{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,20]],"date-time":"2026-04-20T18:23:25Z","timestamp":1776709405876,"version":"3.51.2"},"reference-count":52,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,9,12]],"date-time":"2024-09-12T00:00:00Z","timestamp":1726099200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2024,9,12]],"date-time":"2024-09-12T00:00:00Z","timestamp":1726099200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31860304"],"award-info":[{"award-number":["31860304"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Genomics"],"DOI":"10.1186\/s12864-024-10786-1","type":"journal-article","created":{"date-parts":[[2024,9,12]],"date-time":"2024-09-12T10:04:17Z","timestamp":1726135457000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Distribution rules of 8-mer spectra and characterization of evolution state in animal genome sequences"],"prefix":"10.1186","volume":"25","author":[{"given":"Xiaolong","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hong","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenhua","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lu","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,9,12]]},"reference":[{"key":"10786_CR1","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1080\/07391102.1986.10507643","volume":"4","author":"V Brendel","year":"1986","unstructured":"Brendel V, Beckmann JS, Trifonov EN. Linguistics of nucleotide sequences: morphology and comparison of vocabularies. J Biomol Struct Dyn. 1986;4:11\u201321.","journal-title":"J Biomol Struct Dyn"},{"key":"10786_CR2","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1016\/S0097-8485(96)00040-X","volume":"21","author":"S Audic","year":"1997","unstructured":"Audic S, Claverie JM. Detection of eukaryotic promoters using Markov transition matrices. Comp Chem. 1997;21:223\u20137.","journal-title":"Comp Chem"},{"key":"10786_CR3","doi-asserted-by":"publisher","first-page":"107623","DOI":"10.1016\/j.compbiolchem.2022.107623","volume":"97","author":"R Bhukya","year":"2022","unstructured":"Bhukya R, Kumari A, Amilpur S, Dasari CM. PPred-PCKSM: a multi-layer predictor for identifying promoter and its variants using position based features. Comput Biol Chem. 2022;97:107623.","journal-title":"Comput Biol Chem"},{"key":"10786_CR4","doi-asserted-by":"publisher","first-page":"2167","DOI":"10.1101\/gr.121905.111","volume":"21","author":"D Lee","year":"2011","unstructured":"Lee D, Karchin R, Beer MA. Discriminative prediction of mammalian enhancers from DNA sequence. Genome Res. 2011;21:2167\u201380.","journal-title":"Genome Res"},{"key":"10786_CR5","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1016\/j.jtbi.2015.09.014","volume":"387","author":"EK Mohamed Hashim","year":"2015","unstructured":"Mohamed Hashim EK, Abdullah R. Rare k-mer DNA: identification of sequence motifs and prediction of CpG island and promoter. J Theor Biol. 2015;387:88\u2013100.","journal-title":"J Theor Biol"},{"key":"10786_CR6","doi-asserted-by":"publisher","first-page":"777","DOI":"10.1007\/s10577-010-9160-9","volume":"18","author":"X Zhao","year":"2010","unstructured":"Zhao X, Pei Z, Liu J, Qin S, Cai L. Prediction of nucleosome DNA formation potential and nucleosome positioning using increment of diversity combined with quadratic discriminant analysis. Chromosome Res. 2010;18:777\u201385.","journal-title":"Chromosome Res"},{"key":"10786_CR7","doi-asserted-by":"publisher","first-page":"1474","DOI":"10.1038\/s41588-018-0207-8","volume":"50","author":"JM Kirk","year":"2018","unstructured":"Kirk JM, Kim SO, Inoue K, Smola MJ, Lee DM, Schertzer MD, Wooten JS, Baker AR, Sprague D, Collins DW, et al. Functional classification of long non-coding RNAs by k-mer content. Nat Genet. 