{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T23:25:06Z","timestamp":1780615506083,"version":"3.54.1"},"reference-count":52,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2020,10,14]],"date-time":"2020-10-14T00:00:00Z","timestamp":1602633600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2020,10,14]],"date-time":"2020-10-14T00:00:00Z","timestamp":1602633600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81670462"],"award-info":[{"award-number":["81670462"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81970440"],"award-info":[{"award-number":["81970440"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81921001"],"award-info":[{"award-number":["81921001"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Peking University Basic Research Program","award":["BMU2020JC001"],"award-info":[{"award-number":["BMU2020JC001"]}]},{"name":"Peking University Clinical Scientist Program","award":["BMU2019LCKXJ001"],"award-info":[{"award-number":["BMU2019LCKXJ001"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2020,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Small open reading frame (smORF) is open reading frame with a length of less than 100 codons. Microproteins, translated from smORFs, have been found to participate in a variety of biological processes such as muscle formation and contraction, cell proliferation, and immune activation. Although previous studies have collected and annotated a large abundance of smORFs, functions of the vast majority of smORFs are still unknown. It is thus increasingly important to develop computational methods to annotate the functions of these smORFs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>In this study, we collected 617,462 unique smORFs from three studies. The expression of smORF RNAs was estimated by reannotated microarray probes. Using a speed-optimized correlation algorism, the functions of smORFs were predicted by their correlated genes with known functional annotations. After applying our method to 5 known microproteins from literatures, our method successfully predicted their functions. Further validation from the UniProt database showed that at least one function of 202 out of 270 microproteins was predicted.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>\n                      We developed a method, smORFunction, to provide function predictions of smORFs\/microproteins in at most 265 models generated from 173 datasets, including 48 tissues\/cells, 82 diseases (and normal). The tool can be available at\n                      <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/www.cuilab.cn\/smorfunction\">https:\/\/www.cuilab.cn\/smorfunction<\/jats:ext-link>\n                      <jats:underline>.<\/jats:underline>\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12859-020-03805-x","type":"journal-article","created":{"date-parts":[[2020,10,14]],"date-time":"2020-10-14T08:03:20Z","timestamp":1602662600000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["smORFunction: a tool for predicting functions of small open reading frames and microproteins"],"prefix":"10.1186","volume":"21","author":[{"given":"Xiangwen","family":"Ji","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunmei","family":"Cui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3018-5221","authenticated-orcid":false,"given":"Qinghua","family":"Cui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,10,14]]},"reference":[{"issue":"D1","key":"3805_CR1","doi-asserted-by":"publisher","first-page":"D766","DOI":"10.1093\/nar\/gky955","volume":"47","author":"A Frankish","year":"2019","unstructured":"Frankish