Accurate computational determination of RNA-protein interactions remains challenging, particularly when encountering unknown RNAs and proteins. The limited number of RNAs and their flexibility constrained the effectiveness of the deep-learning models for
ZeRPI: A graph neural network model for zero-shot prediction of RNA-protein interactionsRNA-protein interactionGraph neural networksZero-shotRNA-protein interactions are crucial for biological functions across multiple levels. RNA binding proteins (RBPs) intricately engage in diverse biological processes ...
In this study, we evaluate 11in vivoprotein-RNA interaction prediction methods across 313 CLIP-seq datasets with respect to their classification performance on a large cohort of CLIP-seq datasets. Our benchmark revealed that no particular deep learning architecture, such as CNN or RNN, represents ...
This paper describes a web server called PRIdictor (Protein-RNA Interaction predictor), which predicts protein-binding sites in RNA as well as RNA-binding sites in protein with consideration of interaction partners of protein and RNA. Depending on the input data to PRIdictor, prediction of binding...
“1/0” labels to denote the binding and non-binding events in the training dataset, PrismNet apparently learned a quantitative model for RBP binding from the big data of sequence, structure, and protein–RNA interaction. Unexpectedly, cell type-specific binding sites (Fig.1d) generally had ...
ProteinInteractionDeep learningPredictionGraph attentionLong non-coding RNAs (lncRNAs) play a broad spectrum of distinctive regulatory roles through interactions with proteins. However, only a few plant lncRNAs have been experimentally characterized. We propose GPLPI, a graph representation learning method,...
few studies to date have focused on the “partner prediction problem”, i.e., identification of specific RNA interaction partner(s) for a known RNA binding protein, or protein binding partner(s) for non-coding RNAs (ncRNAs). Although large-scale experimental analyses of RPIs such as RNAcompe...
lncRNA-protein-interaction-prediction摘星**星梦 上传284.38 KB 文件格式 zip 该项目是关于 lncRNA-protein 交互预测的研究,旨在提出一种线性标签传播方法(LPLNP 方法)来预测未知的 lncRNA-protein 交互。该代码库包含我们的数据集以及单个 LPLNP、集成 LPLNP 模型和其他最新方法的代码。请遵循 Guideline.pdf 中的...
Finally, the future research directions of lncRNA protein interaction prediction are pointed out.doi:10.2174/0929866526666191025104043Lin ZhongZhong MingGuobo XieChunlong FanXue PiaoProtein and Peptide Letters
RPISeq – RNA-Protein Interaction PredictionRPISeq:: DESCRIPTIONRPISeq is a family of classifiers for predicting RNA-protein interactions using only sequence information. Advertisement::DEVELOPERRPISeq team:: SCREENSHOTSN/A:: REQUIREMENTSWeb Browser