首页|Gannan Normal University Reports Findings in Machine Learning (A deep learning m odel for DNA enhancer prediction based on nucleotide position aware feature enco ding)
Gannan Normal University Reports Findings in Machine Learning (A deep learning m odel for DNA enhancer prediction based on nucleotide position aware feature enco ding)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting originating in Jiangxi, Peopl e's Republic of China, by NewsRx journalists, research stated, "Enhancers, genom ic DNA elements, regulate neighboring gene expression crucial for biological pro cesses like cell differentiation and stress response. However, current machine l earning methods for predicting DNA enhancers often underutilize hidden features in gene sequences, limiting model accuracy." The news reporters obtained a quote from the research from Gannan Normal Univers ity, "Hence, this article proposes the PDCNN model, a deep learning-based enhanc er prediction method. PDCNN extracts statistical nucleotide representations from gene sequences, discerning positional distribution information of nucleotides i n modifier-like DNA sequences. With a convolutional neural network structure, PD CNN employs dual convolutional and fully connected layers. The cross-entropy los s function iteratively updates using a gradient descent algorithm, enhancing pre diction accuracy. Model parameters are fine-tuned to select optimal combinations for training, achieving over 95% accuracy. Comparative analysis w ith traditional methods and existing models demonstrates PDCNN's robust feature extraction capability."
JiangxiPeople's Republic of ChinaAsi aCyborgsEmerging TechnologiesGeneticsMachine Learning
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