Cargando…

spaCI: deciphering spatial cellular communications through adaptive graph model

Cell–cell communications are vital for biological signalling and play important roles in complex diseases. Recent advances in single-cell spatial transcriptomics (SCST) technologies allow examining the spatial cell communication landscapes and hold the promise for disentangling the complex ligand–re...

Descripción completa

Detalles Bibliográficos
Autores principales:	Tang, Ziyang, Zhang, Tonglin, Yang, Baijian, Su, Jing, Song, Qianqian
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Oxford University Press 2022
Materias:	Problem Solving Protocol
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9851335/ https://www.ncbi.nlm.nih.gov/pubmed/36545790 http://dx.doi.org/10.1093/bib/bbac563

Ejemplares similares

SpaRx: elucidate single-cell spatial heterogeneity of drug responses for personalized treatment
por: Tang, Ziyang, et al.
Publicado: (2023)

Deciphering signatures of natural selection via deep learning
por: Qin, Xinghu, et al.
Publicado: (2022)

An inductive graph neural network model for compound–protein interaction prediction based on a homogeneous graph
por: Wan, Xiaozhe, et al.
Publicado: (2022)

SWEET: a single-sample network inference method for deciphering individual features in disease
por: Chen, Hsin-Hua, et al.
Publicado: (2023)

cropCSM: designing safe and potent herbicides with graph-based signatures
por: Pires, Douglas E V, et al.
Publicado: (2022)

Ensembles of knowledge graph embedding models improve predictions for drug discovery
por: Rivas-Barragan, Daniel, et al.
Publicado: (2022)

SMG: self-supervised masked graph learning for cancer gene identification
por: Cui, Yan, et al.
Publicado: (2023)

Drug repositioning based on weighted local information augmented graph neural network
por: Meng, Yajie, et al.
Publicado: (2023)

An end-to-end heterogeneous graph attention network for Mycobacterium tuberculosis drug-resistance prediction
por: Yang, Yang, et al.
Publicado: (2021)

netANOVA: novel graph clustering technique with significance assessment via hierarchical ANOVA
por: Duroux, Diane, et al.
Publicado: (2023)

Subgraph extraction and graph representation learning for single cell Hi-C imputation and clustering
por: Zheng, Jiahao, et al.
Publicado: (2023)

A universal framework for single-cell multi-omics data integration with graph convolutional networks
por: Gao, Hongli, et al.
Publicado: (2023)

Fusing 2D and 3D molecular graphs as unambiguous molecular descriptors for conformational and chiral stereoisomers
por: Du, Wenjie, et al.
Publicado: (2022)

Assessing protein model quality based on deep graph coupled networks using protein language model
por: Liu, Dong, et al.
Publicado: (2023)

SPCS: a spatial and pattern combined smoothing method for spatial transcriptomic expression
por: Liu, Yusong, et al.
Publicado: (2022)

Predicting gene regulatory links from single-cell RNA-seq data using graph neural networks
por: Mao, Guo, et al.
Publicado: (2023)

MeSHHeading2vec: a new method for representing MeSH headings as vectors based on graph embedding algorithm
por: Guo, Zhen-Hao, et al.
Publicado: (2020)

AttentionSiteDTI: an interpretable graph-based model for drug-target interaction prediction using NLP sentence-level relation classification
por: Yazdani-Jahromi, Mehdi, et al.
Publicado: (2022)

Natural Language Processing with Python and spaCy
por: Vasiliev, Yuli
Publicado: (2020)

Comprehensive assessment of cellular senescence in the tumor microenvironment
por: Wang, Xiaoman, et al.
Publicado: (2022)

CHERRY: a Computational metHod for accuratE pRediction of virus–pRokarYotic interactions using a graph encoder–decoder model
por: Shang, Jiayu, et al.
Publicado: (2022)

Benchmarking cell-type clustering methods for spatially resolved transcriptomics data
por: Cheng, Andrew, et al.
Publicado: (2022)

KLFDAPC: a supervised machine learning approach for spatial genetic structure analysis
por: Qin, Xinghu, et al.
Publicado: (2022)

Spatial density of open chromatin: an effective metric for the functional characterization of topologically associated domains
por: Jiang, Shuai, et al.
Publicado: (2020)

FunRes: resolving tissue-specific functional cell states based on a cell–cell communication network model
por: Jung, Sascha, et al.
Publicado: (2020)

SpaRx: Elucidate single-cell spatial heterogeneity of drug responses for personalized treatment
por: Tang, Ziyang, et al.
Publicado: (2023)

Deep learning based on biologically interpretable genome representation predicts two types of human adaptation of SARS-CoV-2 variants
por: Li, Jing, et al.
Publicado: (2022)

Protein functional annotation of simultaneously improved stability, accuracy and false discovery rate achieved by a sequence-based deep learning
por: Hong, Jiajun, et al.
Publicado: (2019)

Clinical trials, progression-speed differentiating features and swiftness rule of the innovative targets of first-in-class drugs
por: Li, Ying Hong, et al.
Publicado: (2019)

ANPELA: analysis and performance assessment of the label-free quantification workflow for metaproteomic studies
por: Tang, Jing, et al.
Publicado: (2019)

CAFU: a Galaxy framework for exploring unmapped RNA-Seq data
por: Chen, Siyuan, et al.
Publicado: (2019)

Virus-CKB: an integrated bioinformatics platform and analysis resource for COVID-19 research
por: Feng, Zhiwei, et al.
Publicado: (2020)

MolAICal: a soft tool for 3D drug design of protein targets by artificial intelligence and classical algorithm
por: Bai, Qifeng, et al.
Publicado: (2020)

New insights on human essential genes based on integrated analysis and the construction of the HEGIAP web-based platform
por: Chen, Hebing, et al.
Publicado: (2019)

A comprehensive method protocol for annotation and integrated functional understanding of lncRNAs
por: Kunz, Meik, et al.
Publicado: (2019)

An efficient multi-locus mixed model framework for the detection of small and linked QTLs in F(2)
por: Wen, Yang-Jun, et al.
Publicado: (2018)

Revealing tumor heterogeneity of breast cancer by utilizing the linkage between somatic and germline mutations
por: Zou, Meng, et al.
Publicado: (2018)

Protein–peptide docking using CABS-dock and contact information
por: Blaszczyk, Maciej, et al.
Publicado: (2018)

Regression on imperfect class labels derived by unsupervised clustering
por: Brøndum, Rasmus Froberg, et al.
Publicado: (2020)

Toward a gold standard for benchmarking gene set enrichment analysis
por: Geistlinger, Ludwig, et al.
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_t75ujok4trgqe6hh0lvnavp5il