A5100456729- Cancer therapeutics and mechanisms
- Advanced Clustering Algorithms Research
- Synthesis and Catalytic Reactions
- Complex Network Analysis Techniques
- Face and Expression Recognition
- Advanced Graph Neural Networks
- Cancer, Hypoxia, and Metabolism
- Chemical Synthesis and Analysis
- Microbial Natural Products and Biosynthesis
- Advanced Computing and Algorithms
- Marine Sponges and Natural Products
- Network Security and Intrusion Detection
- Text and Document Classification Technologies
- PARP inhibition in cancer therapy
- Data Management and Algorithms
- Reinforcement Learning in Robotics
- Histone Deacetylase Inhibitors Research
- Advanced Computational Techniques and Applications
- Image Retrieval and Classification Techniques
- Biochemical and Molecular Research
- Graph Theory and Algorithms
- Image and Signal Denoising Methods
- Plant-Microbe Interactions and Immunity
- Neural Networks and Applications
- Protein Degradation and Inhibitors
Tianjin University
2022-2024
Foshan Hospital of TCM
2024
Technical University of Denmark
2024
Guangzhou University of Chinese Medicine
2024
Agricultural Genomics Institute at Shenzhen
2023
Shandong First Medical University
2023
Shandong Provincial Hospital
2023
Chinese Academy of Agricultural Sciences
2023
Hubei University of Education
2023
Ningxia Medical University General Hospital
2022
Seeds establish dormancy to delay germination until the arrival of a favorable growth season. Here, we identify fate switch constituted by MKK3-MPK7 kinase cascade and ethylene response factor ERF4 responsible for seed state transition from germination. We show that dormancy-breaking factors activate module, which affects relies on expression some EXPAs control dormancy. Furthermore, direct downstream substrate this ERF4, suppresses these directly binding GCC boxes in their exon regions. The...
Today, the concept of brain connectivity plays a central role in neuroscience. While functional is defined as temporal coherence between activities different areas, effective simplest circuit that would produce same relationship observed experimentally cortical sites. The most used method to estimate neuroscience structural equation modeling (SEM), typically on data related hemodynamic behavior. However, use measures limits resolution which process can be followed. present research proposes...
Communication learning is an important research direction in the multiagent reinforcement (MARL) domain. Graph neural networks (GNNs) can aggregate information of neighbor nodes for representation learning. In recent years, several MARL methods leverage GNN to model interactions between agents coordinate actions and complete cooperative tasks. However, simply aggregating neighboring through GNNs may not extract enough useful information, topological relationship ignored. To tackle this...
Root-knot nematodes (RKNs, Meloidogyne spp.) seriously damage tomato production worldwide, and biocontrol bacteria can induce immunity to RKNs. Our previous studies have revealed that Pseudomonas putida strain Sneb821 trigger against M. incognita several long noncoding RNAs microRNAs (miRNAs) are involved in this process. However, the molecular functions of miRNAs immune responses remain unclear. In study, deep small RNA sequencing identified 78 differentially expressed plants inoculated...
Efficient communication learning among agents has been shown crucial for cooperative multi-agent reinforcement (MARL), as it can promote the action coordination of and ultimately improve performance. Graph neural network (GNN) provide a general paradigm learning, which consider channels nodes edges in graph, with selection corresponding to node labeling. Under such paradigm, an agent aggregates information from neighbor agents, reduce uncertainty local decision-making induce implicit...
Image clustering is a research hotspot in machine learning and computer vision. Existing graph-based semi-supervised deep methods suffer from three problems: 1) because uses only high-level features, the detailed information contained shallow-level features ignored; 2) most feature extraction networks employ step odd convolutional kernel, which results an uneven distribution of receptive field intensity; 3) adjacency matrix precomputed fixed, it cannot adapt to changes relationship between...
Information sharing through communication is essential for tackling complex multi-agent reinforcement learning tasks. Many existing protocols can be viewed as instances of message passing graph neural networks (GNNs). However, due to the significantly limited expressive ability standard GNN method, agent feature representations remain similar and indistinguishable even though agents have different neighborhood structures. This further results in homogenization behaviors reduces capability...
Fungi provide valuable solutions for diverse biotechnological applications, such as enzymes in the food industry, bioactive metabolites healthcare, and biocontrol organisms agriculture. Current workflows identifying new fungi often rely on subjective visual observations of strains' performance microbe-microbe interaction studies, making process time-consuming difficult to reproduce. To overcome these challenges, we developed an AI-automated image classification approach using machine...
Broad learning system (BLS) is a novel randomized framework which has faster modeling efficiency. Although BLS with incremental better extendibility for updating model rapidly, the mode of lacks self-supervision mechanism cannot adjust structure adaptively. Learning from idea stochastic configuration network (SCN), multilayer based on (SC) algorithm proposed regression, termed as IMLBLS-SC. First, to improve feature ability, SC adopted configure parameters enhancement nodes instead random...
Recent research on multi-agent reinforcement learning (MARL) has shown that action coordination of multi-agents can be significantly enhanced by introducing communication mechanisms. Meanwhile, graph neural network (GNN) provides a promising paradigm for MARL. Under this paradigm, agents and channels regarded as nodes edges in the graph, aggregate information from neighboring through GNN. However, GNN-based is susceptible to adversarial attacks noise perturbations, how achieve robust under...