{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T19:56:13Z","timestamp":1757620573454,"version":"3.44.0"},"publisher-location":"Singapore","reference-count":22,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819506972"},{"type":"electronic","value":"9789819506989"}],"license":[{"start":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T00:00:00Z","timestamp":1754006400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T00:00:00Z","timestamp":1754006400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-981-95-0698-9_12","type":"book-chapter","created":{"date-parts":[[2025,7,31]],"date-time":"2025-07-31T07:27:41Z","timestamp":1753946861000},"page":"135-147","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Multi-task Learning with Cross-Stitch for Synergistic Effect of Drug Combination Prediction"],"prefix":"10.1007","author":[{"given":"Anqi","family":"Liang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiujuan","family":"Lei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ming","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Pan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,8,1]]},"reference":[{"issue":"6","key":"12_CR1","doi-asserted-by":"publisher","first-page":"bbab271","DOI":"10.1093\/bib\/bbab271","volume":"22","author":"K Fan","year":"2021","unstructured":"Fan, K., Cheng, L., Li, L.: Artificial intelligence and machine learning methods in predicting anti-cancer drug combination effects. Brief Bioinform. 22(6), bbab271 (2021)","journal-title":"Brief Bioinform."},{"key":"12_CR2","doi-asserted-by":"publisher","first-page":"5193","DOI":"10.1038\/srep05193","volume":"4","author":"B Yadav","year":"2014","unstructured":"Yadav, B., Pemovska, T., et al.: Quantitative scoring of differential drug sensitivity for individually optimized anticancer therapies. Sci. Rep. 4, 5193 (2014)","journal-title":"Sci. Rep."},{"issue":"2","key":"12_CR3","first-page":"43","volume":"1","author":"J Ma","year":"2019","unstructured":"Ma, J., Motsinger-Reif, A.: Current methods for quantifying drug synergism. Proteom. Bioinform. 1(2), 43\u201348 (2019)","journal-title":"Proteom. Bioinform."},{"issue":"1","key":"12_CR4","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1177\/108705719800300102","volume":"3","author":"J Major","year":"1998","unstructured":"Major, J.: Challenges and opportunities in high throughput screening: implications for new technologies. J. Biomol. Screen. 3(1), 13\u201317 (1998)","journal-title":"J. Biomol. Screen."},{"key":"12_CR5","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1016\/j.artmed.2017.05.008","volume":"83","author":"X Li","year":"2017","unstructured":"Li, X., Xu, Y., Cui, H., et al.: Prediction of synergistic anti-cancer drug combinations based on drug target network and drug induced gene expression profiles. Artif. Intell. Med. 83, 35\u201343 (2017)","journal-title":"Artif. Intell. Med."},{"issue":"1","key":"12_CR6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12859-019-3288-1","volume":"20","author":"H Liu","year":"2019","unstructured":"Liu, H., Zhang, W., Nie, L., et al.: Predicting effective drug combinations using gradient tree boosting based on features extracted from drug-protein heterogeneous network. BMC Bioinform. 20(1), 1\u201312 (2019)","journal-title":"BMC Bioinform."},{"issue":"2","key":"12_CR7","first-page":"59","volume":"12","author":"M Jeon","year":"2018","unstructured":"Jeon, M., Kim, S., Park, S., et al.: In silico drug combination discovery for personalized cancer therapy. BMC Syst. Biol. 12(2), 59\u201367 (2018)","journal-title":"BMC Syst. Biol."},{"issue":"9","key":"12_CR8","doi-asserted-by":"publisher","first-page":"1538","DOI":"10.1093\/bioinformatics\/btx806","volume":"34","author":"K Preuer","year":"2018","unstructured":"Preuer, K., Lewis, R.P., Hochreiter, S., et al.: DeepSynergy: predicting anti-cancer drug synergy with deep learning. Bioinformatics 34(9), 1538\u20131546 (2018)","journal-title":"Bioinformatics"},{"issue":"1","key":"12_CR9","doi-asserted-by":"publisher","first-page":"bbac503","DOI":"10.1093\/bib\/bbac503","volume":"24","author":"TH Li","year":"2023","unstructured":"Li, T.H., Wang, C.C., Zhang, L., Chen, X.: SNRMPACDC: computational model focused on Siamese network and random matrix projection for anticancer synergistic drug combination prediction. Brief Bioinform. 24(1), bbac503 (2023)","journal-title":"Brief Bioinform."},{"issue":"2","key":"12_CR10","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1109\/TCBB.2019.2919581","volume":"18","author":"M Li","year":"2021","unstructured":"Li, M., Wang, Y., Zheng, R., et al.: DeepDSC: a deep learning method to predict drug sensitivity of cancer cell lines. IEEE\/ACM Trans. Comput. Biol. Bioinform. 18(2), 575\u2013582 (2021)","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinform."},{"key":"12_CR11","doi-asserted-by":"publisher","first-page":"448","DOI":"10.1186\/s12859-023-05524-5","volume":"24","author":"D Chen","year":"2023","unstructured":"Chen, D., Wang, Z., et al.: Predicting anticancer synergistic drug combinations based on multi-task learning. BMC Bioinf. 24, 448 (2023)","journal-title":"BMC Bioinf."