{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,30]],"date-time":"2025-05-30T05:44:39Z","timestamp":1748583879780},"publisher-location":"Cham","reference-count":28,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319443317"},{"type":"electronic","value":"9783319443324"}],"license":[{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016]]},"DOI":"10.1007\/978-3-319-44332-4_10","type":"book-chapter","created":{"date-parts":[[2016,7,30]],"date-time":"2016-07-30T11:02:39Z","timestamp":1469876559000},"page":"129-140","source":"Crossref","is-referenced-by-count":51,"title":["A Deep Learning Approach to DNA Sequence Classification"],"prefix":"10.1007","author":[{"given":"Riccardo","family":"Rizzo","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Antonino","family":"Fiannaca","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Massimo","family":"La Rosa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alfonso","family":"Urso","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2016,7,31]]},"reference":[{"issue":"1","key":"10_CR1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1561\/2200000006","volume":"2","author":"Y Bengio","year":"2009","unstructured":"Bengio, Y.: Learning deep architectures for AI. Found. Trends Mach. Learn. 2(1), 1\u2013127 (2009)","journal-title":"Found. Trends Mach. Learn."},{"key":"10_CR2","unstructured":"Coates, A., Ng, A.Y., Lee, H.: An analysis of single-layer networks in unsupervised feature learning. In: International Conference on Artificial Intelligence and Statistics, pp. 215\u2013223 (2011)"},{"issue":"11","key":"10_CR3","doi-asserted-by":"crossref","first-page":"2278","DOI":"10.1109\/5.726791","volume":"86","author":"Y LeCun","year":"1998","unstructured":"LeCun, Y., Bottou, L., Bengio, Y., Haffner, P.: Gradient-based learning applied to document recognition. Proc. IEEE 86(11), 2278\u20132324 (1998)","journal-title":"Proc. IEEE"},{"issue":"8","key":"10_CR4","doi-asserted-by":"crossref","first-page":"1915","DOI":"10.1109\/TPAMI.2012.231","volume":"35","author":"C Farabet","year":"2013","unstructured":"Farabet, C., Couprie, C., Najman, L., LeCun, Y.: Learning hierarchical features for scene labeling. IEEE Trans. Pattern Anal. Mach. Intell. 35(8), 1915\u20131929 (2013)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10_CR5","doi-asserted-by":"crossref","unstructured":"Sukittanon, S., Surendran, A., Platt, J., Burges, C.: Convolutional Networks for Speech Detection. In: Interspeech, International Speech Communication Association (2004)","DOI":"10.21437\/Interspeech.2004-376"},{"key":"10_CR6","doi-asserted-by":"crossref","unstructured":"Nguyen, A., Yosinski, J., Clune, J.: Deep neural networks are easily fooled: high confidence predictions for unrecognizable images. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 427\u2013436. IEEE (2015)","DOI":"10.1109\/CVPR.2015.7298640"},{"key":"10_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1007\/978-3-319-24462-4_13","volume-title":"Computational Intelligence Methods for Bioinformatics and Biostatistics","author":"R Rizzo","year":"2015","unstructured":"Rizzo, R., Fiannaca, A., La Rosa, M., Urso, A.: The general regression neural network to classify barcode and mini-barcode DNA. In: di Serio, C., Li\u00f2, P., Nonis, A., Tagliaferri, R. (eds.) CIBB 2014. LNCS, vol. 8623, pp. 142\u2013155. Springer, Heidelberg (2015)"},{"issue":"10","key":"10_CR8","doi-asserted-by":"crossref","first-page":"3623","DOI":"10.1128\/JCM.38.10.3623-3630.2000","volume":"38","author":"M Drancourt","year":"2000","unstructured":"Drancourt, M., Bollet, C., Carlioz, A., Martelin, R., Gayral, J.P., Raoult, D.: 16S Ribosomal DNA sequence analysis of a large collection of environmental and clinical unidentifiable bacterial isolates. J. Clin. Microbiol. 38(10), 3623\u20133630 (2000)","journal-title":"J. Clin. Microbiol."