Title |
SCOWLP update: 3D classification of protein-protein, -peptide, -saccharide and -nucleic acid interactions, and structure-based binding inferences across folds
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Published in |
BMC Bioinformatics, October 2011
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DOI | 10.1186/1471-2105-12-398 |
Pubmed ID | |
Authors |
Joan Teyra, Sergey A Samsonov, Sven Schreiber, M Teresa Pisabarro |
Abstract |
Protein interactions are essential for coordinating cellular functions. Proteomic studies have already elucidated a huge amount of protein-protein interactions that require detailed functional analysis. Understanding the structural basis of each individual interaction through their structural determination is necessary, yet an unfeasible task. Therefore, computational tools able to predict protein binding regions and recognition modes are required to rationalize putative molecular functions for proteins. With this aim, we previously created SCOWLP, a structural classification of protein binding regions at protein family level, based on the information obtained from high-resolution 3D protein-protein and protein-peptide complexes. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Australia | 1 | 33% |
Unknown | 2 | 67% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 67% |
Scientists | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United Kingdom | 4 | 2% |
Germany | 2 | <1% |
Korea, Republic of | 1 | <1% |
Australia | 1 | <1% |
Netherlands | 1 | <1% |
Czechia | 1 | <1% |
Brazil | 1 | <1% |
Saudi Arabia | 1 | <1% |
United States | 1 | <1% |
Other | 0 | 0% |
Unknown | 190 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 42 | 21% |
Researcher | 37 | 18% |
Student > Master | 31 | 15% |
Student > Bachelor | 22 | 11% |
Student > Postgraduate | 8 | 4% |
Other | 27 | 13% |
Unknown | 36 | 18% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 55 | 27% |
Biochemistry, Genetics and Molecular Biology | 34 | 17% |
Computer Science | 27 | 13% |
Chemistry | 11 | 5% |
Engineering | 8 | 4% |
Other | 31 | 15% |
Unknown | 37 | 18% |