ArticleNucleic acids research2014
SCOP2 prototype: a new approach to protein structure mining.
Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 162 papers, 1 of them a synthesis that pooled it.
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Who cites it
162 citing papers in PubMed, 1 synthesis or guideline pooled it, 338 citations in OpenAlex.
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- Advancements in one-dimensional protein structure prediction using machine learning and deep learning.Computational and structural biotechnology journal · 2025Review
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- Statistical analysis of sequential motifs at biologically relevant protein-protein interfaces.Computational and structural biotechnology journal · 2024Article
- Quantum chemical calculation dataset for representative protein folds by the fragment molecular orbital method.Scientific data · 2024Article
- Deep generative models of protein structure uncover distant relationships across a continuous fold space.Nature communications · 2024Article
- Teaching old docks new tricks with machine learning enhanced ensemble docking.Scientific reports · 2024Article
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102 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
We present a prototype of a new structural classification of proteins, SCOP2 (http://scop2.mrc-lmb.cam.ac.uk/), that we have developed recently. SCOP2 is a successor to the Structural Classification of Proteins (SCOP, http://scop.mrc-lmb.cam.ac.uk/scop/) database. Similarly to SCOP, the main focus of SCOP2 is to organize structurally characterized proteins according to their structural and evolutionary relationships. SCOP2 was designed to provide a more advanced framework for protein structure annotation and classification. It defines a new approach to the classification of proteins that is essentially different from SCOP, but retains its best features. The SCOP2 classification is described in terms of a directed acyclic graph in which nodes form a complex network of many-to-many relationships and are represented by a region of protein structure and sequence. The new classification project is expected to ensure new advances in the field and open new areas of research.
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