{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T16:25:48Z","timestamp":1787502348082,"version":"build-2736575974"},"reference-count":58,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2021,4,1]],"date-time":"2021-04-01T00:00:00Z","timestamp":1617235200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/R513295\/1"],"award-info":[{"award-number":["EP\/R513295\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/N014529\/1"],"award-info":[{"award-number":["EP\/N014529\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/R018472\/1"],"award-info":[{"award-number":["EP\/R018472\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,5,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Protein\u2013protein interactions are crucial in many biological pathways and facilitate cellular function. Investigating these interactions as a graph of pairwise interactions can help to gain a systemic understanding of cellular processes. It is known, however, that proteins interact with each other not exclusively in pairs but also in polyadic interactions and that they can form multiprotein complexes, which are stable interactions between multiple proteins. In this manuscript, we use hypergraphs to investigate multiprotein complex data. We investigate two random null models to test which hypergraph properties occur as a consequence of constraints, such as the size and the number of multiprotein complexes. We find that assortativity, the number of connected components, and clustering differ from the data to these null models. Our main finding is that projecting a hypergraph of polyadic interactions onto a graph of pairwise interactions leads to the identification of different proteins as hubs than the hypergraph. We find in our data set that the hypergraph degree is a more accurate predictor for gene essentiality than the degree in the pairwise graph. In our data set analysing a hypergraph as pairwise graph drastically changes the distribution of the local clustering coefficient. Furthermore, using a pairwise interaction representing multiprotein complex data may lead to a spurious hierarchical structure, which is not observed in the hypergraph. Hence, we illustrate that hypergraphs can be more suitable than pairwise graphs for the analysis of multiprotein complex data.<\/jats:p>","DOI":"10.1093\/comnet\/cnaa028","type":"journal-article","created":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T07:10:58Z","timestamp":1596265858000},"source":"Crossref","is-referenced-by-count":34,"title":["Hypergraphs for predicting essential genes using multiprotein complex data"],"prefix":"10.1093","volume":"9","author":[{"given":"Florian","family":"Klimm","sequence":"first","affiliation":[{"name":"Department of Mathematics, Imperial College London, London SW7 2AZ, UK and MRC Mitochondrial Biology Unit, University of Cambridge, Cambridge Biomedical Campus Hills Road, Cambridge CB2 0XY, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Charlotte M","family":"Deane","sequence":"additional","affiliation":[{"name":"Department of Statistics, University of Oxford, Oxford OX1 3LB, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gesine","family":"Reinert","sequence":"additional","affiliation":[{"name":"Department of Statistics, University of Oxford, Oxford OX1 3LB, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2021,5,5]]},"reference":[{"key":"2021070819455328200_B1","doi-asserted-by":"crossref","first-page":"200","DOI":"10.1002\/9781119970606.ch10","article-title":"Protein interaction networks and their statistical analysis","volume-title":"Handbook of Statistical Systems Biology","author":"Ali,","year":"2011"},{"key":"2021070819455328200_B2","doi-asserted-by":"crossref","first-page":"986","DOI":"10.1016\/j.cell.2011.02.016","article-title":"Interactome networks and human disease","volume":"144","author":"Vidal,","year":"2011","journal-title":"Cell"},{"key":"2021070819455328200_B3","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1002\/pmic.200500209","article-title":"Virtual identification of essential proteins within the protein interaction network of yeast","volume":"6","author":"Estrada,","year":"2006","journal-title":"Proteomics"},{"key":"2021070819455328200_B4","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pgen.0020088","article-title":"Why do hubs tend to be essential in protein networks?","volume":"2","author":"He,","year":"2006","journal-title":"PLoS Genet."},{"key":"2021070819455328200_B5","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1038\/35075138","article-title":"Lethality and centrality in protein networks","volume":"411","author":"Jeong,","year":"2001","journal-title":"Nature"},{"key":"2021070819455328200_B6","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1186\/s12918-018-0598-2","article-title":"A systematic survey of centrality measures for protein-protein interaction networks","volume":"12","author":"Ashtiani,","year":"2018","journal-title":"BMC Syst. 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