Author
Listed:
- Qiangfeng Cliff Zhang
(Howard Hughes Medical Institute, Columbia University
Columbia University
Center for Computational Biology and Bioinformatics, Columbia Initiative in Systems Biology, Columbia University)
- Donald Petrey
(Howard Hughes Medical Institute, Columbia University
Columbia University
Center for Computational Biology and Bioinformatics, Columbia Initiative in Systems Biology, Columbia University)
- Lei Deng
(Columbia University
Center for Computational Biology and Bioinformatics, Columbia Initiative in Systems Biology, Columbia University
Tongji University)
- Li Qiang
(Naomi Berrie Diabetes Center, College of Physicians & Surgeons of Columbia University)
- Yu Shi
(Molecular and Cell Biology Laboratory, The Salk Institute for Biological Studies)
- Chan Aye Thu
(Columbia University)
- Brygida Bisikirska
(Center for Computational Biology and Bioinformatics, Columbia Initiative in Systems Biology, Columbia University)
- Celine Lefebvre
(Center for Computational Biology and Bioinformatics, Columbia Initiative in Systems Biology, Columbia University
Institute of Cancer Genetics, Columbia University)
- Domenico Accili
(Naomi Berrie Diabetes Center, College of Physicians & Surgeons of Columbia University)
- Tony Hunter
(Molecular and Cell Biology Laboratory, The Salk Institute for Biological Studies)
- Tom Maniatis
(Columbia University)
- Andrea Califano
(Columbia University
Center for Computational Biology and Bioinformatics, Columbia Initiative in Systems Biology, Columbia University
Institute of Cancer Genetics, Columbia University
Columbia University)
- Barry Honig
(Howard Hughes Medical Institute, Columbia University
Columbia University
Center for Computational Biology and Bioinformatics, Columbia Initiative in Systems Biology, Columbia University)
Abstract
Protein–protein interactions, essential for understanding how a cell functions, are predicted using a new method that combines protein structure with other computationally and experimentally derived clues.
Suggested Citation
Qiangfeng Cliff Zhang & Donald Petrey & Lei Deng & Li Qiang & Yu Shi & Chan Aye Thu & Brygida Bisikirska & Celine Lefebvre & Domenico Accili & Tony Hunter & Tom Maniatis & Andrea Califano & Barry Honi, 2012.
"Structure-based prediction of protein–protein interactions on a genome-wide scale,"
Nature, Nature, vol. 490(7421), pages 556-560, October.
Handle:
RePEc:nat:nature:v:490:y:2012:i:7421:d:10.1038_nature11503
DOI: 10.1038/nature11503
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Citations
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Cited by:
- Patrick Bryant & Gabriele Pozzati & Arne Elofsson, 2022.
"Improved prediction of protein-protein interactions using AlphaFold2,"
Nature Communications, Nature, vol. 13(1), pages 1-11, December.
- Lucien F. Krapp & Luciano A. Abriata & Fabio Cortés Rodriguez & Matteo Dal Peraro, 2023.
"PeSTo: parameter-free geometric deep learning for accurate prediction of protein binding interfaces,"
Nature Communications, Nature, vol. 14(1), pages 1-11, December.
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