Xiaolong Liu,Jianxia Chen,Wenzhe Chen et al.
Xiaolong Liu et al.
Recently, link prediction (LP) based on graph neural networks (GNNs) methods has achieved notable successes in biological networks (BNs), since it can reveal the organizational principles, functional mechanisms, and dynamic properties of bi...
scDFVA: Single-Cell Deep Clustering by Fusing Variational Graph Attention Autoencoder and ZINB-Based Autoencoder [0.03%]
基于变分图注意力自编码器和ZINB自编码器融合的单细胞深度聚类方法
Ge Zhang,Maohua Qin,Xuye Kou et al.
Ge Zhang et al.
Single-cell RNA sequencing (scRNA-seq) provides a novel perspective to explore cellular biology at the single-cell resolution. Single-cell clustering is a crucial step to reveal cell types and the corresponding biological functions. However...
A Structure-Aware Multimodal Framework for Drug-Target Interaction Prediction via Heterogeneous Graph Learning [0.03%]
一种基于异构图学习的结构感知多模态药物靶点相互作用预测框架
Hua Qian,Deng Pan,Liangpeng Nie et al.
Hua Qian et al.
Predicting drug-target interactions is critical for drug discovery, yet many deep learning methods overlook atom-residue-level relationships. We propose Protein Heterogeneous Graph learning for Drug-Target Interaction prediction (PHGDTI), a...
NCTDA: Nearest Neighbor Gaussian Process-Based Cell Type-Specific Spatially Variable Gene Detection Analysis [0.03%]
基于最近邻高斯过程的细胞类型特异性空间可变基因检测分析(NCTDA)
Zhixin Shi,Ziyan Sun,Yuan Zhang et al.
Zhixin Shi et al.
A primary task of spatial transcriptomics is detecting spatially variable genes (SVGs). Many genes may show spatially heterogeneous expression in specific cell types while showing spatial randomness across the whole tissue, thereby defining...
Mosquito Species and Gender Identification System Based on Artificial Intelligence and Image Processing Methods [0.03%]
基于人工智能和图像处理的蚊虫种类及雌雄鉴别系统
Fu-Hsing Wu,Chuen-Horng Lin,Xin-Yi Zhang et al.
Fu-Hsing Wu et al.
Vector mosquito bites can significantly impact quality of life, pose health risks, and even lead to death. Different mosquito species can transmit various diseases, and their blood-sucking behavior varies by sex. Therefore, accurately ident...
GMSA: A Graph Matching and Point Cloud Registration-Based Method for Spatial Transcriptomics Data Alignment [0.03%]
基于图匹配和点云配准的空间转录组学数据对齐方法(GMSA)
Longfei Tang,Shutong Xiao,Zhao He et al.
Longfei Tang et al.
Spatial transcriptomics (ST) often requires aligning multiple tissue slices to reconstruct three-dimensional biological structures, a task hindered by complex deformations and structural heterogeneity. We propose GMSA, a synergistic alignme...
Ismoiljon Muzaffarov,Xiaowen Liu,Letu Qingge et al.
Ismoiljon Muzaffarov et al.
In this article, we initiate the study on some problems related to multiple protein scaffold filling, with or without references. The objective is to maximize the sum of Blosum62 scores of the filled sequences when no reference is given, or...
Cell Type Prediction for Single-Cell RNA Sequencing Utilizing Unsupervised Domain Adaptation and Semi-Supervised Learning [0.03%]
利用无监督领域适应和半监督学习进行单细胞RNA测序的细胞类型预测
Chaelin Park,Joung Min Choi,Heejoon Chae
Chaelin Park
Single-cell RNA sequencing (scRNA-seq) techniques for measuring gene expression in individual cells have developed rapidly. Recently, the identification of cell types in scRNA-seq analysis has been accomplished using deep learning. Most met...
PPIGAN: Prediction of Protein-Protein Interactions Using Generative Adversarial Networks [0.03%]
基于生成对抗网络的蛋白质-蛋白质相互作用预测模型(PPIGAN)
Xu Zhang,Songyan Xue,Jing Geng et al.
Xu Zhang et al.
The prediction of protein-protein interaction (PPI) can be insightful for exploring the molecular mechanisms of cellular functions. Constructing the negative datasets of PPI is related to the assessment of the prediction accuracy and evalua...
Deep Structure-Enhanced Cell Clustering Model for Single-Cell RNA Sequencing Data [0.03%]
一种深度结构增强的单细胞RNA序列数据细胞聚类模型
Maoxuan Yao,Lina Ren
Maoxuan Yao
Recently, deep cell clustering, which employs deep neural networks to learn cell representation for clustering purposes, has attracted increasing research interests. Traditional deep cell clustering models for single-cell RNA sequencing dat...