Le Ou-Yang
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View article: Ultrasound-Assisted Green Natural Deep Eutectic Solvent Extraction of Flavonoids from Wild Blueberry: Process Optimization, Composition Identification, and Antioxidant Activity
Ultrasound-Assisted Green Natural Deep Eutectic Solvent Extraction of Flavonoids from Wild Blueberry: Process Optimization, Composition Identification, and Antioxidant Activity Open
To improve the deep processing and utilization of wild blueberries, this study presents a green and highly efficient method for extracting flavonoids from blueberries. The approach combines natural deep eutectic solvents (NADESs) with ultr…
View article: Unveiling spatial domains from spatial multi-omics data using dual-graph regularized ensemble learning
Unveiling spatial domains from spatial multi-omics data using dual-graph regularized ensemble learning Open
With the rapid advancement of spatial multi-omics technologies, the simultaneous analysis of molecular profiles and spatial locations has provided unprecedented insights into cellular heterogeneity and tissue microenvironments. However, da…
View article: GeCC: Generalized Contrastive Clustering with Domain Shifts Modeling
GeCC: Generalized Contrastive Clustering with Domain Shifts Modeling Open
Contrastive clustering performs clustering and data representation in a unified model, where instance- and cluster-level constrastive learning are conducted simultaneously. However, commonly-used data augmentation methods make contrastive …
View article: GCLink: a graph contrastive link prediction framework for gene regulatory network inference
GCLink: a graph contrastive link prediction framework for gene regulatory network inference Open
Motivation Gene regulatory networks (GRNs) unveil the intricate interactions among genes, pivotal in elucidating the complex biological processes within cells. The advent of single-cell RNA-sequencing (scRNA-seq) enables the inference of G…
View article: Trace Element Geochemical Characteristics of Plants and Their Role in Indicating Concealed Ore Bodies outside the Shizhuyuan W–Sn Polymetallic Deposit, Southern Hunan Province, China
Trace Element Geochemical Characteristics of Plants and Their Role in Indicating Concealed Ore Bodies outside the Shizhuyuan W–Sn Polymetallic Deposit, Southern Hunan Province, China Open
To explore the potential of plant trace elements as indicators in the search for concealed deposits within the W–Sn polymetallic mining area of Shizhuyuan, Hunan Province, this study focused on the geochemical characterization of 21 trace …
View article: NJGCG: A node-based joint Gaussian copula graphical model for gene networks inference across multiple states
NJGCG: A node-based joint Gaussian copula graphical model for gene networks inference across multiple states Open
Inferring the interactions between genes is essential for understanding the mechanisms underlying biological processes. Gene networks will change along with the change of environment and state. The accumulation of gene expression data from…
View article: Clustering single-cell multi-omics data via graph regularized multi-view ensemble learning
Clustering single-cell multi-omics data via graph regularized multi-view ensemble learning Open
Motivation Single-cell clustering plays a crucial role in distinguishing between cell types, facilitating the analysis of cell heterogeneity mechanisms. While many existing clustering methods rely solely on gene expression data obtained fr…
View article: MARS: a motif-based autoregressive model for retrosynthesis prediction
MARS: a motif-based autoregressive model for retrosynthesis prediction Open
Motivation Retrosynthesis is a critical task in drug discovery, aimed at finding a viable pathway for synthesizing a given target molecule. Many existing approaches frame this task as a graph-generating problem. Specifically, these methods…
View article: ETDock: A Novel Equivariant Transformer for Protein-Ligand Docking
ETDock: A Novel Equivariant Transformer for Protein-Ligand Docking Open
Predicting the docking between proteins and ligands is a crucial and challenging task for drug discovery. However, traditional docking methods mainly rely on scoring functions, and deep learning-based docking approaches usually neglect the…
View article: A partially shared joint clustering framework for detecting protein complexes from multiple state-specific signed interaction networks
A partially shared joint clustering framework for detecting protein complexes from multiple state-specific signed interaction networks Open
Detecting protein complexes is critical for studying cellular organizations and functions. The accumulation of protein-protein interaction (PPI) data enables the identification of protein complexes computationally. Although various computa…
View article: Inferring cancer common and specific gene networks via multi-layer joint graphical model
Inferring cancer common and specific gene networks via multi-layer joint graphical model Open
Cancer is a complex disease caused primarily by genetic variants. Reconstructing gene networks within tumors is essential for understanding the functional regulatory mechanisms of carcinogenesis. Advances in high-throughput sequencing tech…
View article: MIDAS: a deep generative model for mosaic integration and knowledge transfer of single-cell multimodal data
MIDAS: a deep generative model for mosaic integration and knowledge transfer of single-cell multimodal data Open
A bstract Rapidly developing single-cell multi-omics sequencing technologies generate increasingly large bodies of multimodal data. Integrating multimodal data from different sequencing technologies, i.e . mosaic data, permits larger-scale…
View article: Predicting Protein-Ligand Binding Affinity with Equivariant Line Graph Network
