{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T15:32:23Z","timestamp":1772119943885,"version":"3.50.1"},"reference-count":55,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2021,3,31]],"date-time":"2021-03-31T00:00:00Z","timestamp":1617148800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,3,31]],"date-time":"2021-03-31T00:00:00Z","timestamp":1617148800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J. Comput. Sci. Technol."],"published-print":{"date-parts":[[2021,4]]},"DOI":"10.1007\/s11390-021-0866-2","type":"journal-article","created":{"date-parts":[[2021,4,14]],"date-time":"2021-04-14T06:03:22Z","timestamp":1618380202000},"page":"261-275","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Synthetic Lethal Interactions Prediction Based on Multiple Similarity Measures Fusion"],"prefix":"10.1007","volume":"36","author":[{"given":"Lian-Lian","family":"Wu","sequence":"first","affiliation":[]},{"given":"Yu-Qi","family":"Wen","sequence":"additional","affiliation":[]},{"given":"Xiao-Xi","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Bo-Wei","family":"Yan","sequence":"additional","affiliation":[]},{"given":"Song","family":"He","sequence":"additional","affiliation":[]},{"given":"Xiao-Chen","family":"Bo","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,3,31]]},"reference":[{"issue":"5340","key":"866_CR1","doi-asserted-by":"publisher","first-page":"1064","DOI":"10.1126\/science.278.5340.1064","volume":"278","author":"LH Hartwell","year":"1997","unstructured":"Hartwell L H, Szankasi P, Roberts C J et al. Integrating genetic approaches into the discovery of anticancer drugs. Science, 1997, 278(5340): 1064-1068. https:\/\/doi.org\/10.1126\/science.278.5340.1064.","journal-title":"Science"},{"issue":"6","key":"866_CR2","doi-asserted-by":"publisher","first-page":"437","DOI":"10.1038\/nrg2085","volume":"8","author":"C Boone","year":"2007","unstructured":"Boone C, Bussey H, Andrews B J. Exploring genetic interactions and networks with yeast. Nature Reviews Genetics, 2007, 8(6): 437-449. https:\/\/doi.org\/10.1038\/nrg2085.","journal-title":"Nature Reviews Genetics"},{"issue":"5","key":"866_CR3","doi-asserted-by":"publisher","first-page":"351","DOI":"10.1038\/nrd3374","volume":"10","author":"DA Chan","year":"2011","unstructured":"Chan D A, Giaccia A J. Harnessing synthetic lethal interactions in anticancer drug discovery. Nature Reviews Drug Discovery, 2011, 10(5): 351-364. https:\/\/doi.org\/10.1038\/nrd3374.","journal-title":"Nature Reviews Drug Discovery"},{"key":"866_CR4","doi-asserted-by":"publisher","unstructured":"Deng X, Das S, Valdez K et al. SL-BioDP: Multi-cancer interactive tool for prediction of synthetic lethality and response to cancer treatment. Cancers (Basel), 2019, 11(11): Article No. 1682. https:\/\/doi.org\/10.3390\/cancers11111682.","DOI":"10.3390\/cancers11111682"},{"issue":"18","key":"866_CR5","doi-asserted-by":"publisher","first-page":"1725","DOI":"10.1056\/NEJMra1407390","volume":"371","author":"DP McLornan","year":"2014","unstructured":"McLornan D P, List A, Mufti G J. Applying synthetic lethality for the selective targeting of cancer. New England Journal of Medicine, 2014, 371(18): 1725-1735. https:\/\/doi.org\/10.1056\/NEJMra1407390.","journal-title":"New England Journal of Medicine"},{"issue":"7035","key":"866_CR6","doi-asserted-by":"publisher","first-page":"913","DOI":"10.1038\/nature03443","volume":"434","author":"HE Bryant","year":"2007","unstructured":"Bryant H E, Schultz N, Thomas H D et al. Specific killing of BRCA2-deficient tumours with inhibitors of poly(ADP-ribose) polymerase. Nature, 2007, 434(7035): 913-917. https:\/\/doi.org\/10.1038\/nature03443.","journal-title":"Nature"},{"key":"866_CR7","doi-asserted-by":"publisher","unstructured":"Downward J. Targeting RAS signalling pathways in cancer therapy. Nature Reviews