DNA binding protein predictionpre-trained language modelsprotein sequence classificationdeep learningRNA-BINDINGFEATURESPSEAACDPPIdentifying proteins is crucial for disease diagnosis and treatment. With the increase of known proteins, large-scale batch predictions are essential. However, traditional biological ...
In this article, a tool for DNA-binding protein prediction based on Convolutional Neural Networks (CNN) and Bidirectional Long Short-Term Memory (BiLSTM) neural networks is proposed. It can not only extract features from the original sequence of a protein, but also extract related features from...
Named Stacking Ensemble Model for DNA-binding Protein Prediction, or StackDPP in short, our model achieved 0.92, 0.92 and 0.93 accuracy in 10-fold cross-validation, jackknife and independent testing respectively. Conclusion: StackDPP has performed very well in cross-validation ...
We introduced a novel approach for DNA-binding propensity prediction using relational machine learning which could potentially be used also for protein function prediction in general.Background The process of protein-DNA interaction has been an important subject of recent computational-biology research, ho...
evolutionary profilesfunctional annotationsPSSMsequence‐based predictionsSequence based DNA‐binding protein (DBP) prediction is a widely studied biological problem. Sliding windows on Position Specific Substitution Matrices (PSSMs) rows predict DNA‐binding residues well on known DBPs but the same models ...
Convolutional neural network architectures for predicting DNA–protein binding CNN用于基因组学研究的最大优势之一是,它可以探测某一motif(指蛋白质分子具有特定功能的或者作为一个独立结构域一部分相近的二级结构聚合体)是否在指定序列窗口内,这种探测能力非常有利于motif的鉴定,进而有助于结合位点的分类...
Protein-DNA Interactions PreetiPandey, ...ShandarAhmad, inEncyclopedia of Bioinformatics and Computational Biology, 2019 Prediction of DNA Binding Residues and DNA Binding Proteins The binding of DNA to the protein is very specific where DNA binds to a particular region of the protein usually termed...
- 《Protein & Peptide Letters》 被引量: 231发表: 2009年 Prediction of protein secondary structure content for the twilight zone sequences The method uses a multiple linear regression model and introduces a comprehensive feature-based sequence representation to predict amount of helices and strands.....
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 ...
Improving language model of human genome for DNA-protein binding prediction based on task-specific pre-training The DNA-protein binding plays a pivotal role in regulating gene expression and evolution, and computational identification of DNA-...