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Intelligent Computing Theories and Application

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Cover of 'Intelligent Computing Theories and Application'

Table of Contents

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    Book Overview
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    Chapter 1 A Comparison Study of Predicting lncRNA-Protein Interactions via Representative Network Embedding Methods
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    Chapter 2 GATSDCD: Prediction of circRNA-Disease Associations Based on Singular Value Decomposition and Graph Attention Network
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    Chapter 3 Anti-breast Cancer Drug Design and ADMET Prediction of ERa Antagonists Based on QSAR Study
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    Chapter 4 Real-Time Optimal Scheduling of Large-Scale Electric Vehicles Based on Non-cooperative Game
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    Chapter 5 TBC-Unet: U-net with Three-Branch Convolution for Gliomas MRI Segmentation
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    Chapter 6 Drug–Target Interaction Prediction Based on Graph Neural Network and Recommendation System
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    Chapter 7 NSAP: A Neighborhood Subgraph Aggregation Method for Drug-Disease Association Prediction
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    Chapter 8 Comprehensive Evaluation of BERT Model for DNA-Language for Prediction of DNA Sequence Binding Specificities in Fine-Tuning Phase
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    Chapter 9 Identification and Evaluation of Key Biomarkers of Acute Myocardial Infarction by Machine Learning
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    Chapter 10 Glioblastoma Subtyping by Immuogenomics
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    Chapter 11 Functional Analysis of Molecular Subtypes with Deep Similarity Learning Model Based on Multi-omics Data
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    Chapter 12 Predicting Drug-Disease Associations by Self-topological Generalized Matrix Factorization with Neighborhood Constraints
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    Chapter 13 iEnhancer-BERT: A Novel Transfer Learning Architecture Based on DNA-Language Model for Identifying Enhancers and Their Strength
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    Chapter 14 GCNMFCDA: A Method Based on Graph Convolutional Network and Matrix Factorization for Predicting circRNA-Disease Associations
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    Chapter 15 Prediction of MiRNA-Disease Association Based on Higher-Order Graph Convolutional Networks
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    Chapter 16 SCDF: A Novel Single-Cell Classification Method Based on Dimension-Reduced Data Fusion
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    Chapter 17 Research on the Potential Mechanism of Rhizoma Drynariae in the Treatment of Periodontitis Based on Network Pharmacology
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    Chapter 18 Predicting Drug-Disease Associations via Meta-path Representation Learning based on Heterogeneous Information Net works
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    Chapter 19 An Enhanced Graph Neural Network Based on the Tissue-Like P System
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    Chapter 20 Cell Classification Based on Stacked Autoencoder for Single-Cell RNA Sequencing
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    Chapter 21 A Novel Cuprotosis-Related Gene Signature Predicts Survival Outcomes in Patients with Clear-Cell Renal Cell Carcinoma
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    Chapter 22 Identification of miRNA-lncRNA Underlying Interactions Through Representation for Multiplex Heterogeneous Network
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    Chapter 23 ACNN: Drug-Drug Interaction Prediction Through CNN and Attention Mechanism
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    Chapter 24 Elucidating Quantum Semi-empirical Based QSAR, for Predicting Tannins’ Anti-oxidant Activity with the Help of Artificial Neural Network
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    Chapter 25 Drug-Target Interaction Prediction Based on Transformer
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    Chapter 26 Protein-Ligand Binding Affinity Prediction Based on Deep Learning
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    Chapter 27 Position-Defined CpG Islands Provide Complete Co-methylation Indexing for Human Genes
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    Chapter 28 Predicting the Subcellular Localization of Multi-site Protein Based on Fusion Feature and Multi-label Deep Forest Model
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    Chapter 29 Construction of Gene Network Based on Inter-tumor Heterogeneity for Tumor Type Identification
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    Chapter 30 A Novel Synthetic Lethality Prediction Method Based on Bidirectional Attention Learning
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    Chapter 31 A Novel Trajectory Inference Method on Single-Cell Gene Expression Data
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    Chapter 32 Bioinformatic Analysis of Clear Cell Renal Carcinoma via ATAC-Seq and RNA-Seq
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    Chapter 33 The Prognosis Model of Clear Cell Renal Cell Carcinoma Based on Allograft Rejection Markers
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    Chapter 34 Membrane Protein Amphiphilic Helix Structure Prediction Based on Graph Convolution Network
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    Chapter 35 The CNV Predict Model in Esophagus Cancer