2018;50:1474\u201382.","journal-title":"Nat Genet"},{"key":"10786_CR8","doi-asserted-by":"publisher","first-page":"16385","DOI":"10.1038\/s41598-018-34708-w","volume":"8","author":"BL Gudenas","year":"2018","unstructured":"Gudenas BL, Wang L. Prediction of LncRNA subcellular localization with deep learning from sequence features. Sci Rep. 2018;8:16385.","journal-title":"Sci Rep"},{"key":"10786_CR9","doi-asserted-by":"publisher","first-page":"2583","DOI":"10.1016\/j.ygeno.2020.02.011","volume":"112","author":"A Ahmad","year":"2020","unstructured":"Ahmad A, Lin H, Shatabda S. Locate-R: subcellular localization of long non-coding RNAs using nucleotide compositions. Genomics. 2020;112:2583\u20139.","journal-title":"Genomics"},{"key":"10786_CR10","doi-asserted-by":"publisher","first-page":"4196","DOI":"10.1093\/bioinformatics\/bty508","volume":"34","author":"Z-D Su","year":"2018","unstructured":"Su Z-D, Huang Y, Zhang Z-Y, Zhao Y-W, Wang D, Chen W, Chou K-C, Lin H. iLoc-lncRNA: predict the subcellular location of lncRNAs by incorporating octamer composition into general PseKNC. Bioinformatics. 2018;34:4196\u2013204.","journal-title":"Bioinformatics"},{"key":"10786_CR11","doi-asserted-by":"publisher","first-page":"107088","DOI":"10.1016\/j.compbiolchem.2019.107088","volume":"83","author":"S Cheng","year":"2019","unstructured":"Cheng S, Zhang L, Tan J, Gong W, Li C, Zhang X. DM-RPIs: Predicting ncRNA-protein interactions using stacked ensembling strategy. Comput Biol Chem. 2019;83:107088.","journal-title":"Comput Biol Chem"},{"key":"10786_CR12","doi-asserted-by":"publisher","first-page":"1475","DOI":"10.3390\/genes11121475","volume":"11","author":"MN Asim","year":"2020","unstructured":"Asim MN, Malik MI, Zehe C, Trygg J, Dengel A, Ahmed S. MirLocPredictor: a ConvNet-Based Multi-label MicroRNA subcellular localization predictor by incorporating k-Mer positional information. Genes. 2020;11:1475.","journal-title":"Genes"},{"key":"10786_CR13","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1007\/978-1-0716-1158-6_4","volume":"2254","author":"JM Kirk","year":"2021","unstructured":"Kirk JM, Sprague D, Calabrese JM. Classification of long noncoding RNAs by k-mer content. Methods Mol Biol. 2021;2254:41\u201360.","journal-title":"Methods Mol Biol"},{"key":"10786_CR14","doi-asserted-by":"publisher","first-page":"1750023","DOI":"10.1142\/S0219720017500238","volume":"15","author":"S Montaseri","year":"2017","unstructured":"Montaseri S, Zare-Mirakabad F, Ganjtabesh M. Evaluating the quality of SHAPE data simulated by k-mers for RNA structure prediction. J Bioinform Comput Biol. 2017;15:1750023.","journal-title":"J Bioinform Comput Biol"},{"key":"10786_CR15","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1093\/bioinformatics\/15.2.111","volume":"15","author":"C Miller","year":"1999","unstructured":"Miller C, Gurd J, Brass A. A RAPID algorithm for sequence database comparisons: application to the identification of vector contamination in the EMBL databases. Bioinformatics. 1999;15:111\u201321.","journal-title":"Bioinformatics"},{"key":"10786_CR16","doi-asserted-by":"publisher","first-page":"308","DOI":"10.1093\/bioinformatics\/bts690","volume":"29","author":"Y Liu","year":"2013","unstructured":"Liu Y, Schr\u00f6der J, Schmidt B. Musket: a multistage k-mer spectrum-based error corrector for Illumina sequence data. Bioinformatics. 