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Open Access Highly Accessed Research article

HINT: High-quality protein interactomes and their applications in understanding human disease

Jishnu Das12 and Haiyuan Yu12*

Author Affiliations

1 Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853, USA

2 Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY 14853, USA

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BMC Systems Biology 2012, 6:92  doi:10.1186/1752-0509-6-92

Published: 30 July 2012

Additional files

Additional file 1:

Histogram of number of interactions reported by different studies focusing on detecting binary protein interactions in human and S. cerevisiae respectively.

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Additional file 2:

Binary and co-complex interaction networks in S. pombe.

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Additional file 3:

Binary protein-protein interactions in human – HT studies.

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Additional file 4:

Binary protein-protein interactions in S. cerevisiae – HT studies.

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Additional file 5:

Validation and retest rates for binary protein-protein interactions in human – HT studies.

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Additional file 6:

Validation and retest rates for binary protein-protein interactions in S. cerevisiae – HT studies.

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Additional file 7:

Example of an interaction from a small-scale study with low-quality supporting evidence.

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Additional file 8:

Overlaps between binary and co-complex interaction, HT and LC interaction networks in human and S. cerevisiae.

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Additional file 9:

Clustering coefficient and edge betweenness for binary and co-complex networks in human and S. cerevisiae.

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Additional file 10:

List of PSI-MI evidence codes used to classify binary interactions and co-complex associations.

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Additional file 11:

Mapping used to convert MIPS evidence codes to PSI-MI evidence codes.

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Additional file 12:

Mapping used to convert VisAnt evidence codes to PSI-MI evidence codes.

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Additional file 13:

Description of database-specific filtering techniques.

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