NPCMF: Nearest Profile-based Collaborative Matrix Factorization method for predicting miRNA-disease associations.

ABSTRACT:

Background

Predicting meaningful miRNA-disease associations (MDAs) is costly. Therefore, an increasing number of researchers are beginning to focus on methods to predict potential MDAs. Thus, prediction methods with improved accuracy are under development. An efficient computational method is proposed to be crucial for predicting novel MDAs. For improved experimental productivity, large biological datasets are used by researchers. Although there are many effective and feasible methods to predict potential MDAs, the possibility remains that these methods are flawed.

Results

A simple and effective method, known as Nearest Profile-based Collaborative Matrix Factorization (NPCMF), is proposed to identify novel MDAs. The nearest profile is introduced to our method to achieve the

SUBMITTER: Gao YL 

PROVIDER: S-EPMC6591872 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature