{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T20:01:39Z","timestamp":1742932899147,"version":"3.40.3"},"publisher-location":"Cham","reference-count":16,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031231971"},{"type":"electronic","value":"9783031231988"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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":[[2022]]},"DOI":"10.1007\/978-3-031-23198-8_1","type":"book-chapter","created":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T02:36:12Z","timestamp":1672540572000},"page":"1-8","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["MLMVFE: A Machine Learning Approach Based on Muli-view Features Extraction for Drug-Disease Associations Prediction"],"prefix":"10.1007","author":[{"given":"Ying","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ying-Lian","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junliang","family":"Shang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jin-Xing","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,1,1]]},"reference":[{"key":"1_CR1","doi-asserted-by":"publisher","first-page":"801","DOI":"10.1016\/j.tips.2019.07.013","volume":"40","author":"HCS Chan","year":"2019","unstructured":"Chan, H.C.S., Shan, H.B., Dahoun, T., et al.: Advancing drug discovery via artificial intelligence. Trends. Pharmacol. Sci. 40, 801 (2019). https:\/\/doi.org\/10.1016\/j.tips.2019.07.013","journal-title":"Trends. Pharmacol. Sci."},{"doi-asserted-by":"publisher","unstructured":"Yang, M.Y., Wu, G.Y., Zhao, Q.C., et al.: Computational drug repositioning based on multi-similarities bilinear matrix factorization. Brief. Bioinform. 22, bbaa267 (2021). https:\/\/doi.org\/10.1093\/bib\/bbaa267","key":"1_CR2","DOI":"10.1093\/bib\/bbaa267"},{"key":"1_CR3","doi-asserted-by":"publisher","first-page":"451","DOI":"10.1093\/bib\/bbz15","volume":"22","author":"YY Chu","year":"2021","unstructured":"Chu, Y.Y., Kaushik, A.C., Wang, X.G., et al.: DTI-CDF: a cascade deep forest model towards the prediction of drug-target interactions based on hybrid features. Brief. Bioinform. 22, 451\u2013462 (2021). https:\/\/doi.org\/10.1093\/bib\/bbz15","journal-title":"Brief. Bioinform."},{"key":"1_CR4","doi-asserted-by":"publisher","first-page":"2115","DOI":"10.1109\/TKDE.2019.2914200","volume":"32","author":"L Hu","year":"2020","unstructured":"Hu, L., Chan, K.C.C., Yuan, X.H., et al.: A variational bayesian framework for cluster analysis in a complex network. IEEE Trans. Knowl. Data. Eng. 32, 2115\u20132128 (2020). https:\/\/doi.org\/10.1109\/TKDE.2019.2914200","journal-title":"IEEE Trans. Knowl. Data. Eng."},{"key":"1_CR5","doi-asserted-by":"publisher","first-page":"542","DOI":"10.1093\/bioinformatics\/btaa775","volume":"37","author":"L Hu","year":"2021","unstructured":"Hu, L., Zhang, J., Pan, X.Y., et al.: HiSCF: leveraging higher-order structures for clustering analysis in biological networks. Bioinformatics 37, 542\u2013550 (2021). https:\/\/doi.org\/10.1093\/bioinformatics\/btaa775","journal-title":"Bioinformatics"},{"key":"1_CR6","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1016\/j.cbi.2017.12.003","volume":"280","author":"N Aztopal","year":"2018","unstructured":"Aztopal, N., Erkisa, M., Erturk, E., et al.: Valproic acid, a histone deacetylase inhibitor, induces apoptosis in breast cancer stem cells. Chem. -Biol. Interact. 280, 51\u201358 (2018). https:\/\/doi.org\/10.1016\/j.cbi.2017.12.003","journal-title":"Chem. -Biol. Interact."},{"key":"1_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2020.103624","volume":"112","author":"GH Li","year":"2020","unstructured":"Li, G.H., Luo, J.W., Wang, D.C., et al.: Potential circRNA-disease association prediction using DeepWalk and network consistency projection. J. Biomed. Inform. 112, 103624 (2020). https:\/\/doi.org\/10.1016\/j.jbi.2020.103624","journal-title":"J. Biomed. Inform."},{"key":"1_CR8","doi-asserted-by":"publisher","first-page":"153","DOI":"10.3847\/1538-3881\/ac4d97","volume":"163","author":"JC Liang","year":"2022","unstructured":"Liang, J.C., Bu, Y.D., Tan, K.F., et al.: Estimation of stellar atmospheric parameters with light gradient boosting machine algorithm and principal component analysis. Astron. J. 163, 153 (2022). https:\/\/doi.org\/10.3847\/1538-3881\/ac4d97","journal-title":"Astron. J."