Cancer, 2003, 3(1): 11-22. https:\/\/doi.org\/10.1038\/nrc969.","DOI":"10.1038\/nrc969"},{"issue":"2","key":"866_CR8","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1056\/NEJMoa0900212","volume":"361","author":"PC Fong","year":"2009","unstructured":"Fong P C, Boss D S, Yap T A et al. Inhibition of poly(ADP-ribose) polymerase in tumors from BRCA mutation carriers. New England Journal of Medicine, 2009, 361(2): 123-134. https:\/\/doi.org\/10.1056\/NEJMoa0900212.","journal-title":"New England Journal of Medicine"},{"issue":"7267","key":"866_CR9","doi-asserted-by":"publisher","first-page":"1071","DOI":"10.1038\/nature08467","volume":"461","author":"SP Jackson","year":"2009","unstructured":"Jackson S P, Bartek J. The DNA-damage response in human biology and disease. Nature, 2009, 461(7267): 1071-1078. https:\/\/doi.org\/10.1038\/nature08467.","journal-title":"Nature"},{"key":"866_CR10","doi-asserted-by":"publisher","unstructured":"Lee J S, Das A, Auslander N et al. Harnessing synthetic lethality to predict the response to cancer treatment. Nature Communications, 2018, 9(1): Article No. 2546. https:\/\/doi.org\/10.1038\/s41467-018-04647-1.","DOI":"10.1038\/s41467-018-04647-1"},{"issue":"2","key":"866_CR11","doi-asserted-by":"publisher","first-page":"266","DOI":"10.1101\/gr.154201","volume":"11","author":"A Simons","year":"2001","unstructured":"Simons A, Dafni N, Dotan I. Establishment of a chemical synthetic lethality screen in cultured human cells. Genome Research, 2001, 11(2): 266-273. https:\/\/doi.org\/10.1101\/gr.154201.","journal-title":"Genome Research"},{"issue":"7269","key":"866_CR12","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1038\/nature08460","volume":"462","author":"DA Barbie","year":"2009","unstructured":"Barbie D A, Tamayo P, Boehm J S et al. Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1. Nature, 2009, 462(7269): 108-112. https:\/\/doi.org\/10.1038\/nature08460.","journal-title":"Nature"},{"issue":"8","key":"866_CR13","doi-asserted-by":"publisher","first-page":"1227","DOI":"10.1038\/cr.2012.82","volume":"22","author":"M Steckel","year":"2012","unstructured":"Steckel M, Molina-Arcas M, Weigelt B et al. Determination of synthetic lethal interactions in KRAS oncogene-dependent cancer cells reveals novel therapeutic targeting strategies. Cell Research, 2012, 22(8): 1227-1245. https:\/\/doi.org\/10.1038\/cr.2012.82.","journal-title":"Cell Research"},{"issue":"5","key":"866_CR14","doi-asserted-by":"publisher","first-page":"463","DOI":"10.1038\/nbt.3834","volume":"35","author":"K Han","year":"2017","unstructured":"Han K, Jeng E E, Hess G T et al. Synergistic drug combinations for cancer identified in a CRISPR screen for pairwise genetic interactions. Nature Biotechnology, 2017, 35(5): 463-474. https:\/\/doi.org\/10.1038\/nbt.3834.","journal-title":"Nature Biotechnology"},{"issue":"6","key":"866_CR15","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1038\/nmeth.4286","volume":"14","author":"D Du","year":"2017","unstructured":"Du D, Roguev A, Gordon D E et al. Genetic interaction mapping in mammalian cells using CRISPR interference. Nature Methods, 2017, 14(6): 577-580. https:\/\/doi.org\/10.1038\/nmeth.4286.","journal-title":"Nature Methods"},{"key":"866_CR16","doi-asserted-by":"publisher","unstructured":"Bleicher K H, B\u00f6hm H J, M\u00fcller K et al. Hit and lead generation: Beyond high-throughput screening. Nature Reviews Drug Discovery, 2003, 2(5): 369-378. https:\/\/doi.org\/10.1038\/nrd1086.","DOI":"10.1038\/nrd1086"},{"issue":"11","key":"866_CR17","doi-asserted-by":"publisher","first-page":"882","DOI":"10.1038\/nrd941","volume":"1","author":"J Bajorath","year":"2002","unstructured":"Bajorath J. Integration of virtual and high-throughput screening. Nature Reviews Drug Discovery, 2002, 1(11): 882-894. https:\/\/doi.org\/10.1038\/nrd941.","journal-title":"Nature