A, Diekhans M, Ferreira AM, Johnson R, Jungreis I, Loveland J, Mudge JM, Sisu C, Wright J, Armstrong J, et al. GENCODE reference annotation for the human and mouse genomes. Nucleic Acids Res. 2019;47(D1):D766\u201373.","journal-title":"Nucleic Acids Res"},{"issue":"7644","key":"3805_CR2","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1038\/nature21374","volume":"543","author":"CC Hon","year":"2017","unstructured":"Hon CC, Ramilowski JA, Harshbarger J, Bertin N, Rackham OJ, Gough J, Denisenko E, Schmeier S, Poulsen TM, Severin J, et al. An atlas of human long non-coding RNAs with accurate 5\u2019 ends. Nature. 2017;543(7644):199\u2013204.","journal-title":"Nature"},{"issue":"22","key":"3805_CR3","doi-asserted-by":"publisher","first-page":"5866","DOI":"10.1093\/hmg\/ddu309","volume":"23","author":"I Ezkurdia","year":"2014","unstructured":"Ezkurdia I, Juan D, Rodriguez JM, Frankish A, Diekhans M, Harrow J, Vazquez J, Valencia A, Tress ML. Multiple evidence strands suggest that there may be as few as 19,000 human protein-coding genes. Hum Mol Genet. 2014;23(22):5866\u201378.","journal-title":"Hum Mol Genet"},{"issue":"9","key":"3805_CR4","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1038\/nrm.2017.58","volume":"18","author":"JP Couso","year":"2017","unstructured":"Couso JP, Patraquim P. Classification and function of small open reading frames. Nat Rev Mol Cell Biol. 2017;18(9):575\u201389.","journal-title":"Nat Rev Mol Cell Biol"},{"issue":"12","key":"3805_CR5","doi-asserted-by":"publisher","first-page":"909","DOI":"10.1038\/nchembio.1964","volume":"11","author":"A Saghatelian","year":"2015","unstructured":"Saghatelian A, Couso JP. Discovery and characterization of smORF-encoded bioactive polypeptides. Nat Chem Biol. 2015;11(12):909\u201316.","journal-title":"Nat Chem Biol"},{"key":"3805_CR6","doi-asserted-by":"publisher","first-page":"e03528","DOI":"10.7554\/eLife.03528","volume":"3","author":"JL Aspden","year":"2014","unstructured":"Aspden JL, Eyre-Walker YC, Phillips RJ, Amin U, Mumtaz MA, Brocard M, Couso JP. Extensive translation of small Open Reading Frames revealed by Poly-Ribo-Seq. Elife. 2014;3:e03528.","journal-title":"Elife"},{"issue":"D1","key":"3805_CR7","doi-asserted-by":"publisher","first-page":"D497","DOI":"10.1093\/nar\/gkx1130","volume":"46","author":"V Olexiouk","year":"2018","unstructured":"Olexiouk V, Van Criekinge W, Menschaert G. An update on sORFs.org: a repository of small ORFs identified by ribosome profiling. Nucleic Acids Res. 2018;46(D1):D497\u2013502.","journal-title":"Nucleic Acids Res"},{"issue":"4","key":"3805_CR8","first-page":"636","volume":"19","author":"Y Hao","year":"2018","unstructured":"Hao Y, Zhang L, Niu Y, Cai T, Luo J, He S, Zhang B, Zhang D, Qin Y, Yang F, et al. SmProt: a database of small proteins encoded by annotated coding and non-coding RNA loci. Brief Bioinform. 2018;19(4):636\u201343.","journal-title":"Brief Bioinform"},{"issue":"4","key":"3805_CR9","doi-asserted-by":"publisher","first-page":"458","DOI":"10.1038\/s41589-019-0425-0","volume":"16","author":"TF Martinez","year":"2020","unstructured":"Martinez TF, Chu Q, Donaldson C, Tan D, Shokhirev MN, Saghatelian A. Accurate annotation of human protein-coding small open reading frames. Nat Chem Biol. 2020;16(4):458\u201368.","journal-title":"Nat Chem Biol"},{"issue":"1","key":"3805_CR10","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1038\/nchembio.1120","volume":"9","author":"SA Slavoff","year":"2013","unstructured":"Slavoff SA, Mitchell AJ, Schwaid AG, Cabili MN, Ma J, Levin JZ, Karger AD, Budnik BA, Rinn JL, Saghatelian A. Peptidomic