{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T19:06:25Z","timestamp":1783969585961,"version":"3.55.0"},"publisher-location":"Singapore","reference-count":27,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819234974","type":"print"},{"value":"9789819234981","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T00:00:00Z","timestamp":1783987200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T00:00:00Z","timestamp":1783987200000},"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":[[2027]]},"DOI":"10.1007\/978-981-92-3498-1_30","type":"book-chapter","created":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T18:45:53Z","timestamp":1783968353000},"page":"349-360","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["TAXICF: Efficient Index Construction and Accurate Metagenomic Classification with Interleaved Cuckoo Filters"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-8073-3582","authenticated-orcid":false,"given":"Qinzhong","family":"Tian","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-1788-3084","authenticated-orcid":false,"given":"Pinglu","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6406-1142","authenticated-orcid":false,"given":"Quan","family":"Zou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,14]]},"reference":[{"key":"30_CR1","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1146\/annurev-pathmechdis-012418-012751","volume":"14","author":"W Gu","year":"2019","unstructured":"Gu, W., Miller, S., Chiu, C.Y.: Clinical metagenomic next-generation sequencing for pathogen detection. Annu. Rev. Pathol. 14, 319\u2013338 (2019). https:\/\/doi.org\/10.1146\/annurev-pathmechdis-012418-012751","journal-title":"Annu. Rev. Pathol."},{"key":"30_CR2","doi-asserted-by":"publisher","first-page":"2815","DOI":"10.1038\/s41596-022-00738-y","volume":"17","author":"J Lu","year":"2022","unstructured":"Lu, J., et al.: Metagenome analysis using the kraken software suite. Nat. Protoc. 17, 2815\u20132839 (2022). https:\/\/doi.org\/10.1038\/s41596-022-00738-y","journal-title":"Nat. Protoc."},{"key":"30_CR3","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1016\/j.mimet.2016.01.011","volume":"122","author":"F Valenzuela-Gonz\u00e1lez","year":"2016","unstructured":"Valenzuela-Gonz\u00e1lez, F., Mart\u00ednez-Porchas, M., Villalpando-Canchola, E., Vargas-Albores, F.: Studying long 16S rDNA sequences with ultrafast-metagenomic sequence classification using exact alignments (kraken). J. Microbiol. Methods 122, 38\u201342 (2016). https:\/\/doi.org\/10.1016\/j.mimet.2016.01.011","journal-title":"J. Microbiol. Methods"},{"key":"30_CR4","doi-asserted-by":"publisher","unstructured":"Jiang, Z., et al.: Reference-guided chromosome-by-chromosome de novo assembly at scale using low-coverage high-Fidelity long-reads with HiFiCCL. Adv. Sci. n\/a, e15308. https:\/\/doi.org\/10.1002\/advs.202515308","DOI":"10.1002\/advs.202515308"},{"key":"30_CR5","doi-asserted-by":"publisher","first-page":"D243","DOI":"10.1093\/nar\/gkae1038","volume":"53","author":"T Goldfarb","year":"2025","unstructured":"Goldfarb, T., Kodali, V.K., Pujar, S., et al.: NCBI RefSeq: reference sequence standards through 25 years of curation and annotation. Nucleic Acids Res. 53, D243\u2013D257 (2025). https:\/\/doi.org\/10.1093\/nar\/gkae1038","journal-title":"Nucleic Acids Res."},{"key":"30_CR6","doi-asserted-by":"publisher","first-page":"D501","DOI":"10.1093\/nar\/gki025","volume":"33","author":"KD Pruitt","year":"2005","unstructured":"Pruitt, K.D., Tatusova, T., Maglott, D.R.: NCBI reference sequence (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic Acids Res. 33, D501\u2013D504 (2005). https:\/\/doi.org\/10.1093\/nar\/gki025","journal-title":"Nucleic Acids Res."},{"key":"30_CR7","doi-asserted-by":"publisher","first-page":"833","DOI":"10.1038\/nbt.3935","volume":"35","author":"C Quince","year":"2017","unstructured":"Quince, C., Walker, A.W., Simpson, J.T., Loman, N.J., Segata, N.: Shotgun metagenomics, from sampling to analysis. Nat. Biotechnol. 35, 833\u2013844 (2017). https:\/\/doi.org\/10.1038\/nbt.3935","journal-title":"Nat. Biotechnol."