Degree-Based Similarity Indexes for Identifying Potential miRNA-Disease Associations
Identifying disease-associated miRNAs is helpful to explore the pathogenesis of diseases. However, without foreknowledge of the experimentally valid disease-associated miRNAs information, the development of promising and affordable approaches for effective treatment of human diseases is challenging....
Main Authors: | Yajie Meng, Min Jin, Xianfang Tang, Junlin Xu |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9133264/ |
Similar Items
-
LRMCMDA: Predicting miRNA-Disease Association by Integrating Low-Rank Matrix Completion With miRNA and Disease Similarity Information
by: Junlin Xu, et al.
Published: (2020-01-01) -
Modelling Self-Organization in Complex Networks Via a Brain-Inspired Network Automata Theory Improves Link Reliability in Protein Interactomes
by: Carlo Vittorio Cannistraci
Published: (2018-10-01) -
A relationship between the incremental values of area under the ROC curve and of area under the precision-recall curve
by: Qian M. Zhou, et al.
Published: (2021-07-01) -
Teknik Resampling untuk Mengatasi Ketidakseimbangan Kelas pada Klasifikasi Penyakit Diabetes Menggunakan C4.5, Random Forest, dan SVM
by: Wahyu Nugraha, et al.
Published: (2021-08-01) -
Quantification of thermal dose in moderate clinical hyperthermia with radiotherapy: a relook using temperature–time area under the curve (AUC)
by: Niloy R. Datta, et al.
Published: (2021-01-01)