Predicting Protein-Ligand Binding Affinity with Equivariant Line Graph Network Open
Binding affinity prediction of three-dimensional (3D) protein ligand complexes is critical for drug repositioning and virtual drug screening. Existing approaches transform a 3D protein-ligand complex to a two-dimensional (2D) graph, and th…
View article: MARS: A Motif-based Autoregressive Model for Retrosynthesis Prediction
MARS: A Motif-based Autoregressive Model for Retrosynthesis Prediction Open
Retrosynthesis is a major task for drug discovery. It is formulated as a graph-generating problem by many existing approaches. Specifically, these methods firstly identify the reaction center, and break target molecule accordingly to gener…
View article: Editorial: Machine Learning and Mathematical Models for Single-Cell Data Analysis
Editorial: Machine Learning and Mathematical Models for Single-Cell Data Analysis Open
Understanding how individual cells communicate with each other and respond to evolution and perturbations is a central challenge of biology (Altschuler and Wu, 2010). Due to the heterogeneity of cells, studying a bulk population of cells m…
View article: Design and Optimization of Metal Cavity Bandpass Filter and Fragmented Patch Antenna By Combining Simulation Software and Genetic Algorithm
Design and Optimization of Metal Cavity Bandpass Filter and Fragmented Patch Antenna By Combining Simulation Software and Genetic Algorithm Open
An electromagnetic (EM) structure optimization method based on Genetic algorithm (GA) and EM simulation software is proposed. The aim is to accelerate optimization speed of electromagnetic structure and improve designed performance. An alg…
View article: Willingness to receive SARS-CoV-2 vaccine among healthcare workers in public institutions of Zhejiang Province, China
Willingness to receive SARS-CoV-2 vaccine among healthcare workers in public institutions of Zhejiang Province, China Open
This study aims to investigate healthcare workers' (HCWs) willingness to receive SARS-CoV-2 vaccine in Zhejiang and to discover the related influential factors. The survey was conducted in six regions of Zhejiang Province, China, and 13 ho…
View article: EC-PGMGR: Ensemble Clustering Based on Probability Graphical Model With Graph Regularization for Single-Cell RNA-seq Data
EC-PGMGR: Ensemble Clustering Based on Probability Graphical Model With Graph Regularization for Single-Cell RNA-seq Data Open
Advances in technology have made it convenient to obtain a large amount of single cell RNA sequencing (scRNA-seq) data. Since that clustering is a very important step in identifying or defining cellular phenotypes, many clustering approach…
View article: T3SEpp: an Integrated Prediction Pipeline for Bacterial Type III Secreted Effectors
T3SEpp: an Integrated Prediction Pipeline for Bacterial Type III Secreted Effectors Open
Type III secreted effector (T3SE) prediction remains a big computational challenge. In practical applications, current software tools often suffer problems of high false-positive rates. One of the causal factors could be the relatively uni…
View article: A graph regularized generalized matrix factorization model for predicting links in biomedical bipartite networks
A graph regularized generalized matrix factorization model for predicting links in biomedical bipartite networks Open
Motivation Predicting potential links in biomedical bipartite networks can provide useful insights into the diagnosis and treatment of complex diseases and the discovery of novel drug targets. Computational methods have been proposed recen…
View article: Joint reconstruction of multiple gene networks by simultaneously capturing inter-tumor and intra-tumor heterogeneity
Joint reconstruction of multiple gene networks by simultaneously capturing inter-tumor and intra-tumor heterogeneity Open
Motivation Reconstruction of cancer gene networks from gene expression data is important for understanding the mechanisms underlying human cancer. Due to heterogeneity, the tumor tissue samples for a single cancer type can be divided into …
View article: Presentation_1_Weighted Fused Pathway Graphical Lasso for Joint Estimation of Multiple Gene Networks.pdf
Presentation_1_Weighted Fused Pathway Graphical Lasso for Joint Estimation of Multiple Gene Networks.pdf Open
Gene regulatory networks (GRNs) are often inferred based on Gaussian graphical models that could identify the conditional dependence among genes by estimating the corresponding precision matrix. Classical Gaussian graphical models are usua…
View article: Weighted Fused Pathway Graphical Lasso for Joint Estimation of Multiple Gene Networks
Weighted Fused Pathway Graphical Lasso for Joint Estimation of Multiple Gene Networks Open
Gene regulatory networks (GRNs) are often inferred based on Gaussian graphical models that could identify the conditional dependence among genes by estimating the corresponding precision matrix. Classical Gaussian graphical models are usua…
View article: LncRNA-Disease Association Prediction Using Two-Side Sparse Self-Representation
LncRNA-Disease Association Prediction Using Two-Side Sparse Self-Representation Open
Evidences increasingly indicate the involvement of long non-coding RNAs (lncRNAs) in various biological processes. As the mutations and abnormalities of lncRNAs are closely related to the progression of complex diseases, the identification…
View article: Semantic Hierarchy Preserving Deep Hashing for Large-scale Image Retrieval
Semantic Hierarchy Preserving Deep Hashing for Large-scale Image Retrieval Open
Deep hashing models have been proposed as an efficient method for large-scale similarity search. However, most existing deep hashing methods only utilize fine-level labels for training while ignoring the natural semantic hierarchy structur…