discovery of short open reading frame-encoded peptides in human cells. Nat Chem Biol. 2013;9(1):59\u201364.","journal-title":"Nat Chem Biol"},{"issue":"6270","key":"3805_CR11","doi-asserted-by":"publisher","first-page":"271","DOI":"10.1126\/science.aad4076","volume":"351","author":"BR Nelson","year":"2016","unstructured":"Nelson BR, Makarewich CA, Anderson DM, Winders BR, Troupes CD, Wu F, Reese AL, McAnally JR, Chen X, Kavalali ET, et al. A peptide encoded by a transcript annotated as long noncoding RNA enhances SERCA activity in muscle. Science. 2016;351(6270):271\u20135.","journal-title":"Science"},{"key":"3805_CR12","doi-asserted-by":"publisher","first-page":"15664","DOI":"10.1038\/ncomms15664","volume":"8","author":"Q Zhang","year":"2017","unstructured":"Zhang Q, Vashisht AA, O\u2019Rourke J, Corbel SY, Moran R, Romero A, Miraglia L, Zhang J, Durrant E, Schmedt C, et al. The microprotein Minion controls cell fusion and muscle formation. Nat Commun. 2017;8:15664.","journal-title":"Nat Commun"},{"issue":"34","key":"3805_CR13","doi-asserted-by":"publisher","first-page":"4750","DOI":"10.1038\/s41388-018-0281-5","volume":"37","author":"M Polycarpou-Schwarz","year":"2018","unstructured":"Polycarpou-Schwarz M, Gross M, Mestdagh P, Schott J, Grund SE, Hildenbrand C, Rom J, Aulmann S, Sinn HP, Vandesompele J, et al. The cancer-associated microprotein CASIMO1 controls cell proliferation and interacts with squalene epoxidase modulating lipid droplet formation. Oncogene. 2018;37(34):4750\u201368.","journal-title":"Oncogene"},{"issue":"4","key":"3805_CR14","doi-asserted-by":"publisher","first-page":"529","DOI":"10.1007\/s11427-019-9580-5","volume":"63","author":"W Xu","year":"2020","unstructured":"Xu W, Deng B, Lin P, Liu C, Li B, Huang Q, Zhou H, Yang J, Qu L. Ribosome profiling analysis identified a KRAS-interacting microprotein that represses oncogenic signaling in hepatocellular carcinoma cells. Sci China Life Sci. 2020;63(4):529\u201342.","journal-title":"Sci China Life Sci"},{"issue":"13","key":"3805_CR15","doi-asserted-by":"publisher","first-page":"3701","DOI":"10.1016\/j.celrep.2018.05.058","volume":"23","author":"CA Makarewich","year":"2018","unstructured":"Makarewich CA, Baskin KK, Munir AZ, Bezprozvannaya S, Sharma G, Khemtong C, Shah AM, McAnally JR, Malloy CR, Szweda LI, et al. MOXI is a mitochondrial micropeptide that enhances fatty acid beta-oxidation. Cell Rep. 2018;23(13):3701\u20139.","journal-title":"Cell Rep"},{"issue":"13","key":"3805_CR16","doi-asserted-by":"publisher","first-page":"3710","DOI":"10.1016\/j.celrep.2018.06.002","volume":"23","author":"CS Stein","year":"2018","unstructured":"Stein CS, Jadiya P, Zhang X, McLendon JM, Abouassaly GM, Witmer NH, Anderson EJ, Elrod JW, Boudreau RL. Mitoregulin: a lncRNA-encoded microprotein that supports mitochondrial supercomplexes and respiratory efficiency. Cell Rep. 2018;23(13):3710\u201320.","journal-title":"Cell Rep"},{"issue":"2","key":"3805_CR17","doi-asserted-by":"publisher","first-page":"428","DOI":"10.4049\/jimmunol.1900791","volume":"204","author":"A Bhatta","year":"2020","unstructured":"Bhatta A, Atianand M, Jiang Z, Crabtree J, Blin J, Fitzgerald KA. A Mitochondrial micropeptide is required for activation of the Nlrp3 inflammasome. J Immunol. 2020;204(2):428\u201337.","journal-title":"J Immunol"},{"issue":"11","key":"3805_CR18","doi-asserted-by":"publisher","first-page":"1361","DOI":"10.1038\/s41587-019-0298-5","volume":"37","author":"G Kustatscher","year":"2019","unstructured":"Kustatscher G, Grabowski P, Schrader TA, Passmore JB, Schrader M, Rappsilber J. Co-regulation map of the human proteome enables identification of protein functions. Nat Biotechnol. 