A5021455957- Single-cell and spatial transcriptomics
- Gene expression and cancer classification
- Cancer-related molecular mechanisms research
- Machine Learning in Bioinformatics
- Neuroinflammation and Neurodegeneration Mechanisms
- Bioinformatics and Genomic Networks
- Face and Expression Recognition
- Immune cells in cancer
- Circular RNAs in diseases
- MicroRNA in disease regulation
- Macrophage Migration Inhibitory Factor
- Cell Image Analysis Techniques
- RNA and protein synthesis mechanisms
- Model-Driven Software Engineering Techniques
- Mobile Agent-Based Network Management
- Extracellular vesicles in disease
- Machine Learning and ELM
- Text and Document Classification Technologies
- Genetics, Bioinformatics, and Biomedical Research
- Embedded Systems and FPGA Design
- Advanced Algorithms and Applications
- Advanced Image and Video Retrieval Techniques
- Domain Adaptation and Few-Shot Learning
- E-commerce and Technology Innovations
- Image Retrieval and Classification Techniques
Quzhou University
2022-2024
University of Electronic Science and Technology of China
2022-2024
The Ohio State University
2020-2022
Tianjin University
2020-2022
Tianjin University of Science and Technology
2018
Wuhan College
2011
Abstract Single-cell RNA-sequencing (scRNA-Seq) is widely used to reveal the heterogeneity and dynamics of tissues, organisms, complex diseases, but its analyses still suffer from multiple grand challenges, including sequencing sparsity differential patterns in gene expression. We introduce scGNN (single-cell graph neural network) provide a hypothesis-free deep learning framework for scRNA-Seq analyses. This formulates aggregates cell–cell relationships with networks models heterogeneous...
Alzheimer's disease (AD) is a progressive neurodegenerative disorder of the brain and most common form dementia among elderly. The single-cell RNA-sequencing (scRNA-Seq) single-nucleus (snRNA-Seq) techniques are extremely useful for dissecting function/dysfunction highly heterogeneous cells in at level, corresponding data analyses can significantly improve our understanding why particular vulnerable AD. We developed an integrated database named scREAD (single-cell RNA-Seq disease), which as...
The rapid development of single-cell RNA sequencing (scRNA-Seq) technology provides strong technical support for accurate and efficient analyzing gene expression data. However, the analysis scRNA-Seq is accompanied by many obstacles, including dropout events curse dimensionality. Here, we propose scGMAI, which a new Gaussian mixture clustering method based on autoencoder networks fast independent component (FastICA). Specifically, scGMAI utilizes to reconstruct values from data FastICA used...
Single-cell RNA-sequencing (scRNA-seq) data widely exist in bioinformatics. It is crucial to devise a distance metric for scRNA-seq data. Almost all existing clustering methods based on spectral algorithms work three separate steps: similarity graph construction; continuous labels learning; discretization of the learned by k-means clustering. However, this common practice has potential flaws that may lead severe information loss and degradation performance. Furthermore, performance kernel...
Most existing metric learning methods focus on a similarity or distance measure relying similar and dissimilar relations between sample pairs. However, pairs of samples cannot be simply identified as in many real-world applications, e.g., multi-label learning, label distribution tasks with continuous decision values. To this end, paper we propose novel relation alignment (RAML) formulation to handle the problem those scenarios. Since two can measured by difference degree values, motivated...
ABSTRACT Single-cell RNA-sequencing (scRNA-Seq) is widely used to reveal the heterogeneity and dynamics of tissues, organisms, complex diseases, but its analyses still suffer from multiple grand challenges, including sequencing sparsity differential patterns in gene expression. We introduce scGNN (single-cell graph neural network) provide a hypothesis-free deep learning framework for scRNA-Seq analyses. This formulates aggregates cell-cell relationships with networks models heterogeneous...
Advances in single-cell RNA sequencing (scRNA-seq) technologies allow researchers to analyze the genome-wide transcription profile and solve biological problems at individual-cell resolution. However, existing clustering methods on scRNA-seq suffer from high dropout rate curse of dimensionality data. Here, we propose a novel pipeline, scBKAP, cornerstone which is bisecting K-means method based an autoencoder network reduction model MPDR. Specially, scBKAP utilizes reconstruct gene expression...
Abstract Summary Alzheimer’s disease (AD) is a progressive neurodegenerative disorder of the brain and most common form dementia among elderly. The single-cell RNA-sequencing (scRNA-Seq) single-nucleus (snRNA-Seq) techniques are extremely useful for dissecting function/dysfunction highly heterogeneous cells in at level, corresponding data analyses can significantly improve our understanding why particular vulnerable AD. We developed an integrated database named scREAD ( s ingle- c ell R...
ABSTRACT Massively bulk RNA sequencing databases incorporating drug screening have opened up an avenue to inform the optimal clinical application of cancer drugs. Meanwhile, growing single-cell (scRNA-seq) data contributes improving therapeutic effectiveness by studying heterogeneity responses for cell subpopulations. There is a clear significance in developing computational biology approaches predict and interpret response single from samples. Here, we introduce scDEAL, deep transfer...
Pseudouridine is a type of abundant RNA modification that seen in many different animals and crucial for variety biological functions. Accurately identifying pseudouridine sites within the sequence vital subsequent study various mechanisms pseudouridine. However, use traditional experimental methods faces certain challenges. The development fast convenient computational necessary to accurately identify from information. To address this, we introduce novel site prediction model called...
This paper analyzes the role of image identification technology in security systems for intelligent buildings, and proposes that incorporating technical support can enhance intelligence automation thus provide users buildings with more secure, convenient, comfortable living workplace environments.
Alzheimer's disease (AD) is a progressive neurodegenerative disorder of the brain and most common form dementia among elderly. The single-cell RNA-sequencing (scRNA-Seq) single-nucleus (snRNA-Seq) techniques are extremely useful for dissecting function/dysfunction highly heterogeneous cells in at level, corresponding data analyses can significantly improve our understanding why particular vulnerable AD. We developed an integrated database named scREAD (single-cell RNA-Seq Disease), which as...