},{"issue":"10","key":"10_CR9","doi-asserted-by":"crossref","first-page":"R108","DOI":"10.1186\/gb-2009-10-10-r108","volume":"10","author":"B Chor","year":"2009","unstructured":"Chor, B., Horn, D., Goldman, N., Levy, Y., Massingham, T.: Genomic DNA k-mer spectra: models and modalities. Genome Biol. 10(10), R108 (2009)","journal-title":"Genome Biol."},{"issue":"Suppl. 14","key":"10_CR10","doi-asserted-by":"crossref","first-page":"S9","DOI":"10.1186\/1471-2105-10-S14-S9","volume":"10","author":"P Kuksa","year":"2009","unstructured":"Kuksa, P., Pavlovic, V.: Efficient alignment-free DNA barcode analytics. BMC Bioinform. 10(Suppl. 14), S9 (2009)","journal-title":"BMC Bioinform."},{"key":"10_CR11","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1007\/978-3-319-23497-7_9","volume-title":"Mathematical Models in Biology","author":"M Rosa La","year":"2015","unstructured":"La Rosa, M., Fiannaca, A., Rizzo, R., Urso, A.: DNA Barcode classification using general regression neural network with different distance models. In: Zazzu, V., Ferraro, M.B., Guarracino, M.R. (eds.) Mathematical Models in Biology, pp. 119\u2013132. Springer, Heidelberg (2015)"},{"key":"10_CR12","series-title":"Communications in Computer and Information Science","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1007\/978-3-642-41016-1_23","volume-title":"Engineering Applications of Neural Networks","author":"A Fiannaca","year":"2013","unstructured":"Fiannaca, A., La Rosa, M., Rizzo, R., Urso, A.: Analysis of DNA barcode sequences using neural gas and spectral representation. In: Iliadis, L., Papadopoulos, H., Jayne, C. (eds.) EANN 2013, Part II. CCIS, vol. 384, pp. 212\u2013221. Springer, Heidelberg (2013)"},{"issue":"3","key":"10_CR13","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/j.artmed.2015.06.002","volume":"64","author":"A Fiannaca","year":"2015","unstructured":"Fiannaca, A., La Rosa, M., Rizzo, R., Urso, A.: A k-mer-based barcode DNA classification methodology based on spectral representation and a neural gas network. Artif. Intell. Med. 64(3), 173\u2013184 (2015)","journal-title":"Artif. Intell. Med."},{"key":"10_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1007\/978-3-319-09042-9_4","volume-title":"Computational Intelligence Methods for Bioinformatics and Biostatistics","author":"M Rosa La","year":"2014","unstructured":"La Rosa, M., Fiannaca, A., Rizzo, R., Urso, A.: Genomic sequence classification using probabilistic topic modeling. In: Formenti, E., Tagliaferri, R., Wit, E. (eds.) CIBB 2013. LNCS, vol. 8452, pp. 49\u201361. Springer, Heidelberg (2014)"},{"issue":"Suppl 6","key":"10_CR15","doi-asserted-by":"crossref","first-page":"S2","DOI":"10.1186\/1471-2105-16-S6-S2","volume":"16","author":"M Rosa La","year":"2015","unstructured":"La Rosa, M., Fiannaca, A., Rizzo, R., Urso, A.: Probabilistic topic modeling for the analysis and classification of genomic sequences. BMC Bioinform. 16(Suppl 6), S2 (2015)","journal-title":"BMC Bioinform."},{"key":"10_CR16","doi-asserted-by":"crossref","unstructured":"Weitschek, E., Cunial, F., Felici, G.: Classifying bacterial genomes with compact logic formulas on k-Mer frequencies. In: 2014 25th International Workshop on Database and Expert Systems Applications, pp. 69\u201373. IEEE (2014)","DOI":"10.1109\/DEXA.2014.30"},{"key":"10_CR17","unstructured":"Bastien, F., Lamblin, P., Pascanu, R., Bergstra, J., Godfellow, I., Bergeron, A., Bouchard, N., Warde-Farley, D., Bengio, Y.: Theano: new features and speed improvements. In: NIPS 2012 Deep Learning Workshop (2012)"},{"key":"10_CR18","doi-asserted-by":"crossref","unstructured":"Bergstra, J., Breuleux, O., Bastien, F., Lamblin, P., Pascanu, R., Desjardins, G., Turian, J., Warde-Farley, D., Bengio, Y.: Theano: a CPU and GPU math compiler in Python. In: 9th Python in Science Conference, pp. 1\u20137 (2010)","DOI":"10.25080\/Majora-92bf1922-003"},{"issue":"Database issue","key":"10_CR19","doi-asserted-by":"crossref","first-page":"D141","DOI":"10.1093\/nar\/gkn879","volume":"37","author":"JR Cole","year":"2009","unstructured":"Cole, J.R., Wang, Q., Cardenas, E., Fish, J., Chai, B., Farris, R.J., Kulam-Syed-Mohideen, A.S., McGarrell, D.M., Marsh, T., Garrity, G.M., Tiedje, J.M.: The Ribosomal Database Project: improved alignments and new tools for rRNA analysis. Nucleic Acids Res. 37(Database issue), D141\u2013D145 (2009)","journal-title":"Nucleic Acids Res."