2019;37(11):1361\u201371.","journal-title":"Nat Biotechnol"},{"key":"3805_CR19","doi-asserted-by":"publisher","first-page":"96","DOI":"10.3389\/fgene.2018.00096","volume":"9","author":"H Li","year":"2018","unstructured":"Li H, Xiao L, Zhang L, Wu J, Wei B, Sun N, Zhao Y. FSPP: a tool for genome-wide prediction of smORF-encoded peptides and their functions. Front Genet. 2018;9:96.","journal-title":"Front Genet"},{"issue":"1","key":"3805_CR20","doi-asserted-by":"publisher","first-page":"e78644","DOI":"10.1371\/journal.pone.0078644","volume":"9","author":"S Zhao","year":"2014","unstructured":"Zhao S, Fung-Leung WP, Bittner A, Ngo K, Liu X. Comparison of RNA-Seq and microarray in transcriptome profiling of activated T cells. PLoS ONE. 2014;9(1):e78644.","journal-title":"PLoS ONE"},{"issue":"3","key":"3805_CR21","doi-asserted-by":"publisher","first-page":"e17820","DOI":"10.1371\/journal.pone.0017820","volume":"6","author":"D Bottomly","year":"2011","unstructured":"Bottomly D, Walter NA, Hunter JE, Darakjian P, Kawane S, Buck KJ, Searles RP, Mooney M, McWeeney SK, Hitzemann R. Evaluating gene expression in C57BL\/6J and DBA\/2J mouse striatum using RNA-Seq and microarrays. PLoS ONE. 2011;6(3):e17820.","journal-title":"PLoS ONE"},{"issue":"3","key":"3805_CR22","doi-asserted-by":"publisher","first-page":"e18216","DOI":"10.1371\/journal.pone.0018216","volume":"6","author":"H Lempiainen","year":"2011","unstructured":"Lempiainen H, Muller A, Brasa S, Teo SS, Roloff TC, Morawiec L, Zamurovic N, Vicart A, Funhoff E, Couttet P, et al. Phenobarbital mediates an epigenetic switch at the constitutive androstane receptor (CAR) target gene Cyp2b10 in the liver of B6C3F1 mice. PLoS ONE. 2011;6(3):e18216.","journal-title":"PLoS ONE"},{"issue":"5","key":"3805_CR23","doi-asserted-by":"publisher","first-page":"802","DOI":"10.1111\/j.1365-2141.2008.07261.x","volume":"142","author":"A Kohlmann","year":"2008","unstructured":"Kohlmann A, Kipps TJ, Rassenti LZ, Downing JR, Shurtleff SA, Mills KI, Gilkes AF, Hofmann WK, Basso G, Dell\u2019orto MC, et al. An international standardization programme towards the application of gene expression profiling in routine leukaemia diagnostics: the Microarray Innovations in LEukemia study prephase. Br J Haematol. 2008;142(5):802\u20137.","journal-title":"Br J Haematol"},{"issue":"1","key":"3805_CR24","doi-asserted-by":"publisher","first-page":"4883","DOI":"10.1038\/s41467-019-12816-z","volume":"10","author":"Q Chu","year":"2019","unstructured":"Chu Q, Martinez TF, Novak SW, Donaldson CJ, Tan D, Vaughan JM, Chang T, Diedrich JK, Andrade L, Kim A, et al. Regulation of the ER stress response by a mitochondrial microprotein. Nat Commun. 2019;10(1):4883.","journal-title":"Nat Commun"},{"issue":"38","key":"3805_CR25","doi-asserted-by":"publisher","first-page":"5564","DOI":"10.1021\/acs.biochem.8b00726","volume":"57","author":"A Rathore","year":"2018","unstructured":"Rathore A, Chu Q, Tan D, Martinez TF, Donaldson CJ, Diedrich JK, Yates JR 3rd, Saghatelian A. MIEF1 microprotein regulates mitochondrial translation. Biochemistry. 