CATH version 3.5 (Class, Architecture, Topology, Homology, available at http://www.cathdb.info/) contains 173 536 domains, 2626 homologous superfamilies and 1313 fold groups. When focusing on structural genomics (SG) structures, we observe that the number of new folds for CATH v3.5 is slightly less than for previous releases, and this observation suggests that we may now know the majority of folds that are easily accessible to structure determination. We have improved the accuracy of our functional family (FunFams) sub-classification method and the CATH sequence domain search facility has been extended to provide FunFam annotations for each domain. The CATH website has been redesigned. We have improved the display of functional data and of ...
SummaryThis paper explores the structural continuum in CATH and the extent to which superfamilies ad...
The CATH domain database clusters closely related structures (>35% sequence identity) into families....
Deep-learning (DL) methods like DeepMind's AlphaFold2 (AF2) have led to substantial improvements in ...
CATH version 3.3 (class, architecture, topology, homology) contains 128,688 domains, 2386 homologous...
This article provides an update of the latest data and developments within the CATH protein structur...
The latest version of the CATH-Gene3D protein structure classification database (4.0, http://www.cat...
The CATH database of protein domain structures (http://www.biochem.ucl.ac.uk/bsm/cath_new) currently...
We report the latest release (version 3.0) of the CATH protein domain database (). There has been a ...
The latest version of CATH (class, architecture, topology, homology) (version 3.2), released in July...
The field of bioinformatics faces the challenge of reliably annotating genomic sequences with struct...
AbstractThis article presents a historical review of the protein structure classification database C...
Gene3D provides comprehensive structural and functional annotation of most available protein sequenc...
Gene3D provides comprehensive structural and functional annotation of most available protein sequenc...
Motivation: Computational approaches that can predict protein functions are essential to bridge the ...
CATH is a protein database of structural domains which are assigned to superfamilies through evidenc...
SummaryThis paper explores the structural continuum in CATH and the extent to which superfamilies ad...
The CATH domain database clusters closely related structures (>35% sequence identity) into families....
Deep-learning (DL) methods like DeepMind's AlphaFold2 (AF2) have led to substantial improvements in ...
CATH version 3.3 (class, architecture, topology, homology) contains 128,688 domains, 2386 homologous...
This article provides an update of the latest data and developments within the CATH protein structur...
The latest version of the CATH-Gene3D protein structure classification database (4.0, http://www.cat...
The CATH database of protein domain structures (http://www.biochem.ucl.ac.uk/bsm/cath_new) currently...
We report the latest release (version 3.0) of the CATH protein domain database (). There has been a ...
The latest version of CATH (class, architecture, topology, homology) (version 3.2), released in July...
The field of bioinformatics faces the challenge of reliably annotating genomic sequences with struct...
AbstractThis article presents a historical review of the protein structure classification database C...
Gene3D provides comprehensive structural and functional annotation of most available protein sequenc...
Gene3D provides comprehensive structural and functional annotation of most available protein sequenc...
Motivation: Computational approaches that can predict protein functions are essential to bridge the ...
CATH is a protein database of structural domains which are assigned to superfamilies through evidenc...
SummaryThis paper explores the structural continuum in CATH and the extent to which superfamilies ad...
The CATH domain database clusters closely related structures (>35% sequence identity) into families....
Deep-learning (DL) methods like DeepMind's AlphaFold2 (AF2) have led to substantial improvements in ...