{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T22:55:02Z","timestamp":1780613702529,"version":"3.54.1"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2022,2,28]],"date-time":"2022-02-28T00:00:00Z","timestamp":1646006400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,2,28]],"date-time":"2022-02-28T00:00:00Z","timestamp":1646006400000},"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":["Nat Comput Sci"],"DOI":"10.1038\/s43588-022-00201-8","type":"journal-article","created":{"date-parts":[[2022,2,28]],"date-time":"2022-02-28T16:03:22Z","timestamp":1646064202000},"page":"78-83","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":58,"title":["Accelerating minimap2 for long-read sequencing applications on modern CPUs"],"prefix":"10.1038","volume":"2","author":[{"given":"Saurabh","family":"Kalikar","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chirag","family":"Jain","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Md","family":"Vasimuddin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7863-858X","authenticated-orcid":false,"given":"Sanchit","family":"Misra","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,2,28]]},"reference":[{"key":"201_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41467-018-08148-z","volume":"10","author":"MJ Chaisson","year":"2019","unstructured":"Chaisson, M. J. et al. Multi-platform discovery of haplotype-resolved structural variation in human genomes. Nat. Commun. 10, 1\u201316 (2019).","journal-title":"Nat. Commun."},{"key":"201_CR2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-015-0866-z","volume":"17","author":"A Conesa","year":"2016","unstructured":"Conesa, A. et al. A survey of best practices for RNA-seq data analysis. Genome Biol. 17, 1\u201319 (2016).","journal-title":"Genome Biol."},{"key":"201_CR3","doi-asserted-by":"crossref","unstructured":"Beyter, D. et al. Long-read sequencing of 3,622 Icelanders provides insight into the role of structural variants in human diseases and other traits. Nat. Genet. 53, 779\u2013886 (2021).","DOI":"10.1038\/s41588-021-00865-4"},{"key":"201_CR4","doi-asserted-by":"publisher","first-page":"737","DOI":"10.1038\/s41586-021-03451-0","volume":"592","author":"A Rhie","year":"2021","unstructured":"Rhie, A. et al. Towards complete and error-free genome assemblies of all vertebrate species. Nature 592, 737\u2013746 (2021).","journal-title":"Nature"},{"key":"201_CR5","doi-asserted-by":"crossref","unstructured":"De Coster, W., Weissensteiner, M. H. & Sedlazeck, F. J. Towards population-scale long-read sequencing. Nat. Rev. Genet. 22, 572\u2013587 (2021).","DOI":"10.1038\/s41576-021-00367-3"},{"key":"201_CR6","unstructured":"PromethION Brochure (Nanophore Technologies, 2021); https:\/\/nanoporetech.com\/sites\/default\/files\/s3\/literature\/PromethION-brochure.pdf"},{"key":"201_CR7","doi-asserted-by":"publisher","first-page":"3094","DOI":"10.1093\/bioinformatics\/bty191","volume":"34","author":"H Li","year":"2018","unstructured":"Li, H. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics 34, 3094\u20133100 (2018).","journal-title":"Bioinformatics"},{"key":"201_CR8","doi-asserted-by":"crossref","unstructured":"Guo, L., Lau, J., Ruan, Z., Wei, P. & Cong, J. Hardware acceleration of long read pairwise overlapping in genome sequencing: a race between FPGA and GPU. In 2019 IEEE 27th Annual International Symposium on Field-Programmable Custom Computing Machines 127\u2013135 (IEEE, 2019).","DOI":"10.1109\/FCCM.2019.00027"},{"key":"201_CR9","doi-asserted-by":"crossref","unstructured":"Zeni, A. et al. LOGAN: high-performance GPU-based X-drop long-read alignment. In 2020 IEEE International Parallel and Distributed Processing Symposium 462\u2013471 (IEEE, 2020).","DOI":"10.1109\/IPDPS47924.2020.00055"},{"key":"201_CR10","doi-asserted-by":"crossref","unstructured":"Feng, Z., Qiu, S., Wang, L. & Luo, Q. Accelerating long read alignment on three processors. In Proc. 48th International Conference on Parallel Processing 1\u201310 (ACM, 2019).","DOI":"10.1145\/3337821.3337918"},{"key":"201_CR11","doi-asserted-by":"publisher","first-page":"3363","DOI":"10.1093\/bioinformatics\/bth408","volume":"20","author":"M Roberts","year":"2004","unstructured":"Roberts, M., Hayes, W., Hunt, B. R., Mount, S. M. & Yorke, J. A. Reducing storage requirements for biological sequence comparison. Bioinformatics 