2013;29:308\u201315.","journal-title":"Bioinformatics"},{"key":"10786_CR17","doi-asserted-by":"publisher","first-page":"537","DOI":"10.1186\/1471-2164-14-537","volume":"14","author":"D Williams","year":"2013","unstructured":"Williams D, Trimble WL, Shilts M, Meyer F, Ochman H. Rapid quantification of sequence repeats to resolve the size, structure and contents of bacterial genomes. BMC Genom. 2013;14:537.","journal-title":"BMC Genom"},{"key":"10786_CR18","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1186\/s13059-017-1372-2","volume":"18","author":"J Audoux","year":"2017","unstructured":"Audoux J, Philippe N, Chikhi R, Salson M, Gallopin M, Gabriel M, Le Coz J, Drouineau E, Commes T, Gautheret D. DE-kupl: exhaustive capture of biological variation in RNA-seq data through k-mer decomposition. Genome Biol. 2017;18:243.","journal-title":"Genome Biol"},{"key":"10786_CR19","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1016\/S0168-9525(00)89076-9","volume":"11","author":"S Karlin","year":"1995","unstructured":"Karlin S, Burge C. Dinucleotide relative abundance extremes: a genomic signature. Trends Genet. 1995;11:283\u201390.","journal-title":"Trends Genet"},{"key":"10786_CR20","doi-asserted-by":"publisher","first-page":"546","DOI":"10.1186\/1471-2105-9-546","volume":"9","author":"F Zhou","year":"2008","unstructured":"Zhou F, Olman V, Xu Y. Barcodes for genomes and applications. BMC Bioinform. 2008;9:546.","journal-title":"BMC Bioinform"},{"key":"10786_CR21","doi-asserted-by":"publisher","first-page":"e26296","DOI":"10.1371\/journal.pone.0026296","volume":"6","author":"C Wei","year":"2011","unstructured":"Wei C, Wang G, Chen X, Huang H, Liu B, Xu Y, Li F. Identification and typing of human enterovirus: a genomic barcode approach. PLoS ONE. 2011;6:e26296.","journal-title":"PLoS ONE"},{"key":"10786_CR22","doi-asserted-by":"publisher","first-page":"316","DOI":"10.1016\/j.gene.2016.07.010","volume":"592","author":"PK Meher","year":"2016","unstructured":"Meher PK, Sahu TK, Rao AR. Identification of species based on DNA barcode using k-mer feature vector and Random forest classifier. Gene. 2016;592:316\u201324.","journal-title":"Gene"},{"key":"10786_CR23","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1186\/s13062-015-0083-4","volume":"10","author":"D Wang","year":"2015","unstructured":"Wang D, Xu J, Yu J. KGCAK: a K-mer based database for genome-wide phylogeny and complexity evaluation. Biol Direct. 2015;10:53.","journal-title":"Biol Direct"},{"key":"10786_CR24","doi-asserted-by":"publisher","first-page":"644","DOI":"10.1186\/s12864-021-07952-0","volume":"22","author":"A Kafri","year":"2021","unstructured":"Kafri A, Chor B, Horn D. Inter-chromosomal k-mer distances. BMC Genom. 2021;22:644.","journal-title":"BMC Genom"},{"key":"10786_CR25","doi-asserted-by":"publisher","first-page":"S15","DOI":"10.1186\/1471-2105-13-S3-S15","volume":"13","author":"Y Yang","year":"2012","unstructured":"Yang Y, Nephew K, Kim S. A novel k-mer mixture logistic regression for methylation susceptibility modeling of CpG dinucleotides in human gene promoters. BMC Bioinform. 2012;13:S15.","journal-title":"BMC Bioinform"},{"key":"10786_CR26","doi-asserted-by":"publisher","first-page":"S7","DOI":"10.1186\/1471-2164-16-S11-S7","volume":"16","author":"A Subramanian","year":"2015","unstructured":"Subramanian A, Schwartz R. Reference-free inference of tumor phylogenies from single-cell sequencing data. BMC Genom. 