31 Result(s)
within
**-** Wang
Life Sciences
Computer Communication Networks
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Chapter and Conference Paper
Combining a High-Throughput Bioinformatics Grid and Bioinformatics Web Services
We have created a high-throughput grid for biological sequence analysis, which is freely accessible via bioinformatics Web services. The system allows the execution of computationally intensive sequence alignm...
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Chapter and Conference Paper
Instance Discovery and Schema Matching with Applications to Biological Deep Web Data Integration
This paper presents data mining-based techniques for enabling data integration across deep web data sources. We target query processing across inter-dependent data sources. Thus, besides input-input and output...
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Chapter and Conference Paper
High-Performance Systems for in Silico Microscopy Imaging Studies
High-resolution medical images from advanced instruments provide rich information about morphological and functional characteristics of biological systems. However, most of the information available in biomedi...
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Chapter and Conference Paper
Deep Convolutional Neural Networks with Residual Blocks for Wafer Map Defect Pattern Recognition
Different deep convolution neural network (DCNN) models have been proposed for wafer map pattern identification and classification tasks in previous studies. However, factors such as the effect of input image ...
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Chapter and Conference Paper
ARGLRR: An Adjusted Random Walk Graph Regularization Sparse Low-Rank Representation Method for Single-Cell RNA-Sequencing Data Clustering
Researchers may now explore biological concerns at the cell level because of the advancement of single-cell transcriptome sequencing technologies. One of the primary applications of single-cell RNA-seq (scRNA-...
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Chapter and Conference Paper
MLMVFE: A Machine Learning Approach Based on Muli-view Features Extraction for Drug-Disease Associations Prediction
Determining the associations between drugs and diseases plays an important role in the drugs development processes. However, current drug-disease associations (DDAs) prediction methods are too homogeneous for ...
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Chapter and Conference Paper
GNN-Dom: An Unsupervised Method for Protein Domain Partition via Protein Contact Map
Protein domains are the basic building blocks of protein structures, which fold and function independently. Protein domain partition could be used as measure to decompose the modeling of a large, multi-domain ...
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Chapter and Conference Paper
Correction to: Simulating Spiking Neural Networks Based on SW26010pro
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Chapter and Conference Paper
Automatic ICD Coding Based on Multi-granularity Feature Fusion
International Classification of Disease (ICD) coding is to assign standard codes, which describe the state of a patient, to a clinical note. It is challenging given the complexity and the number of codes. The ...
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Chapter and Conference Paper
NIDN: Medical Code Assignment via Note-Code Interaction Denoising Network
Clinical records are files that contain detailed information about a patient's health status. Clinical notes are typically complex, and the medical code space is large, so medical code assignment from clinical...
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Chapter and Conference Paper
TDCOSR: A Multimodality Fusion Framework for Association Analysis Between Genes and ROIs of Alzheimer’s Disease
The complementary multimodality data fusion analysis provides a new perspective for revealing associations between genes and brain regions of interests (ROIs) of Alzheimer’s disease (AD). In this paper, we pro...
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Chapter and Conference Paper
A Multimodal Data Fusion-Based Deep Learning Approach for Drug-Drug Interaction Prediction
Prediction of drug-drug interaction (DDI) is one of the vital topics in drug development. Many computational methods have been present for DDI prediction. However, these methods are often limited to exploiting...
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Chapter and Conference Paper
Prediction of Drug-Disease Relationship on Heterogeneous Networks Based on Graph Convolution
Drug-disease association prediction is essential in drug development and repositioning. At present, the proposed drug-disease association prediction models based on graph convolution usually learn the characte...
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Chapter and Conference Paper
Fusing Label Relations for Chinese EMR Named Entity Recognition with Machine Reading Comprehension
Chinese electronic medical records named entity recognition (NER) is a core task in medical knowledge mining, which is usually viewed as a sequence labeling problem. Recent works introduce the machine reading ...
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Chapter and Conference Paper
MPCDDI: A Secure Multiparty Computation-Based Deep Learning Framework for Drug-Drug Interaction Predictions
Drug-drug interaction (DDI) is a key concern in drug development and pharmacovigilance. It is important to improve DDI predictions by integrating multi-source data from various pharmaceutical companies. Unfort...
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Chapter and Conference Paper
Simulating Spiking Neural Networks Based on SW26010pro
The spiking neural network (SNN) simulators play a significant role in modeling neural systems and the study of brain function. Currently, many simulators using CPU or GPU have been developed. However, these s...
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Chapter and Conference Paper
Microanatomy of Left Bundle Branch in Chinese Adult Hearts: Aiming to the Research on Morphological Information
Background: The left bundle branch (LBB) in human heart is very thin and certainly individually different, so the corresponding anatomical data is relatively rare. The gradual spread of His-Purkinje system pac...
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Chapter and Conference Paper
Arabinogalactan Prevented APAP-Induced Acute Liver Injury by Regulating the Intestinal Flora in Mice
Background: This study aimed to explore the mechanism by which arabinogalactan (AG) inhibited N-acetyl-para-aminophenol (APAP)-induced acute liver injury in mice. The balance of the mouse intestinal flora and ...
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Chapter and Conference Paper
Physiological Polyphosphate: A New Molecular Paradigm in Biomedical and Biocomputational Applications for Human Therapy
Inorganic polyphosphates (polyP) consist of linear chains of orthophosphate units linked together by high-energy phosphoanhydride bonds. The family of polyP molecules are evolutionarily old biopolymers and fou...
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Chapter and Conference Paper
CHLPCA: Correntropy-Based Hypergraph Regularized Sparse PCA for Single-Cell Type Identification
Over the past decade, high-throughput sequencing technologies have driven a dramatic increase in single-cell RNA sequencing (scRNA-seq) data. The study of scRNA-seq data has widened the scope and depth of rese...
