{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T16:14:59Z","timestamp":1743092099023,"version":"3.40.3"},"publisher-location":"Cham","reference-count":36,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319949673"},{"type":"electronic","value":"9783319949680"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-94968-0_4","type":"book-chapter","created":{"date-parts":[[2018,7,12]],"date-time":"2018-07-12T14:13:51Z","timestamp":1531404831000},"page":"38-48","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["PBMarsNet: A Multivariate Adaptive Regression Splines Based Method to Reconstruct Gene Regulatory Networks"],"prefix":"10.1007","author":[{"given":"Siyu","family":"Zhao","sequence":"first","affiliation":[]},{"given":"Ruiqing","family":"Zheng","sequence":"additional","affiliation":[]},{"given":"Xiang","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Yaohang","family":"Li","sequence":"additional","affiliation":[]},{"given":"Fang-Xiang","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Min","family":"Li","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,7,13]]},"reference":[{"issue":"1","key":"4_CR1","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1016\/S1367-5931(02)00005-4","volume":"7","author":"H Zhu","year":"2003","unstructured":"Zhu, H., Snyder, M.: Protein chip technology. Curr. Opin. Chem. Biol. 7(1), 55\u201363 (2003)","journal-title":"Curr. Opin. Chem. Biol."},{"issue":"5902","key":"4_CR2","doi-asserted-by":"publisher","first-page":"750","DOI":"10.1126\/science.1163045","volume":"322","author":"J Zhao","year":"2008","unstructured":"Zhao, J., Sun, B.K., Erwin, J.A., Song, J.J., Lee, J.T.: Polycomb proteins targeted by a short repeat RNA to the mouse X chromosome. Science 322(5902), 750\u2013756 (2008)","journal-title":"Science"},{"issue":"20","key":"4_CR3","doi-asserted-by":"publisher","first-page":"204101","DOI":"10.1103\/PhysRevLett.99.204101","volume":"99","author":"S Frenzel","year":"2007","unstructured":"Frenzel, S., Pompe, B.: Partial mutual information for coupling analysis of multivariate time series. Phys. Rev. Lett. 99(20), 204101 (2007)","journal-title":"Phys. Rev. Lett."},{"issue":"1","key":"4_CR4","doi-asserted-by":"publisher","first-page":"e8","DOI":"10.1371\/journal.pbio.0050008","volume":"5","author":"JJ Faith","year":"2007","unstructured":"Faith, J.J., Hayete, B., Thaden, J.T., Mogno, I., Wierzbowski, J., Cottarel, G., Kasif, S., Collins, J.J., Gardner, T.S.: Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles. PLoS Biol. 5(1), e8 (2007)","journal-title":"PLoS Biol."},{"issue":"14","key":"4_CR5","doi-asserted-by":"publisher","first-page":"2233","DOI":"10.1093\/bioinformatics\/btw216","volume":"32","author":"A Lachmann","year":"2016","unstructured":"Lachmann, A., Giorgi, F.M., Lopez, G., Califano, A.: ARACNe-AP: gene network reverse engineering through adaptive partitioning inference of mutual information. Bioinformatics 32(14), 2233\u20132235 (2016)","journal-title":"Bioinformatics"},{"key":"4_CR6","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1155\/2007\/79879","volume":"2007","author":"PE Meyer","year":"2007","unstructured":"Meyer, P.E., Kontos, K., Lafitte, F., Bontempi, G.: Information-theoretic inference of large transcriptional regulatory networks. EURASIP J. Bioinf. Syst. Biol. 2007, 8 (2007)","journal-title":"EURASIP J. Bioinf. Syst. Biol."},{"issue":"1","key":"4_CR7","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1093\/bioinformatics\/btr626","volume":"28","author":"X Zhang","year":"2011","unstructured":"Zhang, X., Zhao, X.M., He, K., Lu, L., Cao, Y., Liu, J., Hao, J.K., Liu, Z.P., Chen, L.: Inferring gene regulatory networks from gene expression data by path consistency algorithm based on conditional mutual information. Bioinformatics 28(1), 98\u2013104 (2011)","journal-title":"Bioinformatics"},{"issue":"5","key":"4_CR8","doi-asserted-by":"publisher","first-page":"e31","DOI":"10.1093\/nar\/gku1315","volume":"43","author":"X Zhang","year":"2014","unstructured":"Zhang, X., Zhao, J., Hao, J.K., Zhao, X.M., Chen, L.: Conditional mutual inclusive information enables accurate quantification of associations in gene regulatory networks. Nucleic Acids Res. 43(5), e31 (2014)","journal-title":"Nucleic Acids Res."