20, 3363\u20133369 (2004).","journal-title":"Bioinformatics"},{"key":"201_CR12","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1016\/j.jda.2004.08.011","volume":"3","author":"MI Abouelhoda","year":"2005","unstructured":"Abouelhoda, M. I. & Ohlebusch, E. Chaining algorithms for multiple genome comparison. J. Discrete Algorithms 3, 321\u2013341 (2005).","journal-title":"J. Discrete Algorithms"},{"key":"201_CR13","doi-asserted-by":"crossref","unstructured":"Jain, C., Gibney, D. & Thankachan, S. V. Co-linear chaining with overlaps and gap costs. Preprint at https:\/\/www.biorxiv.org\/content\/10.1101\/2021.02.03.429492v2 (2021).","DOI":"10.1101\/2021.02.03.429492"},{"key":"201_CR14","doi-asserted-by":"crossref","unstructured":"Ho, D. et al. LISA: learned indexes for DNA sequence analysis. Preprint at https:\/\/arxiv.org\/abs\/1910.04728 (2020).","DOI":"10.1101\/2020.12.22.423964"},{"key":"201_CR15","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1101\/gr.213611.116","volume":"27","author":"VA Schneider","year":"2017","unstructured":"Schneider, V. A. et al. Evaluation of GRCh38 and de novo haploid genome assemblies demonstrates the enduring quality of the reference assembly. Genome Res. 27, 849\u2013864 (2017).","journal-title":"Genome Res."},{"key":"201_CR16","doi-asserted-by":"publisher","unstructured":"Nurk, S., Koren, S., Rhie, A., Rautiainen, M. et al. The complete sequence of a human genome. Preprint at https:\/\/doi.org\/10.1101\/2021.05.26.445798 (2021).","DOI":"10.1101\/2021.05.26.445798"},{"key":"201_CR17","doi-asserted-by":"publisher","first-page":"170","DOI":"10.1038\/s41592-020-01056-5","volume":"18","author":"H Cheng","year":"2021","unstructured":"Cheng, H., Concepcion, G. T., Feng, X., Zhang, H. & Li, H. Haplotype-resolved de novo assembly using phased assembly graphs with hifiasm. Nat. Methods 18, 170\u2013175 (2021).","journal-title":"Nat. Methods"},{"key":"201_CR18","doi-asserted-by":"publisher","first-page":"442","DOI":"10.1038\/s41587-020-00746-x","volume":"39","author":"A Payne","year":"2021","unstructured":"Payne, A. et al. Readfish enables targeted nanopore sequencing of gigabase-sized genomes. Nat. Biotechnol. 39, 442\u2013450 (2021).","journal-title":"Nat. Biotechnol."},{"key":"201_CR19","doi-asserted-by":"publisher","first-page":"431","DOI":"10.1038\/s41587-020-0731-9","volume":"39","author":"S Kovaka","year":"2021","unstructured":"Kovaka, S., Fan, Y., Ni, B., Timp, W. & Schatz, M. C. Targeted nanopore sequencing by real-time mapping of raw electrical signal with uncalled. Nat. Biotechnol. 39, 431\u2013441 (2021).","journal-title":"Nat. Biotechnol."},{"key":"201_CR20","doi-asserted-by":"publisher","unstructured":"Zhang, H. et al. Real-time mapping of nanopore raw signals. Bioinformatics https:\/\/doi.org\/10.1093\/bioinformatics\/btab264 (2021).","DOI":"10.1093\/bioinformatics\/btab264"},{"key":"201_CR21","doi-asserted-by":"crossref","unstructured":"Jain, C., Rhie, A., Hansen, N., Koren, S. & Phillippy, A.M. A long read mapping method for highly repetitive reference sequences. Preprint at https:\/\/www.biorxiv.org\/content\/10.1101\/2020.11.01.363887v1.full (2020).","DOI":"10.1101\/2020.11.01.363887"},{"key":"201_CR22","doi-asserted-by":"publisher","first-page":"461","DOI":"10.1038\/s41592-018-0001-7","volume":"15","author":"FJ Sedlazeck","year":"2018","unstructured":"Sedlazeck, F. J. et al. Accurate detection of complex structural variations using single-molecule sequencing. Nat. Methods 15, 461\u2013468 (2018).","journal-title":"Nat. Methods"},{"key":"201_CR23","doi-asserted-by":"publisher","unstructured":"Ren, J. & Chaisson, M. lRA: the long read aligner for sequences and contigs. Preprint at https:\/\/doi.org\/10.1371\/journal.pcbi.1009078 (2020).","DOI":"10.1371\/journal.pcbi.1009078"},{"key":"201_CR24","doi-asserted-by":"crossref","unstructured":"Kraska, T., Beutel, A., Chi, E.H., Dean, J. & Polyzotis, N. The case for learned index structures. In ACM International Conference on Management of Data 489\u2013504 (ACM, 2018).","DOI":"10.1145\/3183713.3196909"},{"key":"201_CR25","doi-asserted-by":"publisher","unstructured":"Galakatos, A., Markovitch, M., Binnig, C., Fonseca, R. & Kraska, T. FITing-Tree: a data-aware index structure. In SIGMOD \u201919: Proceedings of the 2019 International Conference on Management of Data 1189\u20131206 (ACM, 