Reviews Drug Discovery"},{"key":"866_CR18","doi-asserted-by":"publisher","unstructured":"Guo J, Liu H, Zheng J. SynLethDB: Synthetic lethality database toward discovery of selective and sensitive anticancer drug targets. Nucleic Acids Res., 2016, 44(D1): D1011-D1017. https:\/\/doi.org\/10.1093\/nar\/gkv1108.","DOI":"10.1093\/nar\/gkv1108"},{"key":"866_CR19","doi-asserted-by":"publisher","unstructured":"Lu X, Kensche P R, Huynen M A et al. Genome evolution predicts genetic interactions in protein complexes and reveals cancer drug targets. Nature Communications, 2013, 4: Article No. 2124. https:\/\/doi.org\/10.1038\/ncomms3124.","DOI":"10.1038\/ncomms3124"},{"issue":"3","key":"866_CR20","doi-asserted-by":"publisher","first-page":"514","DOI":"10.1016\/j.molcel.2016.06.022","volume":"63","author":"R Srivas","year":"2016","unstructured":"Srivas R, Shen J P, Yang C C et al. A network of conserved synthetic lethal interactions for exploration of precision cancer therapy. Molecular Cell, 2016, 63(3): 514-525. https:\/\/doi.org\/10.1016\/j.molcel.2016.06.022.","journal-title":"Molecular Cell"},{"issue":"5","key":"866_CR21","doi-asserted-by":"publisher","first-page":"539","DOI":"10.1038\/nbt.3527","volume":"34","author":"JW Kim","year":"2016","unstructured":"Kim J W, Botvinnik O B, Abudayyeh O et al. Characterizing genomic alterations in cancer by complementary functional associations. Nature Biotechnology, 2016, 34(5): 539-546. https:\/\/doi.org\/10.1038\/nbt.3527.","journal-title":"Nature Biotechnology"},{"issue":"6","key":"866_CR22","doi-asserted-by":"publisher","first-page":"540","DOI":"10.1016\/j.cels.2016.10.017","volume":"3","author":"H Cho","year":"2016","unstructured":"Cho H, Berger B, Peng J. Compact integration of multi-network topology for functional analysis of genes. Cell Systems, 2016, 3(6): 540-548. https:\/\/doi.org\/10.1016\/j.cels.2016.10.017.","journal-title":"Cell Systems"},{"issue":"5","key":"866_CR23","doi-asserted-by":"publisher","first-page":"1199","DOI":"10.1016\/j.cell.2014.07.027","volume":"158","author":"L Jerby-Arnon","year":"2014","unstructured":"Jerby-Arnon L, Pfetzer N, Waldman Y et al. Predicting cancer-specific vulnerability via data-driven detection of synthetic lethality. Cell, 2014, 158(5): 1199-1209. https:\/\/doi.org\/10.1016\/j.cell.2014.07.027.","journal-title":"Cell"},{"key":"866_CR24","doi-asserted-by":"publisher","unstructured":"Wan F, Li S, Tian T et al. EXP2SL: A machine learning framework for cell-line-specific synthetic lethality prediction. Frontiers in Pharmacology, 2020, 11: Article No. 112. https:\/\/doi.org\/10.3389\/fphar.2020.00112.","DOI":"10.3389\/fphar.2020.00112"},{"issue":"7","key":"866_CR25","doi-asserted-by":"publisher","first-page":"2209","DOI":"10.1093\/bioinformatics\/btz893","volume":"36","author":"H Liany","year":"2020","unstructured":"Liany H, Jeyasekharan A, Rajan V. Predicting synthetic lethal interactions using heterogeneous data sources. Bioinformatics, 2020, 36(7): 2209-2216. https:\/\/doi.org\/10.1093\/bioinformatics\/btz893.","journal-title":"Bioinformatics"},{"issue":"12","key":"866_CR26","doi-asserted-by":"publisher","first-page":"2007","DOI":"10.1093\/bioinformatics\/btv080","volume":"31","author":"P Li","year":"2015","unstructured":"Li P, Huang C, Fu Y et al. Large-scale exploration and analysis of drug combinations. Bioinformatics, 2015, 31(12): 2007-2016. https:\/\/doi.org\/10.1093\/bioinformatics\/btv080.","journal-title":"Bioinformatics"},{"key":"866_CR27","doi-asserted-by":"publisher","unstructured":"Menche J, Sharma A, Kitsak M et al. Uncovering disease-disease relationships through the incomplete interactome. Science, 2015, 347(6224): Article No. 1257601. https:\/\/doi.org\/10.1126\/science.1257601.","DOI":"10.1126\/science.1257601"},{"key":"866_CR28","doi-asserted-by":"publisher","unstructured":"Duan