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    Chapter 36 TB-LNPs: A Web Server for Access to Lung Nodule Prediction Models
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    Chapter 37 A Targeted Drug Design Method Based on GRU and TopP Sampling Strategies
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    Chapter 38 KGAT: Predicting Drug-Target Interaction Based on Knowledge Graph Attention Network
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    Chapter 39 MRLDTI: A Meta-path-Based Representation Learning Model for Drug-Target Interaction Prediction
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    Chapter 40 Single Image Dehazing Based on Generative Adversarial Networks
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    Chapter 41 K-Nearest Neighbor Based Local Distribution Alignment
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    Chapter 42 A Video Anomaly Detection Method Based on Sequence Recognition
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    Chapter 43 Drug-Target Binding Affinity Prediction Based on Graph Neural Networks and Word2vec
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    Chapter 44 Drug-Target Interaction Prediction Based on Attentive FP and Word2vec
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    Chapter 45 Unsupervised Prediction Method for Drug-Target Interactions Based on Structural Similarity
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    Chapter 46 Drug-Target Affinity Prediction Based on Multi-channel Graph Convolution
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    Chapter 47 An Optimization Method for Drug-Target Interaction Prediction Based on RandSAS Strategy
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    Chapter 48 A Novel Cuprotosis-Related lncRNA Signature Predicts Survival Outcomes in Patients with Glioblastoma
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    Chapter 49 Arbitrary Voice Conversion via Adversarial Learning and Cycle Consistency Loss
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    Chapter 50 MGVC: A Mask Voice Conversion Using Generating Adversarial Training
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    Chapter 51 Covid-19 Detection by Wavelet Entropy and Genetic Algorithm
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    Chapter 52 COVID-19 Diagnosis by Wavelet Entropy and Particle Swarm Optimization
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    Chapter 53 An Integrated GAN-Based Approach to Imbalanced Disk Failure Data
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    Chapter 54 Disk Failure Prediction Based on Transfer Learning
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    Chapter 55 Imbalanced Disk Failure Data Processing Method Based on CTGAN
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    Chapter 56 SID 2 T: A Self-attention Model for Spinal Injury Differential Diagnosis
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    Chapter 57 Predicting Protein-DNA Binding Sites by Fine-Tuning BERT
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    Chapter 58 i6mA-word2vec: A Newly Model Which Used Distributed Features for Predicting DNA N6-Methyladenine Sites in Genomes
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    Chapter 59 Oxides Classification with Random Forests
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    Chapter 60 Protein Sequence Classification with LetNet-5 and VGG16
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    Chapter 61 SeqVec-GAT: A Golgi Classification Model Based on Multi-headed Graph Attention Network
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    Chapter 62 Classification of S-succinylation Sites of Cysteine by Neural Network
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    Chapter 63 E. coli Proteins Classification with Naive Bayesian
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    Chapter 64 COVID-19 and SARS Virus Function Sites Classification with Machine Learning Methods
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    Chapter 65 Identification of Protein Methylation Sites Based on Convolutional Neural Network
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    Chapter 66 Image Repair Based on Least Two-Way Generation Against the Network
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    Chapter 67 Prediction of Element Distribution in Cement by CNN
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    Chapter 68 An Ensemble Framework Integrating Whole Slide Pathological Images and miRNA Data to Predict Radiosensitivity of Breast Cancer Patients
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    Chapter 69 Bio-ATT-CNN: A Novel Method for Identification of Glioblastoma
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    Chapter 70 STE-COVIDNet: A Multi-channel Model with Attention Mechanism for Time Series Prediction of COVID-19 Infection
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    Chapter 71 KDPCnet: A Keypoint-Based CNN for the Classification of Carotid Plaque
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    Chapter 72 Multi-source Data-Based Deep Tensor Factorization for Predicting Disease-Associated miRNA Combinations
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    Chapter 73 Correction to: Multi-source Data-Based Deep Tensor Factorization for Predicting Disease-Associated miRNA Combinations
Attention for Chapter 27: Position-Defined CpG Islands Provide Complete Co-methylation Indexing for Human Genes
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Chapter title
Position-Defined CpG Islands Provide Complete Co-methylation Indexing for Human Genes
Chapter number 27
Book title
Intelligent Computing Theories and Application
Published by
Springer, Cham, January 2022
DOI 10.1007/978-3-031-13829-4_27
Book ISBNs
978-3-03-113828-7, 978-3-03-113829-4
Authors

Xiao, Ming, Yin, Ruiying, Gao, Pengbo, Yu, Jun, Ma, Fubo, Dai, Zichun, Zhang, Le

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