2015;16:S7.","journal-title":"BMC Genom"},{"key":"10786_CR27","doi-asserted-by":"publisher","first-page":"5616","DOI":"10.1038\/s41598-018-23589-8","volume":"8","author":"M Sauk","year":"2018","unstructured":"Sauk M, \u017dilina O, Kurg A, Ustav EL, Peters M, Paluoja P, Roost AM, Teder H, Palta P, Brison N, et al. NIPTmer: rapid k-mer-based software package for detection of fetal aneuploidies. Sci Rep. 2018;8:5616.","journal-title":"Sci Rep"},{"key":"10786_CR28","doi-asserted-by":"publisher","first-page":"e201900336","DOI":"10.26508\/lsa.201900336","volume":"2","author":"EO Audemard","year":"2019","unstructured":"Audemard EO, Gendron P, Feghaly A, Lavall\u00e9e VP, H\u00e9bert J, Sauvageau G, Lemieux S. Targeted variant detection using unaligned RNA-Seq reads. Life Sci Alliance. 2019;2:e201900336.","journal-title":"Life Sci Alliance"},{"key":"10786_CR29","doi-asserted-by":"publisher","first-page":"zcaa034","DOI":"10.1093\/narcan\/zcaa034","volume":"2","author":"H Lee","year":"2020","unstructured":"Lee H, Shuaibi A, Bell JM, Pavlichin DS, Ji HP. Unique k-mer sequences for validating cancer-related substitution, insertion and deletion mutations. NAR Cancer. 2020;2:zcaa034.","journal-title":"NAR Cancer"},{"key":"10786_CR30","doi-asserted-by":"publisher","first-page":"giaa110","DOI":"10.1093\/gigascience\/giaa110","volume":"9","author":"M Jaillard","year":"2020","unstructured":"Jaillard M, Palmieri M, van Belkum A, Mah\u00e9 P. Interpreting k-mer-based signatures for antibiotic resistance prediction. Gigascience. 2020;9:giaa110.","journal-title":"Gigascience"},{"key":"10786_CR31","doi-asserted-by":"publisher","first-page":"100356","DOI":"10.1016\/j.imu.2020.100356","volume":"19","author":"M Naghibzadeh","year":"2020","unstructured":"Naghibzadeh M, Savari H, Savadi A, Saadati N, Mehrazin E. Developing an ultra-efficient microsatellite discoverer to find structural differences between SARS-CoV-1 and Covid-19. Inf Med Unlocked. 2020;19:100356.","journal-title":"Inf Med Unlocked"},{"key":"10786_CR32","doi-asserted-by":"publisher","first-page":"104933","DOI":"10.1016\/j.meegid.2021.104933","volume":"93","author":"Y Zhang","year":"2021","unstructured":"Zhang Y, Wen J, Li X, Li G. Exploration of hosts and transmission traits for SARS-CoV-2 based on the k-mer natural vector. Infect Genet Evol. 2021;93:104933.","journal-title":"Infect Genet Evol"},{"key":"10786_CR33","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1186\/s12859-022-04679-x","volume":"23","author":"I Sung","year":"2022","unstructured":"Sung I, Lee S, Pak M, Shin Y, Kim S. AutoCoV: tracking the early spread of COVID-19 in terms of the spatial and temporal patterns from embedding space by K-mer based deep learning. BMC Bioinform. 2022;23:149.","journal-title":"BMC Bioinform"},{"key":"10786_CR34","doi-asserted-by":"publisher","first-page":"819","DOI":"10.1089\/omi.2011.0132","volume":"15","author":"M Cserh\u00e1ti","year":"2011","unstructured":"Cserh\u00e1ti M, Tur\u00f3czy Z, Dudits D, Gy\u00f6rgyey J. The rice word landscape\u2014a detailed catalog of the rice motif content in the noncoding regions. OMICS. 2011;15:819\u201328.","journal-title":"OMICS"},{"key":"10786_CR35","doi-asserted-by":"publisher","first-page":"228","DOI":"10.1186\/s12864-021-07531-3","volume":"22","author":"M Cserhati","year":"2021","unstructured":"Cserhati M. A tail of two pandas\u2014 whole genome k-mer signature analysis of the red panda (Ailurus fulgens) and the Giant panda (Ailuropoda melanoleuca). BMC Genomics. 