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MS2CNN: predicting MS/MS spectrum based on protein sequence using deep convolutional neural networks

机译：MS2CNN：使用深度卷积神经网络基于蛋白质序列预测MS / MS光谱

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摘要

Bar chart of MS CNN COS on charge 2+ (blue), 3+ (orange), and mix (gray) models. Blue and orange dashed lines indicate the peptide number of charge 2+ and 3+ data sets, respectively

机译：MS CNN COS充电2+（蓝色），3 +（橙色）和混合（灰色）模型的条形图。蓝色和橙色虚线分别表示电荷2+和3+数据集的肽数

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期刊名称 BMC Genomics
作者
Yang-Ming Lin; Ching-Tai Chen; Jia-Ming Chang;
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作者单位

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年(卷),期 2019(20),Suppl 9
年度 2019
页码 -1
总页数 10
原文格式 PDF
正文语种
中图分类遗传学;应用微生物学;
关键词
Peptide; Mass spectrum; Tandem mass spectrometry; Spectral library search; Protein identification; Machine learning; Deep learning; Deep convolutional neural networks;

机译：肽;质谱;串联质谱;谱库搜索;蛋白质鉴定;机器学习;深度学习;深度卷积神经网络;

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专利

1. MS2CNN: predicting MS/MS spectrum based on protein sequence using deep convolutional neural networks [J] . Yang-Ming Lin, Ching-Tai Chen, Jia-Ming Chang BMC Genomics . 2019,第S9期

机译：MS2CNN：使用深卷积神经网络预测基于蛋白质序列的MS / MS光谱
2. Enabling full‐length evolutionary profiles based deep convolutional neural network for predicting DNA‐binding proteins from sequence [J] . Chauhan Sucheta, Ahmad Shandar Proteins: Structure, Function, and Genetics . 2020,第1期

机译：从序列中启用基于深卷积神经网络的全长进化型材基于深度卷积神经网络，从而预测DNA结合蛋白
3. A Novel Prediction Method for ATP-Binding Sites From Protein Primary Sequences Based on Fusion of Deep Convolutional Neural Network and Ensemble Learning [J] . Song Jiazhi, Liang Yanchun, Liu Guixia, Quality Control, Transactions . 2020,第期

机译：基于深度卷积神经网络融合的蛋白质原发性序列的ATP结合位点新的预测方法。
4. MR-MS Image Classification based on Convolutional Neural Networks [C] . Dilek Göksel Duru, Adil Deniz Duru 2019 Scientific Meeting on Electrical-Electronics amp; Biomedical Engineering and Computer Science . 2019

机译：基于卷积神经网络的MR-MS图像分类
5. Deep Neural Language Model for Text Classification Based on Convolutional and Recurrent Neural Networks [D] . Hassan, Abdalraouf. 2018

机译：基于卷积神经网络和递归神经网络的深度神经语言文本分类模型
6. Predicting Protein-Protein Interactions from Matrix-Based Protein Sequence Using Convolution Neural Network and Feature-Selective Rotation Forest [O] . Lei Wang, Hai-Feng Wang, San-Rong Liu, -1

机译：使用卷积神经网络和特征选择旋转森林从基于基质的蛋白质序列预测蛋白质与蛋白质的相互作用
7. The First Implication of Image Processing Techniques on Influenza A Virus Sub-Typing Based on HA/NA Protein Sequences, using Convolutional Deep Neural Network [O] . Reza Ahsan, Mansour Ebrahimi 2018

机译：基于HA / NA蛋白序列的流感病毒亚键入的图像处理技术的第一次含义利用卷积深神经网络
8. Hydrophobicity Based Neural Network Method for Predicting Transmembrane Segments in Protein Sequences. [R] . Chen, Z., Liu, Q., Zhu, Y., 2001

机译：基于疏水性的神经网络预测蛋白质序列跨膜段。

MS2CNN: predicting MS/MS spectrum based on protein sequence using deep convolutional neural networks

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