},{"key":"30_CR8","doi-asserted-by":"publisher","first-page":"779","DOI":"10.1016\/j.cell.2019.07.010","volume":"178","author":"SH Ye","year":"2019","unstructured":"Ye, S.H., Siddle, K.J., Park, D.J., Sabeti, P.C.: Benchmarking metagenomics tools for taxonomic classification. Cell 178, 779\u2013794 (2019). https:\/\/doi.org\/10.1016\/j.cell.2019.07.010","journal-title":"Cell"},{"key":"30_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13059-018-1568-0","volume":"19","author":"FP Breitwieser","year":"2018","unstructured":"Breitwieser, F.P., Baker, D.N., Salzberg, S.L.: KrakenUniq: confident and fast metagenomics classification using unique k-mer counts. Genome Biol. 19, 1\u201310 (2018)","journal-title":"Genome Biol."},{"key":"30_CR10","doi-asserted-by":"publisher","first-page":"btae718","DOI":"10.1093\/bioinformatics\/btae718","volume":"40","author":"T Zhou","year":"2024","unstructured":"Zhou, T., Zhang, P., Zou, Q., Han, W.: HAlign 4: a new strategy for rapidly aligning millions of sequences. Bioinformatics 40, btae718 (2024). https:\/\/doi.org\/10.1093\/bioinformatics\/btae718","journal-title":"Bioinformatics"},{"key":"30_CR11","doi-asserted-by":"publisher","first-page":"evae102","DOI":"10.1093\/gbe\/evae102","volume":"16","author":"Q Tian","year":"2024","unstructured":"Tian, Q., Zhang, P., Zhai, Y., Wang, Y., Zou, Q.: Application and comparison of machine learning and database-based methods in taxonomic classification of high-throughput sequencing data. Genome Biol. Evol. 16, evae102 (2024). https:\/\/doi.org\/10.1093\/gbe\/evae102","journal-title":"Genome Biol. Evol."},{"key":"30_CR12","doi-asserted-by":"publisher","first-page":"btae014","DOI":"10.1093\/bioinformatics\/btae014","volume":"40","author":"P Zhang","year":"2024","unstructured":"Zhang, P., Liu, H., Wei, Y., Zhai, Y., Tian, Q., Zou, Q.: FMAlign2: a novel fast multiple nucleotide sequence alignment method for ultralong datasets. Bioinformatics 40, btae014 (2024). https:\/\/doi.org\/10.1093\/bioinformatics\/btae014","journal-title":"Bioinformatics"},{"key":"30_CR13","doi-asserted-by":"publisher","unstructured":"Zhang, P., Wei, Y., Tian, Q., Zou, Q., Wang, Y.: Fast sequence alignment for centromere with RaMA. Genome Res. gr.279763.124. (2025). https:\/\/doi.org\/10.1101\/gr.279763.124","DOI":"10.1101\/gr.279763.124"},{"key":"30_CR14","doi-asserted-by":"crossref","unstructured":"Tian, Q., Zhang, P., Wei, Y., Zou, Q., Wang, Y., Luo, X.: Chimera: Ultrafast and Memory-efficient Database Construction for High-Accuracy Taxonomic Classification in the Age of Expanding Genomic Data (2025). https:\/\/www.biorxiv.org\/content\/10.1101\/2025.03.26.645388v1","DOI":"10.1101\/2025.03.26.645388"},{"key":"30_CR15","doi-asserted-by":"publisher","first-page":"D762","DOI":"10.1093\/nar\/gkad988","volume":"52","author":"DH Haft","year":"2023","unstructured":"Haft, D.H., et al.: RefSeq and the prokaryotic genome annotation pipeline in the age of metagenomes. Nucleic Acids Res. 52, D762 (2023). https:\/\/doi.org\/10.1093\/nar\/gkad988","journal-title":"Nucleic Acids Res."},{"key":"30_CR16","doi-asserted-by":"publisher","first-page":"D851","DOI":"10.1093\/nar\/gkx1068","volume":"46","author":"DH Haft","year":"2018","unstructured":"Haft, D.H., et al.: RefSeq: an update on prokaryotic genome annotation and curation. Nucleic Acids Res. 46, D851\u2013D860 (2018). https:\/\/doi.org\/10.1093\/nar\/gkx1068","journal-title":"Nucleic Acids Res."},{"key":"30_CR17","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1186\/s13059-019-1891-0","volume":"20","author":"DE Wood","year":"2019","unstructured":"Wood, D.E., Lu, J., Langmead, B.: Improved metagenomic analysis with kraken 2. Genome Biol. 20, 257 (2019). https:\/\/doi.org\/10.1186\/s13059-019-1891-0","journal-title":"Genome Biol."},{"key":"30_CR18","doi-asserted-by":"publisher","first-page":"i12","DOI":"10.1093\/bioinformatics\/btaa458","volume":"36","author":"VC Piro","year":"2020","unstructured":"Piro, V.C., Dadi, T.H., Seiler, E., Reinert, K., Renard, B.Y.: Ganon: precise metagenomics classification against large and up-to-date sets of reference sequences. Bioinformatics 36, i12\u2013i20 (2020). https:\/\/doi.org\/10.1093\/bioinformatics\/btaa458","journal-title":"Bioinformatics"},{"key":"30_CR19","doi-asserted-by":"publisher","first-page":"lqaf094","DOI":"10.1093\/nargab\/lqaf094","volume":"7","author":"VC Piro","year":"2025","unstructured":"Piro, V.C., Reinert, K.: ganon2: up-to-date and scalable metagenomics analysis. NAR Genom Bioinform. 