2018;57(38):5564\u201375.","journal-title":"Biochemistry"},{"issue":"2","key":"3805_CR26","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1038\/nchembio.2249","volume":"13","author":"NG D'Lima","year":"2017","unstructured":"D\u2019Lima NG, Ma J, Winkler L, Chu Q, Loh KH, Corpuz EO, Budnik BA, Lykke-Andersen J, Saghatelian A, Slavoff SA. A human microprotein that interacts with the mRNA decapping complex. Nat Chem Biol. 2017;13(2):174\u201380.","journal-title":"Nat Chem Biol"},{"issue":"1\u20132","key":"3805_CR27","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1089\/10665270050081478","volume":"7","author":"Z Zhang","year":"2000","unstructured":"Zhang Z, Schwartz S, Wagner L, Miller W. A greedy algorithm for aligning DNA sequences. J Comput Biol. 2000;7(1\u20132):203\u201314.","journal-title":"J Comput Biol"},{"issue":"D1","key":"3805_CR28","doi-asserted-by":"publisher","first-page":"D506","DOI":"10.1093\/nar\/gky1049","volume":"47","author":"C UniProt","year":"2019","unstructured":"UniProt C. UniProt: a worldwide hub of protein knowledge. Nucleic Acids Res. 2019;47(D1):D506\u201315.","journal-title":"Nucleic Acids Res"},{"issue":"D1","key":"3805_CR29","doi-asserted-by":"publisher","first-page":"D607","DOI":"10.1093\/nar\/gky1131","volume":"47","author":"D Szklarczyk","year":"2019","unstructured":"Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, Simonovic M, Doncheva NT, Morris JH, Bork P, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47(D1):D607\u201313.","journal-title":"Nucleic Acids Res"},{"issue":"1","key":"3805_CR30","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1093\/bfgp\/ely031","volume":"18","author":"X Chen","year":"2019","unstructured":"Chen X, Sun YZ, Guan NN, Qu J, Huang ZA, Zhu ZX, Li JQ. Computational models for lncRNA function prediction and functional similarity calculation. Brief Funct Genom. 2019;18(1):58\u201382.","journal-title":"Brief Funct Genom"},{"issue":"6","key":"3805_CR31","doi-asserted-by":"publisher","first-page":"523","DOI":"10.1002\/yea.706","volume":"18","author":"H Hishigaki","year":"2001","unstructured":"Hishigaki H, Nakai K, Ono T, Tanigami A, Takagi T. Assessment of prediction accuracy of protein function from protein\u2013protein interaction data. Yeast. 2001;18(6):523\u201331.","journal-title":"Yeast"},{"issue":"6","key":"3805_CR32","doi-asserted-by":"publisher","first-page":"1850025","DOI":"10.1142\/S0219720018500257","volume":"16","author":"S Saha","year":"2018","unstructured":"Saha S, Prasad A, Chatterjee P, Basu S, Nasipuri M. Protein function prediction from protein-protein interaction network using gene ontology based neighborhood analysis and physico-chemical features. J Bioinform Comput Biol. 2018;16(6):1850025.","journal-title":"J Bioinform Comput Biol"},{"issue":"5","key":"3805_CR33","doi-asserted-by":"publisher","first-page":"1492","DOI":"10.1039\/c2mb05469h","volume":"8","author":"C Qiu","year":"2012","unstructured":"Qiu C, Wang D, Wang E, Cui Q. An upstream interacting context based framework for the computational inference of microRNA functions. Mol Biosyst. 2012;8(5):1492\u20138.","journal-title":"Mol Biosyst"},{"issue":"W1","key":"3805_CR34","doi-asserted-by":"publisher","first-page":"W460","DOI":"10.1093\/nar\/gkv403","volume":"43","author":"IS Vlachos","year":"2015","unstructured":"Vlachos IS, Zagganas K, Paraskevopoulou MD, Georgakilas G, Karagkouni D, Vergoulis T, Dalamagas T, Hatzigeorgiou AG. DIANA-miRPath v3.0: deciphering microRNA function with experimental support. Nucleic Acids Res. 2015;43(W1):W460\u20136.","journal-title":"Nucleic Acids Res"},{"issue":"Web Server issu","key":"3805_CR35","doi-asserted-by":"publisher","first-page":"W118","DOI":"10.1093\/nar\/gkr432","volume":"39","author":"Q Liao","year":"2011","unstructured":"Liao Q, Xiao H, Bu D, Xie C, Miao R, Luo H, Zhao G, Yu K, Zhao H, Skogerbo G, et al. ncFANs: a web server for functional annotation of long non-coding RNAs. Nucleic Acids Res. 2011;39(Web Server issue):W118\u201324.","journal-title":"Nucleic Acids