},{"issue":"18","key":"4_CR9","doi-asserted-by":"publisher","first-page":"5130","DOI":"10.1073\/pnas.1522586113","volume":"113","author":"J Zhao","year":"2016","unstructured":"Zhao, J., Zhou, Y., Zhang, X., Chen, L.: Part mutual information for quantifying direct associations in networks. Proc. Nat. Acad. Sci. 113(18), 5130\u20135135 (2016)","journal-title":"Proc. Nat. Acad. Sci."},{"issue":"17","key":"4_CR10","doi-asserted-by":"publisher","first-page":"2918","DOI":"10.1093\/bioinformatics\/bth318","volume":"20","author":"X Zhou","year":"2004","unstructured":"Zhou, X., Wang, X., Pal, R., Ivanov, I., Bittner, M., Dougherty, E.R.: A Bayesian connectivity-based approach to constructing probabilistic gene regulatory networks. Bioinformatics 20(17), 2918\u20132927 (2004)","journal-title":"Bioinformatics"},{"key":"4_CR11","doi-asserted-by":"crossref","unstructured":"Werhli, A.V., Husmeier, D.: Reconstructing gene regulatory networks with Bayesian networks by combining expression data with multiple sources of prior knowledge. Stat. Appl. Genet. Mol. Biol. 6(1) (2007)","DOI":"10.2202\/1544-6115.1282"},{"key":"4_CR12","doi-asserted-by":"crossref","unstructured":"Shermin, A., Orgun, M.A.: Using dynamic Bayesian networks to infer gene regulatory networks from expression profiles. In: ACM Symposium on Applied Computing, pp. 799\u2013803 (2009)","DOI":"10.1145\/1529282.1529449"},{"issue":"4","key":"4_CR13","doi-asserted-by":"publisher","first-page":"792","DOI":"10.1109\/TCBB.2015.2474409","volume":"13","author":"Y Li","year":"2016","unstructured":"Li, Y., Chen, H., Zheng, J., Ngom, A.: The max-min high-order dynamic Bayesian network for learning gene regulatory networks with time-delayed regulations. IEEE\/ACM Trans. Comput. Biol. Bioinform. (TCBB) 13(4), 792\u2013803 (2016)","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinform. (TCBB)"},{"key":"4_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1007\/978-3-642-24855-9_8","volume-title":"Pattern Recognition in Bioinformatics","author":"J Zheng","year":"2011","unstructured":"Zheng, J., Chaturvedi, I., Rajapakse, J.C.: Integration of epigenetic data in Bayesian network modeling of gene regulatory network. In: Loog, M., Wessels, L., Reinders, M.J.T., de Ridder, D. (eds.) PRIB 2011. LNCS, vol. 7036, pp. 87\u201396. Springer, Heidelberg (2011). \nhttps:\/\/doi.org\/10.1007\/978-3-642-24855-9_8"},{"issue":"8","key":"4_CR15","doi-asserted-by":"publisher","first-page":"e1005024","DOI":"10.1371\/journal.pcbi.1005024","volume":"12","author":"F Liu","year":"2016","unstructured":"Liu, F., Zhang, S.W., Guo, W.F., Wei, Z.G., Chen, L.: Inference of gene regulatory network based on local bayesian networks. PLoS Comput. Biol. 12(8), e1005024 (2016)","journal-title":"PLoS Comput. Biol."},{"key":"4_CR16","doi-asserted-by":"publisher","first-page":"20533","DOI":"10.1038\/srep20533","volume":"6","author":"N Omranian","year":"2016","unstructured":"Omranian, N., Eloundou-Mbebi, J.M., Mueller-Roeber, B., Nikoloski, Z.: Gene regulatory network inference using fused LASSO on multiple data sets. Sci. Rep. 6, 20533 (2016)","journal-title":"Sci. Rep."},{"issue":"1","key":"4_CR17","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1186\/1752-0509-6-145","volume":"6","author":"AC Haury","year":"2012","unstructured":"Haury, A.C., Mordelet, F., Vera-Licona, P., Vert, J.P.: TIGRESS: trustful inference of gene regulation using stability selection. BMC Syst. Biol. 6(1), 145 (2012)","journal-title":"BMC Syst. Biol."