Although a few lncRNAs have been well studied, the biological functions of the majority of lncRNAs remain enigmatic 9. lncRNAs have close linkages with posttranscriptional gene regulation by regulating biological processes including protein synthesis, RNA maturation and transportation, and transcriptional gene silencing 7, 8. In contrast to small noncoding RNAs (i.e., miRNAs), which are highly conserved and regulate transcriptional and posttranscriptional gene silencing 2, 3, long noncoding RNAs (lncRNAs), as one type of transcribed RNA molecules, are poorly conserved and control gene expression based on various mechanisms 4, 5, 6. Noncoding RNAs regulate the majority of biological processes associated with development, differentiation, and metabolism in organisms 1. The results show that the lncRNA FTX may interact with the protein P35637 and needs further validation. LPIDF obtains better average AUCs of 0.9012, 0.6937 and 0.9457, and the best average AUPRs of 0.9022, 0.6860, and 0.9382, respectively, for the three CVs, significantly outperforming other methods. We compare LPIDF with four classical association prediction models based on three fivefold cross validations on lncRNAs, proteins, and LPIs. Finally, a deep forest model with cascade forest structure is developed to find new LPIs. Second, features of lncRNAs and proteins are constructed based on four-nucleotide composition and BioSeq2vec with encoder-decoder structure, respectively. First, five LPI datasets are obtained and the corresponding sequence information of lncRNAs and proteins are collected. To solve with the above problems, in this study, we develop a Deep Forest-based LPI prediction method (LPIDF). In addition, the prediction performance remains limited. More importantly, part of models did not discover possible LPIs for new lncRNAs (or proteins). However, the majority of them were evaluated only on one LPI dataset, thereby resulting in prediction bias. Existing computational methods have been effectively applied to LPI prediction. The identification of lncRNA–protein Interactions (LPIs) is significantly important to well characterize the biological functions and mechanisms of lncRNAs. Long noncoding RNAs (lncRNAs) regulate many biological processes by interacting with corresponding RNA-binding proteins.

Ftx vector setup