{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T10:12:01Z","timestamp":1767175921751,"version":"build-2238731810"},"update-to":[{"DOI":"10.1371\/journal.pcbi.1013547","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T00:00:00Z","timestamp":1759968000000}}],"reference-count":34,"publisher":"Public Library of Science (PLoS)","issue":"10","license":[{"start":{"date-parts":[[2025,10,3]],"date-time":"2025-10-03T00:00:00Z","timestamp":1759449600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"\n Using data from gene combination double knockout (CDKO) experiments, top ranked synthetic lethal (SL) gene pairs were highly inconsistent among different SL scores. This leads to a significant concern that SL prediction models highly depend on SL scores. In this paper, we introduce a new gene combination effect (GCE) measurement, log-fold change of dual-gRNA expression before and after CRISPR-cas9 lentivirus transfection. We show it is a direct and highly consistent measurement of GCE in all CDKO experiments. We therefore develop a multi-layer encoder model for individual sample specific GCE prediction, MLEC-iGeneCombo. Under a deep learning framework, MLEC-iGeneCombo is a systems biology model that contains sample specific multi-omics encoder, network encoder and cell-line encoder. For the first time, MLEC-iGeneCombo predicts GCE for a new cell. Using data from 18 CDKO experiments, MLEC-iGeneCombo achieves an average GCE prediction performance, 71.9%. All three encoders significantly improve the model\u2019s prediction performance (p\n \n \n \n \n \n \u2264<\/mml:mo>\n \n 0<\/mml:mtext>\n <\/mml:mrow>\n .<\/mml:mo>\n \n 0<\/mml:mtext>\n <\/mml:mrow>\n \n 1<\/mml:mtext>\n <\/mml:mrow>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:alternatives>\n <\/jats:inline-formula>\n ), and their combined use yields the best GCE prediction performance. Our source code is available at\n https:\/\/github.com\/karenyun\/MLEC-iGeneCombo<\/jats:ext-link>\n .\n <\/jats:p>","DOI":"10.1371\/journal.pcbi.1013547","type":"journal-article","created":{"date-parts":[[2025,10,3]],"date-time":"2025-10-03T17:36:37Z","timestamp":1759512997000},"page":"e1013547","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["A multi-layer encoder prediction model for individual sample specific gene combination effect 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selective and sensitive anticancer drug targets","volume":"44","author":"J Guo","year":"2016","journal-title":"Nucleic Acids Res"},{"key":"pcbi.1013547.ref018","doi-asserted-by":"crossref","first-page":"2022","DOI":"10.1093\/database\/baac030","article-title":"SynLethDB 2.0: a web-based knowledge graph database on synthetic lethality for novel anticancer drug discovery","volume":"2022","author":"J Wang","year":"2022","journal-title":"Database"},{"key":"pcbi.1013547.ref019","unstructured":"Kipf T, Welling M. Semi-supervised classification with graph convolutional networks. In: Proceedings of the 5th International Conference on Learning Representations, 2017."},{"issue":"16","key":"pcbi.1013547.ref020","doi-asserted-by":"crossref","first-page":"4458","DOI":"10.1093\/bioinformatics\/btaa211","article-title":"Dual-dropout graph convolutional network for predicting synthetic lethality in human cancers","volume":"36","author":"R Cai","year":"2020","journal-title":"Bioinformatics"},{"issue":"16","key":"pcbi.1013547.ref021","doi-asserted-by":"crossref","first-page":"2432","DOI":"10.1093\/bioinformatics\/btab110","article-title":"Graph contextualized attention network for predicting synthetic lethality in human cancers","volume":"37","author":"Y Long","year":"2021","journal-title":"Bioinformatics"},{"key":"pcbi.1013547.ref022","doi-asserted-by":"crossref","DOI":"10.1093\/bioinformatics\/btab271","article-title":"KG4SL: knowledge graph neural network for synthetic lethality prediction in human cancers","volume":"37","author":"S Wang","year":"2021","journal-title":"Bioinformatics"},{"key":"pcbi.1013547.ref023","article-title":"PiLSL: pairwise interaction learning-based graph neural network for synthetic lethality prediction in human cancers","volume":"38","author":"X Liu","year":"2022","journal-title":"Bioinformatics"},{"key":"pcbi.1013547.ref024","doi-asserted-by":"crossref","first-page":"1103092","DOI":"10.3389\/fgene.2022.1103092","article-title":"Multi-view graph convolutional network for cancer cell-specific synthetic lethality prediction","volume":"13","author":"K Fan","year":"2023","journal-title":"Front Genet"},{"issue":"5","key":"pcbi.1013547.ref025","article-title":"Synthetic lethal connectivity and graph transformer improve synthetic lethality prediction","volume":"25","author":"K Fan","year":"2024","journal-title":"Brief Bioinform"},{"issue":"7757","key":"pcbi.1013547.ref026","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1038\/s41586-019-1186-3","article-title":"Next-generation characterization of the Cancer Cell Line Encyclopedia","volume":"569","author":"M Ghandi","year":"2019","journal-title":"Nature"},{"issue":"12","key":"pcbi.1013547.ref027","doi-asserted-by":"crossref","first-page":"1779","DOI":"10.1038\/ng.3984","article-title":"Computational correction of copy number effect improves specificity of CRISPR-Cas9 essentiality screens in cancer cells","volume":"49","author":"RM Meyers","year":"2017","journal-title":"Nat Genet"},{"key":"pcbi.1013547.ref028","doi-asserted-by":"crossref","DOI":"10.1093\/nar\/gky1079","article-title":"BioGRID interaction database: 2019 update","volume":"47","author":"R Oughtred","year":"2019","journal-title":"Nucleic Acids Res"},{"key":"pcbi.1013547.ref029","unstructured":"Hamilton W, Ying R. Inductive representation learning on large graphs. In: Proceedings of the 31st International Conference on Neural Information Processing Systems, Long Beach, California, USA, 2017. 1025\u201335."},{"key":"pcbi.1013547.ref030","author":"M Fey","year":"2019"},{"key":"pcbi.1013547.ref031","unstructured":"Bengio Y, LeCun Y. Adam: A Method for Stochastic Optimization In: 3rd International Conference on Learning Representations. 2015."},{"issue":"6","key":"pcbi.1013547.ref032","doi-asserted-by":"crossref","first-page":"540","DOI":"10.1016\/j.cels.2016.10.017","article-title":"Compact integration of multi-network topology for functional analysis of genes","volume":"3","author":"H Cho","year":"2016","journal-title":"Cell Systems"},{"issue":"7","key":"pcbi.1013547.ref033","doi-asserted-by":"crossref","first-page":"2209","DOI":"10.1093\/bioinformatics\/btz893","article-title":"Predicting synthetic lethal interactions using heterogeneous data sources","volume":"36","author":"H Liany","year":"2020","journal-title":"Bioinformatics"},{"issue":"2","key":"pcbi.1013547.ref034","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1158\/2159-8290.CD-11-0224","article-title":"Essential gene profiles in breast, pancreatic, and ovarian cancer cells","volume":"2","author":"R Marcotte","year":"2012","journal-title":"Cancer Discov"}],"updated-by":[{"DOI":"10.1371\/journal.pcbi.1013547","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T00:00:00Z","timestamp":1759968000000}}],"container-title":["PLOS Computational Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1013547","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T18:13:44Z","timestamp":1760033624000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1013547"}},"subtitle":[],"editor":[{"given":"Daifeng","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2025,10,3]]},"references-count":34,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2025,10,3]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pcbi.1013547","relation":{},"ISSN":["1553-7358"],"issn-type":[{"value":"1553-7358","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,3]]}}}