Recent methods have shown the significance of secondary structure in understanding RNA-Protein interactions.;In this thesis, we explore prediction models for RNA-Protein interaction using two different schemes. The first applied string algorithms to extract the most effective string patterns from both ...
DeepBind [45] was one of the first methods which employed deep learning for the prediction of protein-binding from nucleotide sequences, demonstrating ground-break on bothin vitroandin vivoprotein-RNA interaction datasets. DeepBind makes use of a single 1D Convolutional layer, which consists of a ...
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 RNA-protein interaction prediction. Here, we introduce ...
sequence data with predicted structures (iv), and sequence data with randomly generated structures (v) (Fig.2e; Supplementary information, Fig.S3f, g). A recent study showed that predicted structures did not improve the prediction performance of protein–RNA binding if ...
Identification of hot-spot residues in protein-protein interactions by computational docking therein: the structural prediction of protein-protein binding mode, and the identification of the relevant residues for the interaction (so called 'hot-... S Grosdidier,J Fernández-Recio - 《Bmc Bioinformatics...
including gene ontology enrichment, KEGG pathway analysis, protein-protein interaction network analysis, transcription factor-gene interaction analysis, miRNA-gene interaction analysis, and drug prediction analysis. Our analyses provide new insights into the interpretation of RBP datasets and the treatment of...
iDEP also enables users to retrieve protein-protein interaction (PPI) networks among top DEGs via an API access to STRING [24]. These networks can be rendered both as static images and as richly annotated, interactive graphs on the STRING website. The API access also provides enrichment analysi...
were developed specifically for short motif prediction on protein binding microarray and (ht-)selex data. since these data normally contain a large number of short sequences (over 100,000 sequence in length of 20 bp ~ 60 bp), there is an advantage of using purified sufficient input ...
In binding site prediction, the 3D3D model is converted to a 3D2D model as a template (protein maintains 3D structure, RNA maintains 2D structure). If the base (residue of the protein) in the target RNA is aligned to the binding site of the template RNA (the binding site of the ...
Over the past decade, RNA sequencing (RNA-seq) has become an indispensable tool for transcriptome-wide analysis of differential gene expression and differential splicing of mRNAs. However, as next-generation sequencing technologies have developed, so too