LncPTPred: predicting lncRNA-protein interaction based on crosslinking and immunoprecipitation (CLIP-Seq) data.

ABSTRACT: Long noncoding RNA (lncRNA)-protein Interaction (LPI) across diverse biological systems, directly and indirectly, regulates various cellular processes. Experimental assays to recognize the protein binding partners of lncRNAs are highly time-consuming and expensive. In silico predictive approaches involving pattern recognition techniques provide a promising alternative to it by reducing the search space. Our work identifies such hidden patterns within the cross-linking immunoprecipitation sequencing (CLIP-Seq) data, which aid in overcoming the problem of obtaining a real negative dataset and thus offer a state-of-the-art machine learning (ML)-based prediction algorithm to predict LPI. The initial phase of this work involves preparing the training dataset, and the next phase is devoted towar

SUBMITTER: Das G 

PROVIDER: S-EPMC12368852 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature