RNA-binding predictionProtein sequenceIdentification of RNA-binding proteins (RBPs) that bind to ribonucleic acid molecules is an important problem in Computational Biology and Bioinformatics. It becomes indispensable to identify RBPs as they play crucial roles in post-transcriptional control of RNAs and...
Kumar M, Gromiha MM, Raghava GP (2008) Prediction of RNA binding sites in a protein using SVM and PSSM profile. Proteins 71(1): 189-194.Manish Kumar, M Michael Gromiha, and G P S Raghava. Prediction of RNA binding sites in a protein using SVM and PSSM profile. Proteins, 71(1):...
Prediction of RNA-protein interactions using a nucleotide language model Motivation:The accumulation of sequencing data has enabled researchers to predict the interactions between RNA sequences and RNA-binding proteins (RBPs) us... K Yamada,M Hamada - 《Bioinformatics Advances》 被引量: 0发表: ...
SOFB is a comprehensive ensemble deep learning approach for elucidating and characterizing protein-nucleic-acid-binding residues Article Open access 03 June 2024 Amalgamation of 3D structure and sequence information for protein–protein interaction prediction Article Open access 05 November 2020 Introducti...
Bioinformatics RNA-protein interactions| Analysis of binding interfaces and prediction of protein binding sites in RNA PURDUE UNIVERSITY Michael R. GribskovDaisuke Kihara GuptaAditiRNA-protein interactions are vital to many biological processes such as translation and splicing. Analysis of the binding ...
Two novel RNA-binding proteins identification through computational prediction and experimental validation Author links open overlay panelJuan Xie a, Xiaoli Zhang a, Jinfang Zheng a, Xu Hong a, Xiaoxue Tong a, Xudong Liu a, Yaqiang Xue b, Xuelian Wang c, Yi Zhang c, Shiyong Liu aShow ...
259Altmetric Metrics Abstract Knowing the sequence specificities of DNA- and RNA-binding proteins is essential for developing models of the regulatory processes in biological systems and for identifying causal disease variants. Here we show that sequence specificities can be ascertained from experimental da...
Although the high success achieved by CNN-BiLSTM brings the model to the fore, MLPs that are rarely used in this regard also have success in various protein classifications. While MLPs have been used to solve problems such as amyloid prediction [12] or protein secondary structure prediction [13...
(HRP-) labeled goat anti rabbit IgG antibody (1:10,000) for 1 h. β-Actin (1:5000) was selected as an internal reference. Then use ECL luminescence kit to detect protein bands on the membrane, and plot and analyze the relative expression of each protein in ImageJ software v1.53c (...
Finally, the prediction step can be implemented using a deep learning algorithm that can make use of the extracted features to classify the protein. To sum up, the main contributions of this work can be summarized as follows: The rest of this article is organized as follows: The second ...