2021;22:228.","journal-title":"BMC Genomics"},{"key":"10786_CR36","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1016\/j.tcs.2021.06.039","volume":"894","author":"V Bonnici","year":"2021","unstructured":"Bonnici V, Franco G, Manca V. Spectral concepts in genome informational analysis. Theor Comput Sci. 2021;894:23\u201330.","journal-title":"Theor Comput Sci"},{"key":"10786_CR37","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1186\/s12859-015-0875-7","volume":"17","author":"VB Dubinkina","year":"2016","unstructured":"Dubinkina VB, Ischenko DS, Ulyantsev VI, Tyakht AV, Alexeev DG. Assessment of k-mer spectrum applicability for metagenomic dissimilarity analysis. BMC Bioinform. 2016;17:38.","journal-title":"BMC Bioinform"},{"key":"10786_CR38","doi-asserted-by":"crossref","unstructured":"Huimin X, Bailin H. Aug. Visualization of K-tuple distribution in procaryote complete genomes and their randomized counterparts. In: Proceedings IEEE Computer Society Bioinformatics Conference: 16\u201316 2002. 2002;2002:31\u201342.","DOI":"10.1109\/CSB.2002.1039327"},{"key":"10786_CR39","doi-asserted-by":"publisher","first-page":"011908","DOI":"10.1103\/PhysRevE.72.011908","volume":"72","author":"YH Chen","year":"2005","unstructured":"Chen YH, Nyeo SL, Yeh CY. Model for the distributions of k-mers in DNA sequences. Physi Rev E. 2005;72:011908.","journal-title":"Physi Rev E"},{"key":"10786_CR40","doi-asserted-by":"publisher","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. 2009;10:R108.","journal-title":"Genome Biol"},{"key":"10786_CR41","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1186\/s12862-020-01723-3","volume":"20","author":"ZH Yang","year":"2020","unstructured":"Yang ZH, Li H, Jia Y, Zheng Y, Meng H, Bao T, Li XL, Luo LF. Intrinsic laws of k-mer spectra of genome sequences and evolution mechanism of genomes. BMC Evol Biol. 2020;20:157.","journal-title":"BMC Evol Biol"},{"key":"10786_CR42","doi-asserted-by":"publisher","first-page":"483","DOI":"10.1016\/j.ygeno.2018.03.006","volume":"111","author":"Y Jia","year":"2019","unstructured":"Jia Y, Li H, Wang J, Meng H, Yang Z. Spectrum structures and biological functions of 8-mers in the human genome. Genomics. 2019;111:483\u201391.","journal-title":"Genomics"},{"key":"10786_CR43","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1007\/s10577-017-9554-z","volume":"25","author":"Y Zheng","year":"2017","unstructured":"Zheng Y, Li H, Wang Y, Meng H, Zhang Q, Zhao X. Evolutionary mechanism and biological functions of 8-mers containing CG dinucleotide in yeast. Chromosome Res. 2017;25:173\u201389.","journal-title":"Chromosome Res"},{"key":"10786_CR44","doi-asserted-by":"publisher","first-page":"634","DOI":"10.1186\/s12864-023-09747-x","volume":"24","author":"XL Li","year":"2023","unstructured":"Li XL, Li H, Yang ZH, Wu Y, Zhang MC. Exploring objective feature sets in constructing the evolution relationship of animal genome sequences. BMC Genom. 2023;24:634.","journal-title":"BMC Genom"},{"key":"10786_CR45","doi-asserted-by":"crossref","unstructured":"Rudner R, Karkas JD, Chargaff E. Separation of B. subtilis DNA into complementary strands. 