- Häftad (Paperback / softback)
- Antal sidor
- 1st ed. 2019
- Springer Nature Switzerland AG
- Jo, Kang-Hyun / Huang, Zhi-Kai
- 243 Illustrations, color; 80 Illustrations, black and white; XXI, 790 p. 323 illus., 243 illus. in c
- Antal komponenter
- 1 Paperback / softback
Du kanske gillar
Intelligent Computing Theories and Application
15th International Conference, ICIC 2019, Nanchang, China, August 3-6, 2019, Proceedings, Part II
Fri frakt inom Sverige för privatpersoner.
Bloggat om Intelligent Computing Theories and Applic...
Particle Swarm Optimization-based Power Allocation Scheme for Secrecy Sum Rate Maximization in NOMA with Cooperative Relaying.- A Discrete Particle Swarm Optimization for PairwiseSequence Alignment.- A Diversity based Competitive Multi-Objective PSO for Feature Selection.- A Decomposition-based Hybrid Estimation of Distribution Algorithm for Practical Mean-CVaR Portfolio Optimization.- CBLNER: a multi-models biomedical named entity recognition system based on machine learning.- Dice Loss in Siamese Network for Visual Object Tracking.- Fuzzy PID Controller for Accurate Power Sharing in DC Microgrid.- Precipitation Modeling and Prediction Based on Fuzzy-control Multi-cellular Gene Expression Programming and Wavelet Transform.- Integrative Enrichment Analysis of Intra- and Inter- Tissues' Differentially Expressed Genes Based on Perceptron.- Identifying differentially expressed genes based on differentially expressed edges.- Gene functional module discovery via integrating geneexpression and PPI network data.- A novel framework for improving the prediction of disease-associated microRNAs.- Precise Prediction of Pathogenic Microorganisms using 16S rRNA Gene Sequences.- Learning from Deep Representations of Multiple Networks for Predicting Drug-Target Interactions.- Simulation of Complex neural firing patterns based on improved deterministic Chay model.- Knowledge based helix angle and residue distance restraint free energy terms of GPCRs.- Improved Spectral Clustering Method for Identifying Cell Types from Single-Cell Data.- A Novel Weight Learning Approach Based on Density for Accurate Prediction of Atherosclerosis.- An effective approach of measuring disease similarities based on the DNN regression model.- Herb Pair Danggui-Baishao:Pharmacological Mechanisms Underlying Primary Dysmenorrhea by Network Pharmacology Approach.- End-to-end learning based compound activity prediction using binding pocket information.- A novel approach for predicting lncRNA-disease associations by structural perturbation method.- Improved Inductive Matrix Completion Method for Predicting MicroRNA-Disease Associations.- A link and Weight-Based Ensemble Clustering for Patient Stratification.- HGMDA:HyperGraph for Predicting MiRNA-disease Association.- Discovering Driver Mutation Profiles in Cancer with A Local Centrality Score.- LRMDA: Using Logistic Regression and Random Walk with Restart for MiRNA-Disease Association Prediction.- Distinguishing driver missense mutations from benign polymorphisms in breast cancer.- A novel method to predict protein regions driving cancer through integration of multi-omics data.- In Silico Identification of Anticancer Peptides with Stacking Heterogeneous Ensemble Learning Model and Sequence Information.- Effective Analysis of Hot Spots in Hub Protein Interfaces Based on Random Forest.- Prediction of human lncRNAs based on integrated information entropy features.- A Gated Recurrent Unit Model for Drug Repositioning by Combining Comprehensive Similarity Measures and Gaussian Interaction Profile Kernel.- A Novel Approach to predicting miRNA-disease associations.- Hierarchical Attention Network for Predicting DNA-Protein Binding Sites.- Motif discovery via convolutional networks with k-mer embedding.- Whole-Genome Shotgun Sequence of Natronobacterium Gregoryi SP2.- The detection of gene modules with overlapping characteristic via integrating multi-omics data in six cancers.- Combining High Speed ELM with a CNN Feature Encoding to Predict LncRNA-Disease Associations.- A prediction method of DNA-binding proteins based on evolutionary information.- Research on RNA Secondary Structure Prediction Based on Decision Tree.- Improving hot region prediction by combining gaussian naive Bayes and DBSCAN.- An efficient LightGBM model to predict protein selfinteracting using Chebyshev moments and bi-gram.- Combining Evolutionary Information and Sparse Bayesian Probability Model to Accurately Predict Self-Interacting Proteins.- Identificati