Q, Flynn C, Niepel M et al. LINCS Canvas Browser: Interactive web app to query, browse and interrogate LINCS L1000 gene expression signatures. Nucleic Acids Research, 2014, 42(W1): W449-W460. https:\/\/doi.org\/10.1093\/nar\/gku476.","DOI":"10.1093\/nar\/gku476"},{"key":"866_CR29","doi-asserted-by":"publisher","unstructured":"The UniProt Consortium. UniProt: A hub for protein information. Nucleic Acids Research, 2015, 43(D1): D204-D212. https:\/\/doi.org\/10.1093\/nar\/gku989.","DOI":"10.1093\/nar\/gku989"},{"issue":"D1","key":"866_CR30","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 Research, 2019, 47(D1): D948-D954. https:\/\/doi.org\/10.1093\/nar\/gky868.","journal-title":"Nucleic Acids Research"},{"key":"866_CR31","doi-asserted-by":"publisher","unstructured":"Subramanian A, Tamayo P, Mootha V K et al. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences of the United States of America, 2005, 102(43): 15545-15550. https:\/\/doi.org\/10.1073\/pnas.0506580102.","DOI":"10.1073\/pnas.0506580102"},{"issue":"2","key":"866_CR32","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1089\/cmb.2008.10TT","volume":"16","author":"F Iorio","year":"2009","unstructured":"Iorio F, Tagliaferri R, Di Bernardo D. Identifying network of drug mode of action by gene expression profiling. Journal of Computational Biology, 2009, 16(2): 241-251. https:\/\/doi.org\/10.1089\/cmb.2008.10TT.","journal-title":"Journal of Computational Biology"},{"key":"866_CR33","doi-asserted-by":"publisher","unstructured":"Smith T F, Waterman M S. Identification of common molecular subsequences. Journal of Molecular Biology, 1981, 147(1): 195-197. https:\/\/doi.org\/10.1016\/0022-2836(81)90087-5.","DOI":"10.1016\/0022-2836(81)90087-5"},{"issue":"2","key":"866_CR34","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1089\/cmb.2010.0213","volume":"18","author":"L Perlman","year":"2011","unstructured":"Perlman L, Gottlieb A, Atias N et al. Combining drug and gene similarity measures for drug-target elucidation. Journal of Computational Biology, 2011, 18(2): 133-145. https:\/\/doi.org\/10.1089\/cmb.2010.0213.","journal-title":"Journal of Computational Biology"},{"issue":"7","key":"866_CR35","doi-asserted-by":"publisher","first-page":"976","DOI":"10.1093\/bioinformatics\/btq064","volume":"26","author":"G Yu","year":"2010","unstructured":"Yu G, Li F, Qin Y et al. GOSemSim: An R package for measuring semantic similarity among GO terms and gene products. Bioinformatics, 2010, 26(7): 976-978. https:\/\/doi.org\/10.1093\/bioinformatics\/btq064.","journal-title":"Bioinformatics"},{"issue":"10","key":"866_CR36","doi-asserted-by":"publisher","first-page":"1274","DOI":"10.1093\/bioinformatics\/btm087","volume":"23","author":"JZ Wang","year":"2007","unstructured":"Wang J Z, Du Z, Payattakool R et al. A new method to measure the semantic similarity of GO terms. Bioinformatics, 2007, 23(10): 1274-1281. https:\/\/doi.org\/10.1093\/bioinformatics\/btm087.","journal-title":"Bioinformatics"},{"issue":"3","key":"866_CR37","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1038\/nmeth.2810","volume":"11","author":"B Wang","year":"2014","unstructured":"Wang B, Mezlini A, Demir F et al. Similarity network fusion for aggregating data types on a genomic scale. Nature Methods, 2014, 11(3): 333-337. https:\/\/doi.org\/10.1038\/nmeth.2810.","journal-title":"Nature Methods"},{"issue":"3","key":"866_CR38","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1080\/00031305.1992.10475879","volume":"46","author":"NS Altman","year":"1992","unstructured":"Altman N S. An introduction to kernel and nearest-neighbor nonparametric regression. The American Statistician, 1992, 46(3): 175-185. https:\/\/doi.org\/10.1080\/00031305.1992.10475879.","journal-title":"The American Statistician"},{"key":"866_CR39","doi-asserted-by":"publisher","unstructured":"He S, He H, Xu W. ICM: A web server for integrated clustering of multi-dimensional biomedical data. Nucleic Acids Research, 2016, 44(W1): W154-W159. https:\/\/doi.org\/10.1093\/nar\/gkw378.","DOI":"10.1093\/nar\/gkw378"},{"issue":"4","key":"866_CR40","doi-asserted-by":"publisher","first-page":"929","DOI":"10.1016\/j.cell.2014.06.049","volume":"158","author":"KA Hoadley","year":"2014","unstructured":"Hoadley K A, Yau C, Wolf D M et al. Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin. Cell, 2014, 158(4): 929-944. https:\/\/doi.org\/10.1016\/j.cell.2014.06.049.","journal-title":"Cell"},{"key":"866_CR41","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1016\/j.ymeth.2018.05.020","volume":"145","author":"T Ma","year":"2018","unstructured":"Ma T, Zhang A. Affinity network fusion and semi-supervised learning for cancer patient clustering. Methods, 2018, 145: 16-24. https:\/\/doi.org\/10.1016\/j.ymeth.2018.05.020.","journal-title":"Methods"},{"issue":"3","key":"866_CR42","doi-asserted-by":"publisher","first-page":"611","DOI":"10.1111\/1467-9868.00196","volume":"21","author":"ME Tipping","year":"1999","unstructured":"Tipping M E, Bishop C M. Probabilistic principal component analysis. Journal of the Royal Statistical Society, Series B, 1999, 21(3): 611-622. https:\/\/doi.org\/10.1111\/1467-9868.00196.","journal-title":"Journal of the Royal Statistical Society, Series B"},{"key":"866_CR43","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa F, Varoquaux G, Gramfort A et al. Scikit-learn: Machine learning in Python. Journal of Machine learning Research, 2011, 12: 2825-2830.","journal-title":"Journal of Machine learning Research"},{"issue":"8","key":"866_CR44","doi-asserted-by":"publisher","first-page":"533","DOI":"10.1038\/s41573-020-0068-6","volume":"19","author":"AR Moore","year":"2020","unstructured":"Moore A R, Rosenberg S C, McCormick F et al. RAS-targeted therapies: Is the undruggable drugged? Nature Reviews Drug Discovery, 2020, 19(8): 533-552. https:\/\/doi.org\/10.1038\/s41573-020-0068-6.","journal-title":"Nature Reviews Drug Discovery"},{"key":"866_CR45","doi-asserted-by":"publisher","unstructured":"Wishart D S, Feunang Y D, Guo A C et al. DrugBank 5.0: A major update to the DrugBank database for 2018. Nucleic Acids Research, 2018, 46(D1): D1074-D1082. https:\/\/doi.org\/10.1093\/nar\/gkx1037.","DOI":"10.1093\/nar\/gkx1037"},{"key":"866_CR46","doi-asserted-by":"publisher","unstructured":"Costa-Cabral S, Brough R, Konde A et al. CDK1 is a synthetic lethal target for KRAS mutant tumours. PLoS ONE, 2016, 11(2): Article No. e0149099. https:\/\/doi.org\/10.1371\/journal.pone.0149099.","DOI":"10.1371\/journal.pone.0149099"},{"issue":"6","key":"866_CR47","doi-asserted-by":"publisher","first-page":"1075","DOI":"10.1038\/bjc.1994.451","volume":"70","author":"JL Grem","year":"1994","unstructured":"Grem J L, Voeller D M, Geoffroy F et al. Determinants of trimetrexate lethality in human colon cancer cells. British Journal of Cancer, 1994, 70(6): 1075-1084. https:\/\/doi.org\/10.1038\/bjc.1994.451.","journal-title":"British Journal of Cancer"},{"key":"866_CR48","doi-asserted-by":"publisher","unstructured":"Raimondi M V, Randazzo O, La Franca M et al. DHFR inhibitors: Reading the past for discovering novel anti-cancer agents. Molecules, 2019, 24(6): Article No. 1140. https:\/\/doi.org\/10.3390\/molecules24061140.","DOI":"10.3390\/molecules24061140"},{"issue":"7","key":"866_CR49","doi-asserted-by":"publisher","first-page":"1076","DOI":"10.2174\/092986712799320682","volume":"19","author":"DS Gesto","year":"2012","unstructured":"Gesto D S, Cerqueira N M, Fernandes P A et al. Gemcitabine: A critical nucleoside for cancer therapy. Current Medicinal Chemistry, 2012, 19(7): 1076-1087. https:\/\/doi.org\/10.2174\/092986712799320682.","journal-title":"Current