},{"issue":"2","key":"4_CR18","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1109\/TCBB.2015.2450740","volume":"13","author":"N Singh","year":"2016","unstructured":"Singh, N., Vidyasagar, M.: bLARS: an algorithm to infer gene regulatory networks. IEEE\/ACM Trans. Comput. Biol. Bioinf. 13(2), 301\u2013314 (2016)","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinf."},{"issue":"1","key":"4_CR19","doi-asserted-by":"publisher","first-page":"545","DOI":"10.1186\/s12859-016-1398-6","volume":"17","author":"S Guo","year":"2016","unstructured":"Guo, S., Jiang, Q., Chen, L., Guo, D.: Gene regulatory network inference using PLS-based methods. BMC Bioinform. 17(1), 545 (2016)","journal-title":"BMC Bioinform."},{"issue":"1","key":"4_CR20","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1186\/s12859-015-0710-1","volume":"16","author":"S Yao","year":"2015","unstructured":"Yao, S., Yoo, S., Yu, D.: Prior knowledge driven Granger causality analysis on gene regulatory network discovery. BMC Bioinform. 16(1), 273 (2015)","journal-title":"BMC Bioinform."},{"key":"4_CR21","unstructured":"Li, M., Zheng, R., Li, Y., Wu, F.X., Wang, J.: MGT-SM: a method for constructing cellular signal transduction networks. IEEE\/ACM Trans. Comput. Biol. Bioinform. (2017)"},{"issue":"9","key":"4_CR22","doi-asserted-by":"publisher","first-page":"e12776","DOI":"10.1371\/journal.pone.0012776","volume":"5","author":"A Irrthum","year":"2010","unstructured":"Irrthum, A., Wehenkel, L., Geurts, P., et al.: Inferring regulatory networks from expression data using tree-based methods. PLoS One 5(9), e12776 (2010)","journal-title":"PLoS One"},{"issue":"3","key":"4_CR23","doi-asserted-by":"publisher","first-page":"e92709","DOI":"10.1371\/journal.pone.0092709","volume":"9","author":"J Ruyssinck","year":"2014","unstructured":"Ruyssinck, J., Geurts, P., Dhaene, T., Demeester, P., Saeys, Y., et al.: NIMEFI: gene regulatory network inference using multiple ensemble feature importance algorithms. PLoS One 9(3), e92709 (2014)","journal-title":"PLoS One"},{"issue":"10","key":"4_CR24","doi-asserted-by":"publisher","first-page":"1614","DOI":"10.1093\/bioinformatics\/btu863","volume":"31","author":"VA Huynh-Thu","year":"2015","unstructured":"Huynh-Thu, V.A., Sanguinetti, G.: Combining tree-based and dynamical systems for the inference of gene regulatory networks. Bioinformatics 31(10), 1614\u20131622 (2015)","journal-title":"Bioinformatics"},{"issue":"10","key":"4_CR25","doi-asserted-by":"publisher","first-page":"e13397","DOI":"10.1371\/journal.pone.0013397","volume":"5","author":"A Greenfield","year":"2010","unstructured":"Greenfield, A., Madar, A., Ostrer, H., Bonneau, R.: DREAM4: combining genetic and dynamic information to identify biological networks and dynamical models. PLoS One 5(10), e13397 (2010)","journal-title":"PLoS One"},{"issue":"8","key":"4_CR26","doi-asserted-by":"publisher","first-page":"796","DOI":"10.1038\/nmeth.2016","volume":"9","author":"D Marbach","year":"2012","unstructured":"Marbach, D., Costello, J.C., K\u00fcffner, R., Vega, N.M., Prill, R.J., Camacho, D.M., Allison, K.R., Aderhold, A., Bonneau, R., Chen, Y., et al.: Wisdom of crowds for robust gene network inference. Nat. Methods 9(8), 796 (2012)","journal-title":"Nat. Methods"},{"issue":"16","key":"4_CR27","doi-asserted-by":"publisher","first-page":"2263","DOI":"10.1093\/bioinformatics\/btr373","volume":"27","author":"T Schaffter","year":"2011","unstructured":"Schaffter, T., Marbach, D., Floreano, D.: GeneNetWeaver: in silico benchmark generation and performance profiling of network inference methods. Bioinformatics 27(16), 2263\u20132270 (2011)","journal-title":"Bioinformatics"},{"key":"4_CR28","doi-asserted-by":"crossref","unstructured":"Friedman, J.H.: Multivariate adaptive regression splines. Ann. Stat. 