},{"key":"1_CR9","doi-asserted-by":"publisher","first-page":"D948","DOI":"10.1093\/nar\/gky868","volume":"47","author":"AP Davis","year":"2019","unstructured":"Davis, A.P., Grondin, C.J., Johnson, R.J., et al.: The comparative toxicogenomics database: update 2019. Nucleic. Acids. Res. 47, D948\u2013D954 (2019). https:\/\/doi.org\/10.1093\/nar\/gky868","journal-title":"Nucleic. Acids. Res."},{"doi-asserted-by":"publisher","unstructured":"DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic. Acids. Res. 46, D1074-D1082 (2017). https:\/\/doi.org\/10.1093\/nar\/gkx1037","key":"1_CR10","DOI":"10.1093\/nar\/gkx1037"},{"key":"1_CR11","doi-asserted-by":"publisher","first-page":"D833","DOI":"10.1093\/nar\/gkw943","volume":"45","author":"J Pinero","year":"2017","unstructured":"Pinero, J., Bravo, A., Queralt-Rosinach, N., et al.: DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants. Nucleic. Acids. Res. 45, D833\u2013D839 (2017). https:\/\/doi.org\/10.1093\/nar\/gkw943","journal-title":"Nucleic. Acids. Res."},{"doi-asserted-by":"publisher","unstructured":"Huang, L., Luo, H.M., Li, S.N., et al.: Drug-drug similarity measure and its applications. Brief. Bioinform. 22, bbaa265 (2021). https:\/\/doi.org\/10.1093\/bib\/bbaa265","key":"1_CR12","DOI":"10.1093\/bib\/bbaa265"},{"key":"1_CR13","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1016\/j.ejmech.2013.05.031","volume":"67","author":"K Nesmerak","year":"2013","unstructured":"Nesmerak, K., Toropov, A.A., Toropova, A.P., et al.: SMILES-based quantitative structure-property relationships for half-wave potential of N-benzylsalicylthioamides. Eur. J. Med. Chem. 67, 111\u2013114 (2013). https:\/\/doi.org\/10.1016\/j.ejmech.2013.05.031","journal-title":"Eur. J. Med. Chem."},{"doi-asserted-by":"crossref","unstructured":"Yan, S.H., Yang, A.M., Kong, S.S. et al.: Predictive intelligence powered attentional stacking matrix factorization algorithm for the computational drug repositioning. Appl. Soft. Comput. 110, 107633 (2021).","key":"1_CR14","DOI":"10.1016\/j.asoc.2021.107633"},{"key":"1_CR15","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1007\/BF03256196","volume":"21","author":"B Warner","year":"2002","unstructured":"Warner, B., Hoffmann, P.: Investigation of the potential of clozapine to cause torsade de pointes. Adverse. Drug. React. Toxicol. Rev. 21, 189\u2013203 (2002)","journal-title":"Adverse. Drug. React. Toxicol. Rev."},{"key":"1_CR16","doi-asserted-by":"publisher","first-page":"469","DOI":"10.1111\/pcn.12435","volume":"70","author":"M Fujimoto","year":"2016","unstructured":"Fujimoto, M., Hashimoto, R., Yamamori, H., et al.: Clozapine improved the syndrome of inappropriate antidiuretic hormone secretion in a patient with treatment-resistant schizophrenia. Psychiat. Clin. Neuros. 70, 469 (2016). https:\/\/doi.org\/10.1111\/pcn.12435","journal-title":"Psychiat. Clin. Neuros."}],"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\/978-3-031-23198-8_1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,18]],"date-time":"2023-07-18T18:03:06Z","timestamp":1689703386000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-23198-8_1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031231971","9783031231988"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-23198-8_1","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"1 January 2023","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":"Haifa","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Israel","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 November 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 November 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"isbra2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/mangul-lab-usc.github.io\/ISBRA","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"72","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"30","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"42% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}