/MDLD

This is a model for predicting lncRNAs associated with disease

Primary LanguagePython

MDLD

Introduction

This is code of MDLD (“Mask-Guided Target Node Feature Learning and Dynamic Detailed Feature Enhancement for LncRNA-Disease Association Prediction”).

Dataset

File_name Data_type Description Source
dis_sim_matrix_process.txt disease-disease The file contains the semantic similarities among 405 diseases. The value in i-th row and j-th column is the similarity between the i-th disease di and the j-th disease dj. MeSH
lnc_dis_association.txt lncRNA-disease The file includes the known 2687 associations between 240 lncRNAs and 405 diseases. The value in i-th row and j-th column is 1 when the i-th lncRNA li is associated with the j-th disease dj, otherwise it is 0. LncRNADisease
mi_dis.txt miRNA-disease The file includes the known 13,559 associations between 495 miRNAs and 405 diseases. The value in i-th row and j-th column is 1 when the i-th miRNA mi is associated with the j-th disease dj, otherwise it is 0. HMDD
lnc_mi.txt lncRNA-miRNA The file includes the known 1002 interactions between 240 lncRNAs and 495 miRNAs. The value in i-th row and j-th column is 1 when the i-th lncRNA li is associated with the j-th miRNA mj, otherwise it is 0. starBase
lnc_sim.txt lncRNA-lncRNA The file contains the semantic similarities among 240 lncRNAs. The value in i-th row and j-th column is the similarity between the i-th lncRNA li and the j-th lncRNA lj. Chen et al.$^{1}$
lncRNA_name.txt lncRNA It contains the names of 240 lncRNAs. LncRNADisease
disease_name.txt disease It contains the names of 405 diseases. LncRNADisease

(1) Chen, X., Clarence Yan, C., Luo, C. et al. Constructing lncRNA Functional Similarity Network Based on lncRNA-Disease Associations and Disease Semantic Similarity. Sci Rep 5, 11338 (2015).

File

-utils : data preprocessing,parameters et al.					
-data : Dataset used in the research						
-models : scripts for implementation of the model					
-main : scripts for model training and testing						

Environment

packages:
python == 3.9.0
torch == 1.13.0
numpy == 1.23.5
scikit-learn == 1.2.2
scipy == 1.10.1
pandas == 2.0.1
matplotlib == 3.7.1

Run

python ./main.py