},{"issue":"2","key":"10_CR20","doi-asserted-by":"crossref","first-page":"e1000667","DOI":"10.1371\/journal.pcbi.1000667","volume":"6","author":"JC Wooley","year":"2010","unstructured":"Wooley, J.C., Godzik, A., Friedberg, I.: A primer on metagenomics. PLoS Comput. Biol. 6(2), e1000667 (2010)","journal-title":"PLoS Comput. Biol."},{"issue":"6","key":"10_CR21","doi-asserted-by":"crossref","first-page":"568","DOI":"10.1109\/72.97934","volume":"2","author":"DF Specht","year":"1991","unstructured":"Specht, D.F.: A general regression neural network. IEEE Trans. Neural Netw. 2(6), 568\u2013576 (1991)","journal-title":"IEEE Trans. Neural Netw."},{"key":"10_CR22","unstructured":"John, G.H.G., Langley, P.: Estimating continuous distributions in bayesian classifiers. In: Besnard, P., Hanks, S. (eds.) Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence, Montreal, Quebec, Canada, vol. 1, pp. 338\u2013345. Morgan Kaufmann, San Franisco, CA (1995)"},{"key":"10_CR23","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L.: Random forests. Mach. Learn. 45, 5\u201332 (2001)","journal-title":"Mach. Learn."},{"key":"10_CR24","volume-title":"Learning with Kernels","author":"B Scholkopf","year":"2002","unstructured":"Scholkopf, B., Smola, A.: Learning with Kernels. MIT Press, Cambridge (2002)"},{"issue":"1","key":"10_CR25","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1145\/1656274.1656278","volume":"11","author":"M Hall","year":"2009","unstructured":"Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The WEKA data mining software. ACM SIGKDD Explor. Newsl. 11(1), 10\u201318 (2009)","journal-title":"ACM SIGKDD Explor. Newsl."},{"issue":"3","key":"10_CR26","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1961189.1961199","volume":"2","author":"CC Chang","year":"2011","unstructured":"Chang, C.C., Lin, C.J.: LIBSVM: a library for support vector machines. ACM Trans. Intell. Syst. Technol. 2(3), 1\u201327 (2011)","journal-title":"ACM Trans. Intell. Syst. Technol."},{"key":"10_CR27","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1007\/978-3-642-76153-9_5","volume-title":"Neurocomputing","author":"S Knerr","year":"1990","unstructured":"Knerr, S., Personnaz, L., Dreyfus, G.: Single-layer learning revisited: a stepwise procedure for building and training a neural network. In: Souli\u00e9, F.F., H\u00e9rault, J. (eds.) Neurocomputing, pp. 41\u201350. Springer, Heidelberg (1990)"},{"issue":"W1","key":"10_CR28","doi-asserted-by":"crossref","first-page":"W65","DOI":"10.1093\/nar\/gkv458","volume":"43","author":"B Liu","year":"2015","unstructured":"Liu, B., Liu, F., Wang, X., Chen, J., Fang, L., Chou, K.C.: Pse-in-One: a web server for generating various modes of pseudo components of DNA, RNA, and protein sequences. Nucleic Acids Res. 43(W1), W65\u2013W71 (2015)","journal-title":"Nucleic Acids Res."}],"container-title":["Lecture Notes in Computer Science","Computational Intelligence Methods for Bioinformatics and Biostatistics"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-44332-4_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,4]],"date-time":"2022-07-04T12:18:25Z","timestamp":1656937105000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-44332-4_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016]]},"ISBN":["9783319443317","9783319443324"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-44332-4_10","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2016]]}}}