},{"issue":"2","key":"12_CR12","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1021\/c160017a018","volume":"5","author":"HL Morgan","year":"1965","unstructured":"Morgan, H.L.: The generation of a unique machine description for chemical structures: a technique developed at chemical abstracts service. J. Chem. Doc. 5(2), 107\u2013113 (1965)","journal-title":"J. Chem. Doc."},{"key":"12_CR13","doi-asserted-by":"crossref","unstructured":"Todeschini, R., Consonni, V.: Molecular descriptors for chemoinformatics. In: Methods and Principles in Medicinal Chemistry, vol. 2, pp. 1\u2013252. Wiley, New York (2009)","DOI":"10.1002\/9783527628766"},{"key":"12_CR14","doi-asserted-by":"crossref","unstructured":"Woo, S., Park, J., et al.: CBAM: convolutional block attention module. In: Ferrari V., Hebert M., Sminchisescu C., Weiss Y. (eds.): European Conference on Computer Vision (ECCV), LNCS, vol. 11211, pp. 3\u201319. Springer, Cham (2018)","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"12_CR15","doi-asserted-by":"crossref","unstructured":"Misra, I., Shrivastava, A., Gupta, A., et al.: Cross-stitch networks for multi-task learning. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3994\u20134003. IEEE Computer Society, Las Vegas (2016)","DOI":"10.1109\/CVPR.2016.433"},{"issue":"6","key":"12_CR16","doi-asserted-by":"publisher","first-page":"1155","DOI":"10.1158\/1535-7163.MCT-15-0843","volume":"15","author":"J O\u2019Neil","year":"2016","unstructured":"O\u2019Neil, J., Benita, Y., Feldman, I., et al.: An unbiased oncology compound screen to identify novel combination strategies. Mol. Cancer Ther. 15(6), 1155\u20131162 (2016)","journal-title":"Mol. Cancer Ther."},{"issue":"W1","key":"12_CR17","doi-asserted-by":"publisher","first-page":"W43","DOI":"10.1093\/nar\/gkz337","volume":"47","author":"B Zagidullin","year":"2019","unstructured":"Zagidullin, B., Aldahdooh, J., Zheng, S., et al.: DrugComb: an integrative cancer drug combination data portal. Nucleic Acids Res. 47(W1), W43-51 (2019)","journal-title":"Nucleic Acids Res."},{"issue":"1","key":"12_CR18","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1093\/jamia\/ocaa212","volume":"28","author":"Y Kim","year":"2021","unstructured":"Kim, Y., Zheng, S., Tang, J., et al.: Anticancer drug synergy prediction in understudied tissues using transfer learning. J. Am. Med. Inform. Assoc. 28(1), 42\u201351 (2021)","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"7391","key":"12_CR19","doi-asserted-by":"publisher","first-page":"603","DOI":"10.1038\/nature11003","volume":"483","author":"J Barretina","year":"2012","unstructured":"Barretina, J., Caponigro, G., Stransky, N., et al.: The cancer cell line encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature 483(7391), 603\u2013607 (2012)","journal-title":"Nature"},{"issue":"D1","key":"12_CR20","doi-asserted-by":"publisher","first-page":"D923","DOI":"10.1093\/nar\/gky872","volume":"47","author":"D van der Meer","year":"2019","unstructured":"van der Meer, D., Barthorpe, S., Yang, W., et al.: Cell model passports: a hub for clinical, genetic and functional datasets of preclinical cancer models. Nucleic Acids Res. 47(D1), D923\u2013D929 (2019)","journal-title":"Nucleic Acids Res."},{"issue":"6","key":"12_CR21","doi-asserted-by":"publisher","first-page":"1526","DOI":"10.23919\/cje.2023.00.344","volume":"33","author":"J Yang","year":"2024","unstructured":"Yang, J., Lei, X., Pan, Y.: Predicting circRNA-disease associations by using multi-biomolecular networks based on variational graph auto-encoder with attention mechanism. Chin. J. Electron. 33(6), 1526\u20131537 (2024)","journal-title":"Chin. J. Electron."},{"issue":"2","key":"12_CR22","doi-asserted-by":"publisher","first-page":"bbab587","DOI":"10.1093\/bib\/bbab587","volume":"23","author":"X Wang","year":"2022","unstructured":"Wang, X., Zhu, H., Jiang, Y., et al.: PRODeepSyn: predicting anticancer synergistic drug combinations by embedding cell lines with protein-protein interaction network. Brief Bioinform. 23(2), bbab587 (2022)","journal-title":"Brief Bioinform."}],"container-title":["Lecture Notes in Computer Science","Bioinformatics Research and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-0698-9_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,8]],"date-time":"2025-09-08T08:36:14Z","timestamp":1757320574000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-0698-9_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,1]]},"ISBN":["9789819506972","9789819506989"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-0698-9_12","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2025,8,1]]},"assertion":[{"value":"1 August 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ISBRA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Bioinformatics Research and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Helsinki","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Finland","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 August 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 August 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"isbra2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.helsinki.fi\/en\/conferences\/isbra2025","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}