{"doi":"10.1371/journal.pcbi.1008490","title":"Context-specific network modeling identifies new crosstalk in β-adrenergic cardiac hypertrophy","abstract":"Cardiac hypertrophy is a context-dependent phenomenon wherein a myriad of biochemical and biomechanical factors regulate myocardial growth through a complex large-scale signaling network. Although numerous studies have investigated hypertrophic signaling pathways, less is known about hypertrophy signaling as a whole network and how this network acts in a context-dependent manner. Here, we developed a systematic approach, CLASSED (Context-specific Logic-bASed Signaling nEtwork Development), to revise a large-scale signaling model based on context-specific data and identify main reactions and new crosstalks regulating context-specific response. CLASSED involves four sequential stages with an automated validation module as a core which builds a logic-based ODE model from the interaction graph and outputs the model validation percent. The context-specific model is developed by estimation of default parameters, classified qualitative validation, hybrid Morris-Sobol global sensitivity analysis, and discovery of missing context-dependent crosstalks. Applying this pipeline to our prior-knowledge hypertrophy network with context-specific data revealed key signaling reactions which distinctly regulate cell response to isoproterenol, phenylephrine, angiotensin II and stretch. Furthermore, with CLASSED we developed a context-specific model of β-adrenergic cardiac hypertrophy. The model predicted new crosstalks between calcium/calmodulin-dependent pathways and upstream signaling of Ras in the ISO-specific context. Experiments in cardiomyocytes validated the model's predictions on the role of CaMKII-Gβγ and CaN-Gβγ interactions in mediating hypertrophic signals in ISO-specific context and revealed a difference in the phosphorylation magnitude and translocation of ERK1/2 between cardiac myocytes and fibroblasts. CLASSED is a systematic approach for developing context-specific large-scale signaling networks, yielding insights into new-found crosstalks in β-adrenergic cardiac hypertrophy.","journal":"PLoS Computational Biology","year":2020,"id":100362,"datarank":0.668834090279523,"base_score":3.4011973816621555,"endowment":3.4011973816621555,"self_citation_contribution":0.5101796072493234,"citation_network_contribution":0.15865448303019955,"self_endowment_contribution":0.5101796072493234,"citer_contribution":0.15865448303019955,"corpus_percentile":null,"corpus_rank":null,"citation_count":29,"citer_count":7,"citers_with_citation_signal":5,"citers_with_endowment":5,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9432,"is_data_producer":true,"deposit_databanks":{"figshare":["10.6084/m9.figshare.12824162.v1"]},"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":492661,"name":"Alexander Paap","orcid":"0000-0001-8092-8105","position":1,"is_corresponding":false},{"id":492662,"name":"Steven L. Christiansen","orcid":"0000-0003-0168-4881","position":2,"is_corresponding":false},{"id":329730,"name":"Jeffrey J. Saucerman","orcid":"0000-0001-9464-8374","position":3,"is_corresponding":false},{"id":492660,"name":"Ali Khalilimeybodi","orcid":"0000-0001-9318-8433","position":0,"is_corresponding":true}],"reference_count":85,"raw_metadata":null,"created_at":"2026-07-18T22:38:35.493878Z","pmid":"33338038","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}