scholarly journals Self-labeling of Fully Mediating Representations by Graph Alignment

2022 ◽  
pp. 46-65
Author(s):  
Martijn Oldenhof ◽  
Adam Arany ◽  
Yves Moreau ◽  
Jaak Simm
Keyword(s):  
Graph Alignment

Node Score, Graph Alignment

2013 ◽  
pp. 1526-1527
Author(s):  
Michal Kolář
Keyword(s):  
Graph Alignment

A Multi -Role Graph Attention Network for Knowledge Graph Alignment

2021 ◽  
Author(s):  
Linyi Ding ◽  
Weijie Yuan ◽  
Kui Meng ◽  
Gongshen Liu
Keyword(s):  
Knowledge Graph ◽  
Attention Network ◽  
Graph Alignment

scholarly journals GraphAligner: rapid and versatile sequence-to-graph alignment

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Mikko Rautiainen ◽  
Tobias Marschall
Keyword(s):  
Genetic Variation ◽  
Error Correction ◽  
Genome Assembly ◽  
State Of The Art ◽  
Source Code ◽  
The State ◽  
Graph Alignment ◽  
Link Type ◽  
Long Reads

Abstract Genome graphs can represent genetic variation and sequence uncertainty. Aligning sequences to genome graphs is key to many applications, including error correction, genome assembly, and genotyping of variants in a pangenome graph. Yet, so far, this step is often prohibitively slow. We present GraphAligner, a tool for aligning long reads to genome graphs. Compared to the state-of-the-art tools, GraphAligner is 13x faster and uses 3x less memory. When employing GraphAligner for error correction, we find it to be more than twice as accurate and over 12x faster than extant tools.Availability: Package manager: https://anaconda.org/bioconda/graphalignerand source code: https://github.com/maickrau/GraphAligner

scholarly journals SEGA: Semiglobal Graph Alignment for Structure-Based Protein Comparison

2011 ◽  
Vol 8 (5) ◽  
pp. 1330-1343 ◽  
Author(s):  
M. Mernberger ◽  
G. Klebe ◽  
E. Hullermeier
Keyword(s):  
Graph Alignment

Data-driven construction of SPARQL queries by approximate question graph alignment in question answering over knowledge graphs

2020 ◽  
Vol 146 ◽  
pp. 113205 ◽  
Author(s):  
Mahdi Bakhshi ◽  
Mohammadali Nematbakhsh ◽  
Mehran Mohsenzadeh ◽  
Amir Masoud Rahmani
Keyword(s):  
Question Answering ◽  
Data Driven ◽  
Graph Alignment ◽  
Knowledge Graphs

Graph alignment and cross-modal learning during early infancy

2013 ◽  
Vol 134 (5) ◽  
pp. 4236-4236
Author(s):  
Andrew R. Plummer
Keyword(s):  
Early Infancy ◽  
Graph Alignment
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