2019); https:\/\/doi.org\/10.1145\/3299869.3319860","DOI":"10.1145\/3299869.3319860"},{"key":"201_CR26","first-page":"1162","volume":"13","author":"P Ferragina","year":"2020","unstructured":"Ferragina, P. & Vinciguerra, G. The PGM-index: a fully-dynamic compressed learned index with provable worst-case bounds. PVLDB 13, 1162\u20131175 (2020).","journal-title":"PVLDB"},{"key":"201_CR27","doi-asserted-by":"publisher","unstructured":"Ding, J. et al. ALEX: An Updatable Adaptive Learned Index. In SIGMOD \u201820: Proceedings of the 2020 International Conference on Management of Data 969-984 (ACM, 2020). https:\/\/doi.org\/10.1145\/3318464.3389711","DOI":"10.1145\/3318464.3389711"},{"key":"201_CR28","doi-asserted-by":"publisher","unstructured":"Wu, Y., Yu, J., Tian, Y., Sidle, R. & Barber, R. Designing succinct secondary indexing mechanism by exploiting column correlations. In SIGMOD \u201919: Proceedings of the 2019 International Conference on Management of Data 1223\u20131240 (ACM, 2019). https:\/\/doi.org\/10.1145\/3299869.3319861","DOI":"10.1145\/3299869.3319861"},{"key":"201_CR29","doi-asserted-by":"publisher","first-page":"744","DOI":"10.1093\/bioinformatics\/btaa911","volume":"37","author":"M Kirsche","year":"2021","unstructured":"Kirsche, M., Das, A. & Schatz, M. C. Sapling: accelerating suffix array queries with learned data models. Bioinformatics 37, 744\u2013749 (2021).","journal-title":"Bioinformatics"},{"key":"201_CR30","doi-asserted-by":"crossref","unstructured":"Marcus, R. et al. Benchmarking learned indexes. In PVLDB Vol. 14, 1\u201313 (2021).","DOI":"10.14778\/3421424.3421425"},{"key":"201_CR31","doi-asserted-by":"publisher","unstructured":"Marcus, R., Zhang, E. & Kraska, T. CDFShop: exploring and optimizing learned index structures. In SIGMOD \u201920: Proc. 2020 ACM SIGMOD International Conference on Management of Data 2789\u20132792 (ACM, 2020); https:\/\/doi.org\/10.1145\/3318464.3384706","DOI":"10.1145\/3318464.3384706"},{"key":"201_CR32","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1186\/s12859-018-2014-8","volume":"19","author":"H Suzuki","year":"2018","unstructured":"Suzuki, H. & Kasahara, M. Introducing difference recurrence relations for faster semi-global alignment of long sequences. BMC Bioinformatics 19, 33\u201347 (2018).","journal-title":"BMC Bioinformatics"},{"key":"201_CR33","doi-asserted-by":"publisher","unstructured":"Cheng, H., Concepcion, G., Feng, X., Zhang, H. & Li, H. Human Assemblies Evaluated in the Hifiasm Paper (Zenodo, 2020); https:\/\/doi.org\/10.5281\/zenodo.4393631","DOI":"10.5281\/zenodo.4393631"},{"key":"201_CR34","doi-asserted-by":"publisher","unstructured":"Kalikar, S., Jain, C., Md, V. & Misra, S. mm2-fast Source Code Used in the Manuscript\u2014Accelerating Minimap2 for Long-Read Sequencing Applications on Modern CPUs (Zenodo, 2022); https:\/\/doi.org\/10.5281\/zenodo.5888171","DOI":"10.5281\/zenodo.5888171"},{"key":"201_CR35","doi-asserted-by":"publisher","unstructured":"Kalikar, S., Jain, C., Md, V. & Misra, S. Scripts Used for the Experiments in the Manuscript\u2014Accelerating Minimap2 for Long-Read Sequencing Applications on Modern CPUs (Zenodo, 2022); https:\/\/doi.org\/10.5281\/zenodo.5884451","DOI":"10.5281\/zenodo.5884451"}],"container-title":["Nature Computational Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s43588-022-00201-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s43588-022-00201-8","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s43588-022-00201-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,25]],"date-time":"2022-11-25T10:26:45Z","timestamp":1669372005000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s43588-022-00201-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,28]]},"references-count":35,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2022,2]]}},"alternative-id":["201"],"URL":"https:\/\/doi.org\/10.1038\/s43588-022-00201-8","relation":{},"ISSN":["2662-8457"],"issn-type":[{"value":"2662-8457","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,2,28]]},"assertion":[{"value":"20 July 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 January 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 February 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"S.K., V.M. and S.M. are employees of Intel Corporation.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}