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Co-phosphorylation networks reveal subtype-specific signaling modules in breast cancer.

, , and . Bioinform., 37 (2): 221-228 (2021)

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What Do We Learn from Network-Based Analysis of Genome-Wide Association Data?, , and . EvoApplications, volume 8602 of Lecture Notes in Computer Science, page 865-876. Springer, (2014)CoPhosK: A Method for Comprehensive Kinase Substrate Annotation using Co-phosphorylation Analysis., , , , , , and . BCB, page 550. ACM, (2019)Assessing the collective disease association of multiple genomic loci., and . BCB, page 376-385. ACM, (2015)MoBaS on Phosphorylation Data., , , , , and . BCB, page 521. ACM, (2016)Deep Learning Model With Adaptive Regularization for EEG-Based Emotion Recognition Using Temporal and Frequency Features., , , and . IEEE Access, (2022)Co-phosphorylation networks reveal subtype-specific signaling modules in breast cancer., , and . Bioinform., 37 (2): 221-228 (2021)Functional characterization of co-phosphorylation networks., , , and . Bioinform., 38 (15): 3785-3793 (2022)PoCos: Population Covering Locus Sets for Risk Assessment in Complex Diseases., and . PLoS Comput. Biol., (2016)MOBAS: identification of disease-associated protein subnetworks using modularity-based scoring., , , and . EURASIP J. Bioinformatics and Systems Biology, (2015)Prioritization of genomic locus pairs for testing epistasis., and . BCB, page 240-248. ACM, (2014)