{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T00:14:09Z","timestamp":1742948049754,"version":"3.40.3"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319993430"},{"type":"electronic","value":"9783319993447"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","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\/978-3-319-99344-7_16","type":"book-chapter","created":{"date-parts":[[2018,8,28]],"date-time":"2018-08-28T02:45:48Z","timestamp":1535424348000},"page":"173-185","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Machine Learning-Driven Noise Separation in High Variation Genomics Sequencing Datasets"],"prefix":"10.1007","author":[{"given":"Milko","family":"Krachunov","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maria","family":"Nisheva","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dimitar","family":"Vassilev","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,8,29]]},"reference":[{"issue":"620","key":"16_CR1","doi-asserted-by":"publisher","first-page":"118","DOI":"10.3399\/bjgp14X677374","volume":"64","author":"E Allen-Vercoe","year":"2014","unstructured":"Allen-Vercoe, E., Petrof, E.O.: The microbiome: what it means for medicine. Br. J. Gen. Pract. 64(620), 118\u2013119 (2014)","journal-title":"Br. J. Gen. Pract."},{"issue":"1","key":"16_CR2","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L.: Random forests. Mach. Learn. 45(1), 5\u201332 (2001)","journal-title":"Mach. Learn."},{"issue":"7426","key":"16_CR3","doi-asserted-by":"publisher","first-page":"705","DOI":"10.1038\/nature11650","volume":"491","author":"R Brenchley","year":"2012","unstructured":"Brenchley, R., et al.: Analysis of the bread wheat genome using whole-genome shotgun sequencing. Nature 491(7426), 705\u2013710 (2012)","journal-title":"Nature"},{"key":"16_CR4","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1186\/1471-2164-12-245","volume":"12","author":"A Gilles","year":"2011","unstructured":"Gilles, A., Megl\u00e9cz, E., Pech, N., Ferreira, S., Malausa, T., Martin, J.F.: Accuracy and quality assessment of 454 gs-flx titanium pyrosequencing. BMC Genomics 12, 245 (2011)","journal-title":"BMC Genomics"},{"issue":"7","key":"16_CR5","doi-asserted-by":"publisher","first-page":"R143","DOI":"10.1186\/gb-2007-8-7-r143","volume":"8","author":"S Huse","year":"2007","unstructured":"Huse, S., Huber, J., Morrison, H., Sogin, M., Welch, D.: Accuracy and quality of massively parallel dna pyrose- quencing. Genome Biol. 8(7), R143 (2007)","journal-title":"Genome Biol."},{"key":"16_CR6","doi-asserted-by":"crossref","unstructured":"Karlsson, O.E., Hansen, T., Knutsson, R., L\u00f6fstr\u00f6m, C., Granberg, F., Berg, M.: Metagenomic detection methods in biopreparedness outbreak scenarios. Biosecurity Bioterrorism Biodefense Strategy Pract. Sci. 11(S1), S146\u2013S157 (2013)","DOI":"10.1089\/bsp.2012.0077"},{"issue":"2","key":"16_CR7","doi-asserted-by":"publisher","first-page":"511","DOI":"10.1093\/nar\/gki198","volume":"33","author":"K Katoh","year":"2005","unstructured":"Katoh, K., Kuma, K., Toh, H., Miyata, T.: MAFFT version 5: improvement in accuracy of multiple sequence alignment. Nucleid Acid Res. 33(2), 511\u2013518 (2005)","journal-title":"Nucleid Acid Res."},{"issue":"7351","key":"16_CR8","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1038\/nature10213","volume":"474","author":"AL Kau","year":"2011","unstructured":"Kau, A.L., et al.: Human nutrition, the gut microbiome, and immune system: envisioning the future. Nature 474(7351), 327\u2013336 (2011)","journal-title":"Nature"},{"key":"16_CR9","unstructured":"Kirov, K., Krachunov, M., Kulev, O., Nisheva, M., Vassilev, D.: Reducing false negatives for errors in snp detection using a machine learning approach. Comptes rendus de l\u2019Acad\u00e9mie bulgare des Sciences 69(2), 155\u2013160 (2016)"},{"key":"16_CR10","doi-asserted-by":"publisher","first-page":"1145","DOI":"10.1016\/j.procs.2017.05.242","volume":"108C","author":"M Krachunov","year":"2017","unstructured":"Krachunov, M., Nisheva, M., Vassilev, D.: Machine learning models in error and variant detection high-variation high-throughput sequencing datasets. Procedia Comput. Sci. 108C, 1145\u20131154 (2017)","journal-title":"Procedia Comput. Sci."},{"key":"16_CR11","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1016\/j.jocs.2013.08.003","volume":"5","author":"M Krachunov","year":"2014","unstructured":"Krachunov, M., Vassilev, D.: An approach to a metagenomic data processing workflow. J. Comput. Sci. 5, 357\u2013362 (2014)","journal-title":"J. Comput. Sci."},{"issue":"1","key":"16_CR12","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1016\/j.tim.2009.11.003","volume":"18","author":"D Kristensen","year":"2010","unstructured":"Kristensen, D., Mushegian, A., Dolja, V., Koonin, E.: New dimensions of the virus world discovered through metagenomics. Trends Microbiol. 18(1), 11\u201319 (2010)","journal-title":"Trends Microbiol."},{"issue":"1","key":"16_CR13","doi-asserted-by":"publisher","first-page":"118","DOI":"10.1111\/j.1462-2920.2009.02051.x","volume":"12","author":"V Kunin","year":"2010","unstructured":"Kunin, V., Engelbrektson, A., Ochman, H., Hugenholtz, P.: Wrinkles in the rare biosphere: pyrosequencing errors can lead to artificial inflation of diversity estimates. Environ. Microbiol. 12(1), 118\u2013123 (2010)","journal-title":"Environ. Microbiol."