Res"},{"issue":"10","key":"3805_CR36","doi-asserted-by":"publisher","first-page":"883","DOI":"10.15252\/msb.20167144","volume":"12","author":"F Edfors","year":"2016","unstructured":"Edfors F, Danielsson F, Hallstrom BM, Kall L, Lundberg E, Ponten F, Forsstrom B, Uhlen M. Gene-specific correlation of RNA and protein levels in human cells and tissues. Mol Syst Biol. 2016;12(10):883.","journal-title":"Mol Syst Biol"},{"issue":"2","key":"3805_CR37","doi-asserted-by":"publisher","first-page":"387","DOI":"10.1016\/j.cell.2019.12.023","volume":"180","author":"DP Nusinow","year":"2020","unstructured":"Nusinow DP, Szpyt J, Ghandi M, Rose CM, McDonald ER 3rd, Kalocsay M, Jane-Valbuena J, Gelfand E, Schweppe DK, Jedrychowski M, et al. Quantitative proteomics of the cancer cell line encyclopedia. Cell. 2020;180(2):387\u2013402.","journal-title":"Cell"},{"key":"3805_CR38","doi-asserted-by":"publisher","first-page":"294","DOI":"10.1186\/1471-2105-8-294","volume":"8","author":"V Sangar","year":"2007","unstructured":"Sangar V, Blankenberg DJ, Altman N, Lesk AM. Quantitative sequence-function relationships in proteins based on gene ontology. BMC Bioinform. 2007;8:294.","journal-title":"BMC Bioinform"},{"issue":"8","key":"3805_CR39","doi-asserted-by":"publisher","first-page":"852","DOI":"10.1007\/s11427-014-4692-4","volume":"57","author":"J Li","year":"2014","unstructured":"Li J, Gao C, Wang Y, Ma W, Tu J, Wang J, Chen Z, Kong W, Cui Q. A bioinformatics method for predicting long noncoding RNAs associated with vascular disease. Sci China Life Sci. 2014;57(8):852\u20137.","journal-title":"Sci China Life Sci"},{"issue":"7","key":"3805_CR40","doi-asserted-by":"publisher","first-page":"1006","DOI":"10.1093\/bioinformatics\/btt730","volume":"30","author":"H Zhao","year":"2014","unstructured":"Zhao H, Sun Z, Wang J, Huang H, Kocher JP, Wang L. CrossMap: a versatile tool for coordinate conversion between genome assemblies. Bioinformatics. 2014;30(7):1006\u20137.","journal-title":"Bioinformatics"},{"issue":"19","key":"3805_CR41","doi-asserted-by":"publisher","first-page":"2363","DOI":"10.1093\/bioinformatics\/btq431","volume":"26","author":"BS Carvalho","year":"2010","unstructured":"Carvalho BS, Irizarry RA. A framework for oligonucleotide microarray preprocessing. Bioinformatics. 2010;26(19):2363\u20137.","journal-title":"Bioinformatics"},{"issue":"17","key":"3805_CR42","doi-asserted-by":"publisher","first-page":"i884","DOI":"10.1093\/bioinformatics\/bty560","volume":"34","author":"S Chen","year":"2018","unstructured":"Chen S, Zhou Y, Chen Y, Gu J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018;34(17):i884\u201390.","journal-title":"Bioinformatics"},{"issue":"8","key":"3805_CR43","doi-asserted-by":"publisher","first-page":"907","DOI":"10.1038\/s41587-019-0201-4","volume":"37","author":"D Kim","year":"2019","unstructured":"Kim D, Paggi JM, Park C, Bennett C, Salzberg SL. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat Biotechnol. 2019;37(8):907\u201315.","journal-title":"Nat Biotechnol"},{"issue":"16","key":"3805_CR44","doi-asserted-by":"publisher","first-page":"2078","DOI":"10.1093\/bioinformatics\/btp352","volume":"25","author":"H Li","year":"2009","unstructured":"Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R. Genome project data processing S: the sequence alignment\/map format and SAMtools. Bioinformatics. 2009;25(16):2078\u20139.","journal-title":"Bioinformatics"},{"issue":"7","key":"3805_CR45","doi-asserted-by":"publisher","first-page":"923","DOI":"10.1093\/bioinformatics\/btt656","volume":"30","author":"Y Liao","year":"2014","unstructured":"Liao Y, Smyth GK, Shi W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. 