Cargando…

GraphML specializations to codify ancestral recombinant graphs

Software which simulates, infers, or analyzes ancestral recombination graphs (ARGs) faces the problem of communicating them. Existing formats omit information either about the location of recombinations along the chromosome or the position of recombinations relative to the branching topology. We pre...

Descripción completa

Detalles Bibliográficos
Autores principales:	McGill, James R., Walkup, Elizabeth A., Kuhner, Mary K.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2013
Materias:	Genetics
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3735989/ https://www.ncbi.nlm.nih.gov/pubmed/23967010 http://dx.doi.org/10.3389/fgene.2013.00146

Ejemplares similares

GraphML-SBGN bidirectional converter for metabolic networks
por: Balaur, Irina, et al.
Publicado: (2022)

The importance and application of the ancestral recombination graph
por: Arenas, Miguel
Publicado: (2013)

Bayesian inference of ancestral recombination graphs
por: Mahmoudi, Ali, et al.
Publicado: (2022)

A minimal descriptor of an ancestral recombinations graph
por: Parida, Laxmi, et al.
Publicado: (2011)

Genome-Wide Inference of Ancestral Recombination Graphs
por: Rasmussen, Matthew D., et al.
Publicado: (2014)

An ancestral recombination graph of human, Neanderthal, and Denisovan genomes
por: Schaefer, Nathan K., et al.
Publicado: (2021)

The era of the ARG: an empiricist's guide to ancestral recombination graphs
por: Lewanski, Alexander L., et al.
Publicado: (2023)

A general and efficient representation of ancestral recombination graphs
por: Wong, Yan, et al.
Publicado: (2023)

Inferring Ancestral Recombination Graphs from Bacterial Genomic Data
por: Vaughan, Timothy G., et al.
Publicado: (2017)

Inference of Ancestral Recombination Graphs through Topological Data Analysis
por: Cámara, Pablo G., et al.
Publicado: (2016)

ARCH: Large-scale Knowledge Graph via Aggregated Narrative Codified Health Records Analysis
por: Gan, Ziming, et al.
Publicado: (2023)

KwARG: parsimonious reconstruction of ancestral recombination graphs with recurrent mutation
por: Ignatieva, Anastasia, et al.
Publicado: (2021)

A Deep-Learning Approach for Inference of Selective Sweeps from the Ancestral Recombination Graph
por: Hejase, Hussein A, et al.
Publicado: (2021)

Biobank-scale inference of ancestral recombination graphs enables genealogical analysis of complex traits
por: Zhang, Brian C., et al.
Publicado: (2023)

Single-cell RNA-seq data analysis using graph autoencoders and graph attention networks
por: Feng, Xiang, et al.
Publicado: (2022)

Predicting lncRNA-protein interactions with bipartite graph embedding and deep graph neural networks
por: Ma, Yuzhou, et al.
Publicado: (2023)

Espalier: Efficient Tree Reconciliation and Ancestral Recombination Graphs Reconstruction Using Maximum Agreement Forests
por: Rasmussen, David A, et al.
Publicado: (2023)

Mapping gene flow between ancient hominins through demography-aware inference of the ancestral recombination graph
por: Hubisz, Melissa J., et al.
Publicado: (2020)

TreeKnit: Inferring ancestral reassortment graphs of influenza viruses
por: Barrat-Charlaix, Pierre, et al.
Publicado: (2022)

Graph Neural Networks and Their Current Applications in Bioinformatics
por: Zhang, Xiao-Meng, et al.
Publicado: (2021)

MRPC: An R Package for Inference of Causal Graphs
por: Badsha, Md. Bahadur, et al.
Publicado: (2021)

Common sense codified
por: CERN Bulletin
Publicado: (2010)

Using Graph Attention Network and Graph Convolutional Network to Explore Human CircRNA–Disease Associations Based on Multi-Source Data
por: Li, Guanghui, et al.
Publicado: (2022)

Hierarchical Microbial Functions Prediction by Graph Aggregated Embedding
por: Hou, Yujie, et al.
Publicado: (2021)

Prediction of lncRNA–Disease Associations via Closest Node Weight Graphs of the Spatial Neighborhood Based on the Edge Attention Graph Convolutional Network
por: Li, Jianwei, et al.
Publicado: (2022)

Correcting for Sequencing Error in Maximum Likelihood Phylogeny Inference
por: Kuhner, Mary K., et al.
Publicado: (2014)

Identifying Disease-Gene Associations With Graph-Regularized Manifold Learning
por: Luo, Ping, et al.
Publicado: (2019)

Graph Embedding Deep Learning Guides Microbial Biomarkers' Identification
por: Zhu, Qiang, et al.
Publicado: (2019)

Editorial: Graph Embedding Methods for Multiple-Omics Data Analysis
por: Lan, Wei, et al.
Publicado: (2021)

Representation Learning: Recommendation With Knowledge Graph via Triple-Autoencoder
por: Geng, Yishuai, et al.
Publicado: (2022)

Graph-structured populations and the Hill–Robertson effect
por: Whigham, Peter A., et al.
Publicado: (2021)

Corrigendum: Graph Embedding Deep Learning Guides Microbial Biomarkers' Identification
por: Zhu, Qiang, et al.
Publicado: (2020)

Multiview Consensus Graph Learning for lncRNA–Disease Association Prediction
por: Tan, Haojiang, et al.
Publicado: (2020)

Identification of the Key Regulators of Spina Bifida Through Graph-Theoretical Approach
por: Tamkeen, Naaila, et al.
Publicado: (2021)

Comparative Analysis of Unsupervised Protein Similarity Prediction Based on Graph Embedding
por: Zhang, Yuanyuan, et al.
Publicado: (2021)

Graph Embedding Based Novel Gene Discovery Associated With Diabetes Mellitus
por: Du, Jianzong, et al.
Publicado: (2021)

GADTI: Graph Autoencoder Approach for DTI Prediction From Heterogeneous Network
por: Liu, Zhixian, et al.
Publicado: (2021)

Knowledge Graphs for Indication Expansion: An Explainable Target-Disease Prediction Method
por: Gurbuz, Ozge, et al.
Publicado: (2022)

Bioinformatic workflow fragment discovery leveraging the social-aware knowledge graph
por: Diao, Jin, et al.
Publicado: (2022)

Matching Biomedical Ontologies via a Hybrid Graph Attention Network
por: Wang, Peng, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_027iv3abl6v2mn26s1hkrf2kf3