It cannot meet the trend of rapid increase in protein sequences. 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 ...
DNA-binding protein is a special kind of protein. It can interact with DNA, play an important role in various gene-related life activities, and is closely related to many diseases. Therefore, it is of great significance to study the identification methods of DNA-binding proteins. However, trad...
Major advance in protein-structure prediction The field of protein-structure prediction has advanced rapidly since the advent of DeepMind's AlphaFold, which can predict protein structure from sequence. These tools have led to an increase in structural data available to scientists and researchers for an...
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...
Examples include classification of seed storage proteins by Osborne fractionation [13], prediction of DNA and RNA binding sites [14], and identification of amyloid protein [15]. While MLP enables modeling complex, non-linear phenomena, the architecture struggles to handle the spatial arrangements of...
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 ...
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...
近日,湖南大学国家超算长沙中心副主任、信息科学与工程学院彭绍亮教授课题组在国际顶级期刊Nature Communications发表了题为“Improving prediction performance of general protein language model by domain-adaptive pretraining on DNA-binding prot...
2月12日,生物学领域重要期刊Briefings in Bioinformatics在线发表了我校人工智能学院计智伟教授课题组题为“ULDNA: Integrating Unsupervised Multi-Source Language Models with LSTM-Attention Network for High-Accuracy Protein-DNA Binding Sit...
wedetailthemeta-analysisofproteinDNA-bindingsites.Wealsoproposespecificimplicationsthatarelikelytoresultinnovelpredictionmethods,increasedperformance,orpracticalapplications.Keywords:DNA-bindingsite;prediction;machinelearningmethod;bioinformaticsOPENACCESSInt.J.Mol.Sci.2015,1651951.IntroductionProtein–DNAinteractionsare...