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Chapter and Conference Paper
Electromagnetic-Induced Calcium Signal with Network Coding for Molecular Communications
Molecular communication (MC) has become a new communication technology between nano-scale devices due to its biocompatibility and low energy consumption. Calcium signaling gradually becomes a hot research topi...
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Chapter and Conference Paper
An Accurate Algorithm for Identifying Mutually Exclusive Patterns on Multiple Sets of Genomic Mutations
In cancer genomics, the mutually exclusive patterns of somatic mutations are important biomarkers that are suggested to be valuable in cancer diagnosis and treatment. However, detecting these patterns of mutat...
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Chapter and Conference Paper
Multi-class Cancer Classification of Whole Slide Images Through Transformer and Multiple Instance Learning
Whole slide images (WSIs) are high-resolution and lack localized annotations, whose classification can be treated as a multiple instance learning (MIL) problem while slide-level labels are available. We introd...
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Chapter and Conference Paper
Screening of Key Genes in Retinoblastoma and Construction of ceRNA Regulatory Network
Retinoblastoma (RB) is an intraocular malignancy with a high incidence and very severe symptoms in children and is a rare life-threatening ophthalmic disease. Screening for key genes in retinoblastoma to ident...
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Chapter and Conference Paper
A Rule-Based Approach for Generating Synthetic Biological Pathways
Deep learning has recently enabled many advances for computer vision applications in image recognition, localization, segmentation, and understanding. However, applying deep learning models to a wider variety ...
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Chapter and Conference Paper
Text Mining Enhancements for Image Recognition of Gene Names and Gene Relations
The volume of the biological literature has been increasing fast, which leads to a rapid growth of biological pathway figures included in the related biological papers. Each pathway figure encompasses rich bio...
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Chapter and Conference Paper
Improving Protein-protein Interaction Prediction by Incorporating 3D Genome Information
Numerous computational methods have been proposed to predict protein-protein interactions, none of which however, considers the original DNA loci of the interacting proteins in the perspective of 3D genome. He...
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Chapter and Conference Paper
A Deep Learning Approach Based on Feature Reconstruction and Multi-dimensional Attention Mechanism for Drug-Drug Interaction Prediction
Drug-drug interactions occur when two or more drugs are taken simultaneously or successively. Early discovery of drug-drug interactions can effectively prevent medical accidents and reduce medical costs. There...
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Chapter and Conference Paper
HGDD: A Drug-Disease High-Order Association Information Extraction Method for Drug Repurposing via Hypergraph
Traditional drug research and development (R&D) methods are characterized by high risk and...
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Chapter and Conference Paper
Joint CC and Bimax: A Biclustering Method for Single-Cell RNA-Seq Data Analysis
One of the important aims of analyzing single-cell RNA sequencing (scRNA-seq) data is to discovery new cell subtypes by clustering. For the scRNA-seq data, it is obvious that lots of genes have similar behavio...
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Chapter and Conference Paper
Electromagnetism-Enabled Transmitter of Molecular Communications Using Ca \(^{2+}\) Signals
Molecular Communications provides a promising solution to achieve precise control and process of bio-things in applications of Healthcare-IoT. In this paper, we investigates the mechanism of electromagnetism-i...
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Chapter and Conference Paper
Intelligent Power Controller of Wireless Body Area Networks Based on Deep Reinforcement Learning
Wireless Body Area networks allow groups of tiny sensors to communicate for purpose of medical applications. With the progress of sensor manufacture and artificial intelligence, abundant wearing devices are pr...
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Chapter and Conference Paper
Irreplaceable Amino Acids and Reduced Alphabets in Short-Term and Directed Protein Evolution
In this paper we extend codon volatility definition to amino acid reduced alphabets to characterize mutations that conserve physical-chemical properties. We also define the average relative changeability of am...