Medicinal Chemistry"},{"issue":"3","key":"866_CR50","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1007\/s00535-011-0484-9","volume":"47","author":"T Shimasaki","year":"2012","unstructured":"Shimasaki T, Ishigaki Y, Nakamura Y et al. Glycogen synthase kinase 3\u03b2 inhibition sensitizes pancreatic cancer cells to gemcitabine. Journal of Gastroenterology, 2012, 47(3): 321-333. https:\/\/doi.org\/10.1007\/s00535-011-0484-9.","journal-title":"Journal of Gastroenterology"},{"issue":"3","key":"866_CR51","doi-asserted-by":"publisher","first-page":"E292","DOI":"10.1002\/ijc.26442","volume":"131","author":"AB Kunnumakkara","year":"2012","unstructured":"Kunnumakkara A B, Sung B, Ravindran J et al. Zyflamend suppresses growth and sensitizes human pancreatic tumors to gemcitabine in an orthotopic mouse model through modulation of multiple targets. International Journal of Cancer, 2012, 131(3): E292-E303. https:\/\/doi.org\/10.1002\/ijc.26442.","journal-title":"International Journal of Cancer"},{"key":"866_CR52","doi-asserted-by":"publisher","unstructured":"Xia G, Wang H, Song Z et al. Gambogic acid sensitizes gemcitabine efficacy in pancreatic cancer by reducing the expression of ribonucleotide reductase subunit-M2 (RRM2). Journal of Experimental & Clinical Cancer Research, 2017, 36(1): Article No. 107. https:\/\/doi.org\/10.1186\/s13046-017-0579-0.","DOI":"10.1186\/s13046-017-0579-0"},{"issue":"10","key":"866_CR53","doi-asserted-by":"publisher","first-page":"1036","DOI":"10.1093\/carcin\/bgx065","volume":"38","author":"K Yoshida","year":"2017","unstructured":"Yoshida K, Toden S, Ravindranathan P et al. Curcumin sensitizes pancreatic cancer cells to gemcitabine by attenuating PRC2 subunit EZH2, and the lncRNA PVT1 expression. Carcinogenesis, 2017, 38(10): 1036-1046. https:\/\/doi.org\/10.1093\/carcin\/bgx065.","journal-title":"Carcinogenesis"},{"issue":"1","key":"866_CR54","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1016\/j.cell.2011.03.020","volume":"145","author":"A Ashworth","year":"2011","unstructured":"Ashworth A, Lord C J, Reis-Filho J S. Genetic interactions in cancer progression and treatment. Cell., 2011, 145(1): 30-38. https:\/\/doi.org\/10.1016\/j.cell.2011.03.020.","journal-title":"Cell."},{"issue":"1","key":"866_CR55","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1016\/j.gde.2010.10.009","volume":"21","author":"R Brough","year":"2011","unstructured":"Brough R, Frankum J R, Costa-Cabral S et al. Searching for synthetic lethality in cancer. Current Opinion in Genetics and Development, 2011, 21(1): 34-41. https:\/\/doi.org\/10.1016\/j.gde.2010.10.009.","journal-title":"Current Opinion in Genetics and Development"}],"container-title":["Journal of Computer Science and Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11390-021-0866-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11390-021-0866-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11390-021-0866-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,4,14]],"date-time":"2021-04-14T06:11:15Z","timestamp":1618380675000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11390-021-0866-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,3,31]]},"references-count":55,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2021,4]]}},"alternative-id":["866"],"URL":"https:\/\/doi.org\/10.1007\/s11390-021-0866-2","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2020.08.03.235366","asserted-by":"object"}]},"ISSN":["1000-9000","1860-4749"],"issn-type":[{"value":"1000-9000","type":"print"},{"value":"1860-4749","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,3,31]]},"assertion":[{"value":"3 August 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 February 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 March 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}