{"doi":"10.1101/2020.07.02.184325","title":"A computational exploration of resilience and evolvability of protein-protein interaction networks","abstract":"Abstract Protein-protein interaction (PPI) networks represent complex intra-cellular protein interactions, and the presence or absence of such interactions can lead to biological changes in an organism. Recent network-based approaches have shown that a phenotype’s PPI network’s resilience to environmental perturbations is related to its placement in the tree of life; though we still do not know how or why certain intra-cellular factors can bring about this resilience. Here, we explore the influence of gene expression and network properties on PPI networks’ resilience. We use publicly-available data of PPIs for E. coli, S. cerevisiae , and H. sapiens , where we compute changes in network resilience as new nodes (proteins) are added to the networks under three node addition mechanisms—random, degree-based, and gene-expression-based attachments. By calculating the resilience of the resulting networks, we estimate the effectiveness of these node addition mechanisms. We demonstrate that adding nodes with gene-expression-based preferential attachment (as opposed to random or degree-based) preserves and can increase the original resilience of PPI network in all three species, regardless of gene expression distribution or network structure. These findings introduce a general notion of prospective resilience , which highlights the key role of network structures in understanding the evolvability of phenotypic traits.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2020,"id":122877,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":4,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9514,"is_data_producer":false,"deposit_databanks":null,"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":564780,"name":"Ludvig Holmér","orcid":"0000-0003-1416-2222","position":1,"is_corresponding":false},{"id":428300,"name":"Keith Smith","orcid":"0000-0002-4615-9020","position":2,"is_corresponding":false},{"id":564781,"name":"Mackenzie M. Johnson","orcid":"0000-0002-3915-2023","position":3,"is_corresponding":false},{"id":564782,"name":"Anshuman Swain","orcid":"0000-0002-9180-2222","position":4,"is_corresponding":false},{"id":88339,"name":"Laura Stolp","orcid":null,"position":5,"is_corresponding":false},{"id":343916,"name":"A Teufel","orcid":"0000-0002-1076-0439","position":6,"is_corresponding":false},{"id":564783,"name":"April S. Kleppe","orcid":"0000-0001-7866-3056","position":7,"is_corresponding":false},{"id":555549,"name":"Brennan Klein","orcid":"0000-0001-8326-5044","position":0,"is_corresponding":true}],"reference_count":72,"raw_metadata":null,"created_at":"2026-07-18T23:14:55.385653Z","pmid":null,"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":[]}