1\u201367 (1991)","DOI":"10.1214\/aos\/1176347963"},{"issue":"1\u20132","key":"4_CR29","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1016\/S0021-9673(03)00604-6","volume":"998","author":"QS Xu","year":"2003","unstructured":"Xu, Q.S., Massart, D., Liang, Y.Z., Fang, K.T.: Two-step multivariate adaptive regression splines for modeling a quantitative relationship between gas chromatography retention indices and molecular descriptors. J. Chromatogr. A 998(1\u20132), 155\u2013167 (2003)","journal-title":"J. Chromatogr. A"},{"issue":"3","key":"4_CR30","doi-asserted-by":"publisher","first-page":"371","DOI":"10.1080\/17415977.2011.624770","volume":"20","author":"GW Weber","year":"2012","unstructured":"Weber, G.W., Batmaz, \u0130., K\u00f6ksal, G., Taylan, P., Yerlikaya-\u00d6zkurt, F.: CMARS: a new contribution to nonparametric regression with multivariate adaptive regression splines supported by continuous optimization. Inverse Prob. Sci. Eng. 20(3), 371\u2013400 (2012)","journal-title":"Inverse Prob. Sci. Eng."},{"key":"4_CR31","series-title":"Springer Series in Statistics","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-21606-5","volume-title":"The Elements of Statistical Learning","author":"J Friedman","year":"2001","unstructured":"Friedman, J., Hastie, T., Tibshirani, R.: The Elements of Statistical Learning. Springer Series in Statistics, vol. 1. Springer, New York (2001). \nhttps:\/\/doi.org\/10.1007\/978-0-387-21606-5"},{"key":"4_CR32","unstructured":"Friedman, J.H.: Estimating functions of mixed ordinal and categorical variables using adaptive splines. Technical report, Stanford Univ., CA, Lab for Computational Statistics (1991)"},{"issue":"8","key":"4_CR33","doi-asserted-by":"publisher","first-page":"1349","DOI":"10.1016\/j.jss.2006.10.049","volume":"80","author":"Y Zhou","year":"2007","unstructured":"Zhou, Y., Leung, H.: Predicting object-oriented software maintainability using multivariate adaptive regression splines. J. Syst. Softw. 80(8), 1349\u20131361 (2007)","journal-title":"J. Syst. Softw."},{"key":"4_CR34","unstructured":"Friedman, J.H.: Fast MARS. Computational Statistics Laboratory of Stanford University (1993)"},{"issue":"8","key":"4_CR35","doi-asserted-by":"publisher","first-page":"422","DOI":"10.1016\/S0168-9525(03)00175-6","volume":"19","author":"H Yu","year":"2003","unstructured":"Yu, H., Luscombe, N.M., Qian, J., Gerstein, M.: Genomic analysis of gene expression relationships in transcriptional regulatory networks. Trends Genet. 19(8), 422\u2013427 (2003)","journal-title":"Trends Genet."},{"issue":"2","key":"4_CR36","doi-asserted-by":"publisher","first-page":"662","DOI":"10.1038\/nprot.2006.106","volume":"1","author":"AA Margolin","year":"2006","unstructured":"Margolin, A.A., Wang, K., Lim, W.K., Kustagi, M., Nemenman, I., Califano, A.: Reverse engineering cellular networks. Nat. Protoc. 1(2), 662 (2006)","journal-title":"Nat. Protoc."}],"container-title":["Lecture Notes in Computer Science","Bioinformatics Research and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-94968-0_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,11,15]],"date-time":"2019-11-15T01:03:41Z","timestamp":1573779821000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-94968-0_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319949673","9783319949680"],"references-count":36,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-94968-0_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"13 July 2018","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":"Beijing","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 June 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 June 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"isbra2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/alan.cs.gsu.edu\/isbra18\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}