2014;30(7):923\u201330.","journal-title":"Bioinformatics"},{"issue":"20","key":"3805_CR46","doi-asserted-by":"publisher","first-page":"2395","DOI":"10.1093\/bioinformatics\/btn429","volume":"24","author":"H Jiang","year":"2008","unstructured":"Jiang H, Wong WH. SeqMap: mapping massive amount of oligonucleotides to the genome. Bioinformatics. 2008;24(20):2395\u20136.","journal-title":"Bioinformatics"},{"issue":"6","key":"3805_CR47","doi-asserted-by":"publisher","first-page":"841","DOI":"10.1093\/bioinformatics\/btq033","volume":"26","author":"AR Quinlan","year":"2010","unstructured":"Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010;26(6):841\u20132.","journal-title":"Bioinformatics"},{"issue":"1","key":"3805_CR48","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1038\/75556","volume":"25","author":"M Ashburner","year":"2000","unstructured":"Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, et al. Gene ontology: tool for the unification of biology. Nat Genet. 2000;25(1):25\u20139.","journal-title":"Nat Genet"},{"issue":"D1","key":"3805_CR49","doi-asserted-by":"publisher","first-page":"D330","DOI":"10.1093\/nar\/gky1055","volume":"47","author":"The Gene Ontology Consortium","year":"2019","unstructured":"The Gene Ontology Consortium. The gene ontology resource: 20 years and still going strong. Nucleic Acids Res. 2019;47(D1):D330\u20138.","journal-title":"Nucleic Acids Res"},{"issue":"1","key":"3805_CR50","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1093\/nar\/28.1.27","volume":"28","author":"M Kanehisa","year":"2000","unstructured":"Kanehisa M, Goto S. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000;28(1):27\u201330.","journal-title":"Nucleic Acids Res"},{"issue":"D1","key":"3805_CR51","doi-asserted-by":"publisher","first-page":"D649","DOI":"10.1093\/nar\/gkx1132","volume":"46","author":"A Fabregat","year":"2018","unstructured":"Fabregat A, Jupe S, Matthews L, Sidiropoulos K, Gillespie M, Garapati P, Haw R, Jassal B, Korninger F, May B, et al. The reactome pathway knowledgebase. Nucleic Acids Res. 2018;46(D1):D649\u201355.","journal-title":"Nucleic Acids Res"},{"issue":"43","key":"3805_CR52","doi-asserted-by":"publisher","first-page":"15545","DOI":"10.1073\/pnas.0506580102","volume":"102","author":"A Subramanian","year":"2005","unstructured":"Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005;102(43):15545\u201350.","journal-title":"Proc Natl Acad Sci U S A"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-020-03805-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12859-020-03805-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-020-03805-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,10,13]],"date-time":"2021-10-13T19:31:18Z","timestamp":1634153478000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/s12859-020-03805-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,14]]},"references-count":52,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2020,12]]}},"alternative-id":["3805"],"URL":"https:\/\/doi.org\/10.1186\/s12859-020-03805-x","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-47996\/v2","asserted-by":"object"},{"id-type":"doi","id":"10.21203\/rs.3.rs-47996\/v1","asserted-by":"object"},{"id-type":"doi","id":"10.21203\/rs.3.rs-47996\/v3","asserted-by":"object"}]},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,10,14]]},"assertion":[{"value":"22 July 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 October 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 October 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Not applicable.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"455"}}