For a given RNA sequence, the initial step involves the prediction of two-dimensional (2D) structures. Subsequently, these predicted 2D structures are used for the modeling of the corresponding 3D structures. The Chen group employed two distinct models for 2D structure prediction: Vfold2D61,62,...
RNA molecules fold into stable native structures to perform their biological function. RNA folding can be influenced by ions, co-factors, and proteins through numerous mechanisms. Understanding these mechanisms at the molecular level is important for elucidating the structure–function relationship in biol...
Method development for RBP binding-site prediction is an active area of research in the domain of computational RNA biology and an abundance of RBP binding-site prediction methods have been developed in recent years [8, 9, 10]. Development of new methods further accelerated with the advent of ...
Figure 1:A overview of E2Efold-3D. E2Efold-3D is a fully differentiable end-to-end approach to performde novoRNA 3D structure prediction using their sequence information. To initialize the sequence presentation of the query sequence and pair embeddings, the MSA of the query sequence will be pa...
RNA 3D structure prediction is a long-standing challenge. Inspired by the recent breakthrough in protein structure prediction, we developed trRosettaRNA, an automated deep learning-based approach to RNA 3D structure prediction. The trRosettaRNA pipeline
rna_secondary_structure_prediction.py- a wrapper for secondary structure prediction methods, e.g., cyclefold, mcfold,ipknot, RNAsubopt, contextfold, centroid_fold, with a use of restraints (if applicable) rna_dot2ct.py- convert dot notation to ct notation. ...
sRNA Target Prediction Organizing Tool (SPOT) integrates computational and experimental data to facilitate functional characterization of bacterial small RNAs. mSphere. 2019;4(1):10–1128. Tjaden B. TargetRNA3: a tool for predicting targets of small regulatory RNAs in prokaryotes 2023. Available from...
actually matter, we used power simulations as implemented in powsimR [49]. We simulated that 10% of genes sampled from the estimated mean-variance relation of each method are differentially expressed between two groups of samples. The fold changes of these genes were drawn from a distribution ...
RNA Secondary Structure Prediction using an Ensemble of Two-dimensional Deep Neural Networks and Transfer Learning. - genostack/SPOT-RNA
an accurate, fast and easy-to-use plant mirna prediction tool using small rna-seq data. bioinformatics. 2014; 30(19):2837–9. article cas google scholar wang w-c, lin f-m, chang w-c, lin k-y, huang h-d, lin n-s. mirexpress: analyzing high-throughput sequencing ...