Computing Diverse Boolean Networks from Phosphoproteomic Time Series Data

Misbah Razzaq; Roland Kaminski; Javier Romero; Torsten Schaub; Jérémie Bourdon; Carito Guziołowski

doi:10.1007/978-3-319-99429-1_4

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Computing Diverse Boolean Networks from Phosphoproteomic Time Series Data

Misbah Razzaq Roland Kaminski Javier Romero Torsten Schaub Jérémie Bourdon Carito Guziołowski

Year: 2018 Lecture notes in computer science Pages: 59-74 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-319-99429-1_4

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Keywords:

Computer science Theoretical computer science Set (abstract data type) Benchmark (surveying) Series (stratigraphy) Answer set programming Artificial intelligence Logic programming Programming language Biology

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Logic, Reasoning, and Knowledge

Physical Sciences → Computer Science → Artificial Intelligence

Bayesian Modeling and Causal Inference

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Physical Sciences → Computer Science → Artificial Intelligence

Computing Diverse Boolean Networks from Phosphoproteomic Time Series Data

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