Network deconvolution as a general method to distinguish direct dependencies in networks
Recognizing direct relationships between variables connected in a network is a pervasive problem in biological, social and information sciences as correlation-based networks contain numerous indirect relationships. Here we present a general method for inferring direct effects from an observed correl...
Main Authors: | Feizi-Khankandi, Soheil, Marbach, Daniel, Medard, Muriel, Kellis, Manolis |
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Other Authors: | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
Format: | Article |
Language: | en_US |
Published: |
Nature Publishing Group
2014
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Online Access: | http://hdl.handle.net/1721.1/87073 https://orcid.org/0000-0002-0964-0616 https://orcid.org/0000-0003-4059-407X |
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