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Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) interactions play important roles in diagnostic biomarkers and therapeutic targets for various human diseases. However, experimental methods for finding miRNAs associated with a particular lncRNA are costly, time consuming, and only a few theoretical approaches play a role in predicting potential lncRNA–miRNA associations. In this study, we have established a novel matrix factorization model to predict lncRNA–miRNA interactions, namely lncRNA–miRNA interactions prediction by logistic matrix factorization with neighborhood regularized (LMFNRLMI). Meanwhile, it only utilizes known positive samples to mine potential associations in data that lack negative samples. As a result, this new model obtains reliable performance in the leave-one-out cross validation (the AUC of 0.9319) and 5-fold cross validation (the AUC of 0.9220), which has …