7, lqaf094 (2025). https:\/\/doi.org\/10.1093\/nargab\/lqaf094","journal-title":"NAR Genom Bioinform."},{"key":"30_CR20","doi-asserted-by":"publisher","first-page":"i766","DOI":"10.1093\/bioinformatics\/bty567","volume":"34","author":"TH Dadi","year":"2018","unstructured":"Dadi, T.H., et al.: DREAM-Yara: an exact read mapper for very large databases with short update time. Bioinformatics 34, i766\u2013i772 (2018). https:\/\/doi.org\/10.1093\/bioinformatics\/bty567","journal-title":"Bioinformatics"},{"key":"30_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.isci.2021.102782","volume":"24","author":"E Seiler","year":"2021","unstructured":"Seiler, E., Mehringer, S., Darvish, M., Turc, E., Reinert, K.: Raptor: a fast and space-efficient pre-filter for querying very large collections of nucleotide sequences. IScience 24, 102782 (2021). https:\/\/doi.org\/10.1016\/j.isci.2021.102782","journal-title":"IScience"},{"key":"30_CR22","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1186\/s13059-023-02971-4","volume":"24","author":"S Mehringer","year":"2023","unstructured":"Mehringer, S., et al.: Hierarchical interleaved bloom filter: enabling ultrafast, approximate sequence queries. Genome Biol. 24, 131 (2023). https:\/\/doi.org\/10.1186\/s13059-023-02971-4","journal-title":"Genome Biol."},{"key":"30_CR23","doi-asserted-by":"publisher","first-page":"914","DOI":"10.1101\/gr.278623.123","volume":"34","author":"J-U Ulrich","year":"2024","unstructured":"Ulrich, J.-U., Renard, B.Y.: Fast and space-efficient taxonomic classification of long reads with hierarchical interleaved XOR filters. Genome Res. 34, 914\u2013924 (2024). https:\/\/doi.org\/10.1101\/gr.278623.123","journal-title":"Genome Res."},{"key":"30_CR24","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1145\/2674005.2674994","volume-title":"Proceedings of the 10th ACM International on Conference on Emerging Networking Experiments and Technologies","author":"B Fan","year":"2014","unstructured":"Fan, B., Andersen, D.G., Kaminsky, M., Mitzenmacher, M.D.: Cuckoo filter: practically better than bloom. In: Proceedings of the 10th ACM International on Conference on Emerging Networking Experiments and Technologies, pp. 75\u201388. Association for Computing Machinery, New York, NY, USA (2014). https:\/\/doi.org\/10.1145\/2674005.2674994"},{"key":"30_CR25","doi-asserted-by":"publisher","DOI":"10.7717\/peerj.10805","volume":"9","author":"R Edgar","year":"2021","unstructured":"Edgar, R.: Syncmers are more sensitive than minimizers for selecting conserved k-mers in biological sequences. PeerJ. 9, e10805 (2021). https:\/\/doi.org\/10.7717\/peerj.10805","journal-title":"PeerJ"},{"key":"30_CR26","doi-asserted-by":"publisher","first-page":"429","DOI":"10.1038\/s41592-022-01431-4","volume":"19","author":"F Meyer","year":"2022","unstructured":"Meyer, F., Fritz, A., Deng, Z.-L., et al.: Critical assessment of metagenome interpretation: the second round of challenges. Nat. Methods 19, 429\u2013440 (2022). https:\/\/doi.org\/10.1038\/s41592-022-01431-4","journal-title":"Nat. Methods"},{"key":"30_CR27","doi-asserted-by":"publisher","first-page":"1785","DOI":"10.1038\/s41596-020-00480-3","volume":"16","author":"F Meyer","year":"2021","unstructured":"Meyer, F., et al.: Tutorial: assessing metagenomics software with the CAMI benchmarking toolkit. Nat. Protoc. 16, 1785\u20131801 (2021). https:\/\/doi.org\/10.1038\/s41596-020-00480-3","journal-title":"Nat. Protoc."}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-92-3498-1_30","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T18:45:54Z","timestamp":1783968354000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-92-3498-1_30"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,14]]},"ISBN":["9789819234974","9789819234981"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-981-92-3498-1_30","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,14]]},"assertion":[{"value":"14 July 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Toronto","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canada","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 July 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2026a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2026\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}