3. Direct analysis. Proc. Natl. Acad. Sci. U.S.A. 1968;60:921\u2013922.","DOI":"10.1073\/pnas.60.3.921"},{"key":"10786_CR46","doi-asserted-by":"publisher","first-page":"2797","DOI":"10.1093\/nar\/21.12.2797","volume":"21","author":"VV Prabhu","year":"1993","unstructured":"Prabhu VV. Symmetry observations in long nucleotide sequences. Nucleic Acids Res. 1993;21:2797\u2013800.","journal-title":"Nucleic Acids Res"},{"key":"10786_CR47","doi-asserted-by":"crossref","unstructured":"Yamagishi MEB. Mathematical Grammar of Biology. Springer Cham; 2017.","DOI":"10.1007\/978-3-319-62689-5"},{"key":"10786_CR48","doi-asserted-by":"publisher","first-page":"e60","DOI":"10.1093\/nar\/gkab122","volume":"49","author":"Z Chen","year":"2021","unstructured":"Chen Z, Zhao P, Li C, Li F, Xiang D, Chen YZ, Akutsu T, Daly Roger J, Webb Geoffrey I, Zhao Q, et al. iLearnPlus: a comprehensive and automated machine-learning platform for nucleic acid and protein sequence analysis, prediction and visualization. Nucleic Acids Res. 2021;49:e60.","journal-title":"Nucleic Acids Res"},{"key":"10786_CR49","doi-asserted-by":"publisher","first-page":"362","DOI":"10.1093\/bioinformatics\/btv604","volume":"32","author":"B Liu","year":"2016","unstructured":"Liu B, Fang L, Long R, Lan X, Chou KC. iEnhancer-2L: a two-layer predictor for identifying enhancers and their strength by pseudo k-tuple nucleotide composition. Bioinformatics. 2016;32:362\u20139.","journal-title":"Bioinformatics"},{"key":"10786_CR50","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1093\/bioinformatics\/btx579","volume":"34","author":"B Liu","year":"2018","unstructured":"Liu B, Yang F, Huang DS, Chou KC. iPromoter-2L: a two-layer predictor for identifying promoters and their types by multi-window-based PseKNC. Bioinformatics. 2018;34:33\u201340.","journal-title":"Bioinformatics"},{"key":"10786_CR51","doi-asserted-by":"publisher","first-page":"e127","DOI":"10.1093\/nar\/gkz740","volume":"47","author":"B Liu","year":"2019","unstructured":"Liu B, Gao X, Zhang H. BioSeq-Analysis2.0: an updated platform for analyzing DNA, RNA and protein sequences at sequence level and residue level based on machine learning approaches. Nucleic Acids Res. 2019;47:e127.","journal-title":"Nucleic Acids Res"},{"key":"10786_CR52","doi-asserted-by":"publisher","first-page":"1047","DOI":"10.1093\/bib\/bbz041","volume":"21","author":"Z Chen","year":"2020","unstructured":"Chen Z, Zhao P, Li F, Marquez-Lago TT, Leier A, Revote J, Zhu Y, Powell DR, Akutsu T, Webb GI, et al. iLearn: an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence data. Brief Bioinf. 2020;21:1047\u201357.","journal-title":"Brief Bioinf"}],"container-title":["BMC Genomics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12864-024-10786-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12864-024-10786-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12864-024-10786-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,12]],"date-time":"2024-09-12T10:04:53Z","timestamp":1726135493000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcgenomics.biomedcentral.com\/articles\/10.1186\/s12864-024-10786-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,12]]},"references-count":52,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["10786"],"URL":"https:\/\/doi.org\/10.1186\/s12864-024-10786-1","relation":{},"ISSN":["1471-2164"],"issn-type":[{"value":"1471-2164","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,12]]},"assertion":[{"value":"17 January 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 September 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 September 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable to this study.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable to this study.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"855"}}