhood Regularized Logistic Matrix Factorization
2.4.3. Laplacian Regularized Least Squares
2.4.4. Reinforcement Learning
2.4.5. RFLMDA
Algorithm1: Pseudocode for RFLMDA algorithm. |
Require: Action space A, state space S, reward value R, sub-models CMF, NRLMF and LapRLS. Ensure: The predicted results of 1: Processing the dataset and training sub-models, namely CMF, NRLMF and LapRLS, respectively; 2: Calculation of the weights for models via Pseudocode for Q-learning algorithm, respectively; 3: Combining . |
Algorithm2: Pseudocode for Q-learning algorithm. |
|
3. Results
3.1. Evaluation Measurements
3.2. Comparison with Other Methods
4. Case Study
4.1. Colorectal Neoplasms
4.2. Breast Neoplasms
4.3. Lymphoma
5. Conclusions and Discussion
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Type of Data | Quantity |
---|---|
MiRNAs | 495 |
Diseases | 383 |
MiRNA-Disease association | 5430 |
Disease Name | Top-50 Prediction List |
---|---|
Colon Neoplasms | 47 |
Kidney Neoplasms | 46 |
Pancreatic Neoplasms | 49 |
Esophageal Neoplasms | 46 |
Breast Neoplasms | 50 |
Gastric Neoplasms | 41 |
Lymphoma | 48 |
Colorectal Neoplasms | 50 |
Disease | Rank | Name | Evidence | Rank | Name | Evidence |
---|---|---|---|---|---|---|
Colorectal Neoplasms | 1 | mir-21 | D | 11 | mir-7 | D |
2 | mir-145 | D | 12 | mir-218 | D | |
3 | mir-210 | D | 13 | mir-148a | D | |
4 | mir-182 | D | 14 | mir-27a | H | |
5 | mir-196a | D | 15 | mir-133a | D | |
6 | mir-126 | D | 16 | mir-143 | D | |
7 | mir-30a | D | 17 | mir-31 | D | |
8 | mir-34a | D | 18 | mir-200c | D | |
9 | mir-183 | D | 19 | mir-34b | D | |
10 | mir-146b | H | 20 | mir-7 | D |
Disease | Rank | Name | Evidence | Rank | Name | Evidence |
---|---|---|---|---|---|---|
Breast Neoplasms | 1 | let-7f | D | 11 | mir-10b | D |
2 | mir-30c | D | 12 | mir-19a | D | |
3 | mir-22 | D | 13 | mir-302b | D | |
4 | mir-17 | D | 14 | mir-200c | D | |
5 | mir-34c | H | 15 | let-7g | D | |
6 | mir-18a | D | 16 | mir-29a | D | |
7 | let-7a | D | 17 | mir-191 | D | |
8 | mir-20a | D | 18 | mir-125a | D | |
9 | mir-218 | D | 19 | mir-151a | H | |
10 | mir-34b | H | 20 | mir-200b | D |
Disease | Rank | Name | Evidence | Rank | Name | Evidence |
---|---|---|---|---|---|---|
Lymphoma | 1 | mir-17 | D | 11 | mir-146a | D |
2 | mir-20a | D | 12 | mir-34a | D | |
3 | mir-19b | D | 13 | mir-125b | D | |
4 | mir-92a | D | 14 | mir-126 | D | |
5 | mir-18a | D | 15 | mir-145 | D | |
6 | mir-21 | D | 16 | mir-181a | D | |
7 | mir-19a | D | 17 | mir-24 | D | |
8 | mir-155 | D | 18 | mir-29b | D | |
9 | mir-16 | D | 19 | mir-101 | D | |
10 | mir-15a | D | 20 | mir-150 | D |
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Cui, L.; Lu, Y.; Sun, J.; Fu, Q.; Xu, X.; Wu, H.; Chen, J. RFLMDA: A Novel Reinforcement Learning-Based Computational Model for Human MicroRNA-Disease Association Prediction. Biomolecules 2021, 11, 1835. https://doi.org/10.3390/biom11121835
Cui L, Lu Y, Sun J, Fu Q, Xu X, Wu H, Chen J. RFLMDA: A Novel Reinforcement Learning-Based Computational Model for Human MicroRNA-Disease Association Prediction. Biomolecules. 2021; 11(12):1835. https://doi.org/10.3390/biom11121835
Chicago/Turabian StyleCui, Linqian, You Lu, Jiacheng Sun, Qiming Fu, Xiao Xu, Hongjie Wu, and Jianping Chen. 2021. "RFLMDA: A Novel Reinforcement Learning-Based Computational Model for Human MicroRNA-Disease Association Prediction" Biomolecules 11, no. 12: 1835. https://doi.org/10.3390/biom11121835