},{"key":"16_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.bdq.2015.02.001","volume":"3","author":"T Laver","year":"2015","unstructured":"Laver, T., et al.: Assessing the performance of the Oxford Nanopore Technologies MinION. Biomol. Detect. Quantification 3, 1\u20138 (2015)","journal-title":"Biomol. Detect. Quantification"},{"key":"16_CR15","unstructured":"Li, R.W. (ed.): Metagenomics and its Applications in Agriculture, Biomedicine and Environmental Studies. Nova Science Pub Inc. (2010)"},{"issue":"13","key":"16_CR16","doi-asserted-by":"publisher","first-page":"1658","DOI":"10.1093\/bioinformatics\/btl158","volume":"22","author":"W Li","year":"2006","unstructured":"Li, W., Godzik, A.: Cd-Hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22(13), 1658\u20131659 (2006)","journal-title":"Bioinformatics"},{"key":"16_CR17","doi-asserted-by":"crossref","unstructured":"Marcussen, T., et al.: Ancient hybridizations among the ancestral genomes of bread wheat. Science 345(6194), 286\u2013291 (2014)","DOI":"10.1126\/science.1250092"},{"issue":"6","key":"16_CR18","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1016\/j.ygeno.2010.03.001","volume":"95","author":"JR Miller","year":"2010","unstructured":"Miller, J.R., Koren, S., Sutton, G.: Assembly algorithms for Next-Generation Sequencing data. Genomics 95(6), 315\u2013327 (2010)","journal-title":"Genomics"},{"key":"16_CR19","unstructured":"Nelson, K., White, B.: Metagenomics and its applications to the study of the human microbiome. In: Metagenomics: Theory, Methods and Applications, pp. 171\u2013182 (2010)"},{"key":"16_CR20","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1007\/978-1-4419-9326-7_11","volume-title":"Ensemble Machine Learning","author":"Y Qi","year":"2012","unstructured":"Qi, Y.: Random forest for bioinformatics. In: Zhang, C., Ma, Y. (eds.) Ensemble Machine Learning, pp. 307\u2013323. Springer, Boston (2012). https:\/\/doi.org\/10.1007\/978-1-4419-9326-7_11"},{"key":"16_CR21","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-61068-4","volume-title":"Neural Networks: A Systematic Introduction","author":"R Rojas","year":"1996","unstructured":"Rojas, R.: Neural Networks: A Systematic Introduction. Springer, Heidelberg (1996). https:\/\/doi.org\/10.1007\/978-3-642-61068-4"},{"issue":"9","key":"16_CR22","doi-asserted-by":"publisher","first-page":"1037","DOI":"10.2217\/fmb.12.82","volume":"7","author":"AA Saei","year":"2012","unstructured":"Saei, A.A., Barzegari, A.: The microbiome: the forgotten organ of the astronaut\u2019s body\u2013probiotics beyond terrestrial limits. Future Microbiol. 7(9), 1037\u20131046 (2012)","journal-title":"Future Microbiol."},{"issue":"17","key":"16_CR23","doi-asserted-by":"publisher","first-page":"2157","DOI":"10.1093\/bioinformatics\/btp379","volume":"25","author":"J Schr\u00f6der","year":"2009","unstructured":"Schr\u00f6der, J., Schr\u00f6der, H., Puglisi, S.J., Sinha, R., Schmidt, B.: SHREC: a short-read error correction method. Bioinformatics 25(17), 2157\u20132163 (2009)","journal-title":"Bioinformatics"},{"key":"16_CR24","unstructured":"United Nations, Food and Agriculture Organization, S.D.F. Crops\/World total\/Wheat\/Area harvested (2014). https:\/\/web.archive.org\/web\/20150906230329\/, http:\/\/faostat.fao.org\/site\/567\/DesktopDefault.aspx?PageID=567. Accessed 25 June 2018"},{"key":"16_CR25","doi-asserted-by":"crossref","unstructured":"Valverde, J., Mellado, R.: Analysis of metagenomic data containing high biodiversity levels. PLoS ONE 8(3) (2013). Article no. e58118","DOI":"10.1371\/journal.pone.0058118"},{"key":"16_CR26","volume-title":"Data Mining: Practical Machine Learning Tools and Techniques","author":"IH Witten","year":"2011","unstructured":"Witten, I.H., Frank, E., Hal, M.A.: Data Mining: Practical Machine Learning Tools and Techniques, 3rd edn. Morgan Kaufmann Publishers, San Francisco (2011)","edition":"3"}],"container-title":["Lecture Notes in Computer Science","Artificial Intelligence: Methodology, Systems, and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-99344-7_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T16:27:30Z","timestamp":1709828850000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-99344-7_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319993430","9783319993447"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-99344-7_16","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":"29 August 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AIMSA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Intelligence: Methodology, Systems, and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Varna","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bulgaria","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":"12 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 September 2018","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":"aimsa2018a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.aimsaconference.org\/","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":"22","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":"7","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":"31% - 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":"2,2","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":"4","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)"}}]}}