{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T20:46:36Z","timestamp":1776285996254,"version":"3.50.1"},"reference-count":92,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,4,19]],"date-time":"2022-04-19T00:00:00Z","timestamp":1650326400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,4,19]],"date-time":"2022-04-19T00:00:00Z","timestamp":1650326400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100001773","name":"University of New South Wales","doi-asserted-by":"publisher","award":["p23542"],"award-info":[{"award-number":["p23542"]}],"id":[{"id":"10.13039\/501100001773","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001773","name":"University of New South Wales","doi-asserted-by":"publisher","award":["p23542"],"award-info":[{"award-number":["p23542"]}],"id":[{"id":"10.13039\/501100001773","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2022,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths worldwide. Recent studies have observed causative mutations in susceptible genes related to colorectal cancer in 10 to 15% of the patients. This highlights the importance of identifying mutations for early detection of this cancer for more effective treatments among high risk individuals. Mutation is considered as the key point in cancer research. Many studies have performed cancer subtyping based on the type of frequently mutated genes, or the proportion of mutational processes. However, to the best of our knowledge, combination of these features has never been used together for this task. This highlights the potential to introduce better and more inclusive subtype classification approaches using wider range of related features to enable biomarker discovery and thus inform drug development for CRC.\n<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>In this study, we develop a new pipeline based on a novel concept called \u2018gene-motif\u2019, which merges mutated gene information with tri-nucleotide motif of mutated sites, for colorectal cancer subtype identification. We apply our pipeline to the International Cancer Genome Consortium (ICGC) CRC samples and identify, for the first time, 3131 gene-motif combinations that are significantly mutated in 536 ICGC colorectal cancer samples. Using these features, we identify seven CRC subtypes with distinguishable phenotypes and biomarkers, including unique cancer related signaling pathways, in which for most of them targeted treatment options are currently available. Interestingly, we also identify several genes that are mutated in multiple subtypes but with unique sequence contexts.\n<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusion<\/jats:title>\n                <jats:p>Our results highlight the importance of considering both the mutation type and mutated genes in identification of cancer subtypes and cancer biomarkers. The new CRC subtypes presented in this study demonstrates distinguished phenotypic properties which can be effectively used to develop new treatments. By knowing the genes and phenotypes associated with the subtypes, a personalized treatment plan can be developed that considers the specific phenotypes associated with their genomic lesion.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12859-022-04652-8","type":"journal-article","created":{"date-parts":[[2022,4,19]],"date-time":"2022-04-19T09:03:24Z","timestamp":1650359004000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Integrative analysis of mutated genes and mutational processes reveals novel mutational biomarkers in colorectal cancer"],"prefix":"10.1186","volume":"23","author":[{"given":"Hamed","family":"Dashti","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Iman","family":"Dehzangi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Masroor","family":"Bayati","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"James","family":"Breen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amin","family":"Beheshti","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nigel","family":"Lovell","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hamid R.","family":"Rabiee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hamid","family":"Alinejad-Rokny","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,4,19]]},"reference":[{"issue":"7407","key":"4652_CR1","doi-asserted-by":"publisher","first-page":"330","DOI":"10.1038\/nature11252","volume":"487","author":"Cancer Genome Atlas Network","year":"2012","unstructured":"Cancer Genome Atlas Network. Comprehensive molecular characterization of human colon and rectal cancer. Nature. 2012;487(7407):330\u20137.","journal-title":"Nature"},{"issue":"5","key":"4652_CR2","doi-asserted-by":"publisher","first-page":"614","DOI":"10.1038\/nm.3174","volume":"19","author":"EM Felipe De Sousa","year":"2013","unstructured":"Felipe De Sousa EM, et al. Poor-prognosis colon cancer is defined by a molecularly distinct subtype and develops from serrated precursor lesions. Nature Med. 2013;19(5):614.","journal-title":"Nature Med"},{"issue":"5","key":"4652_CR3","doi-asserted-by":"publisher","first-page":"619","DOI":"10.1038\/nm.3175","volume":"19","author":"A Sadanandam","year":"2013","unstructured":"Sadanandam A, et al. A colorectal cancer classification system that associates cellular phenotype and responses to therapy. Nat Med. 2013;19(5):619.","journal-title":"Nat Med"},{"issue":"5","key":"4652_CR4","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.1001453","volume":"10","author":"L Marisa","year":"2013","unstructured":"Marisa L, et al. Gene expression classification of colon cancer into molecular subtypes: characterization, validation, and prognostic value. PLoS Med. 2013;10(5): e1001453.","journal-title":"PLoS Med"},{"issue":"3","key":"4652_CR5","doi-asserted-by":"publisher","first-page":"552","DOI":"10.1002\/ijc.28387","volume":"134","author":"P Roepman","year":"2014","unstructured":"Roepman P, et al. Colorectal cancer intrinsic subtypes predict chemotherapy benefit, deficient mismatch repair and epithelial-to-mesenchymal transition. Int J Cancer. 2014;134(3):552\u201362.","journal-title":"Int J Cancer"},{"issue":"11","key":"4652_CR6","doi-asserted-by":"publisher","first-page":"1350","DOI":"10.1038\/nm.3967","volume":"21","author":"J Guinney","year":"2015","unstructured":"Guinney J, et al. The consensus molecular subtypes of colorectal cancer. Nat Med. 2015;21(11):1350.","journal-title":"Nat Med"},{"issue":"7644","key":"4652_CR7","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1038\/nature21374","volume":"543","author":"C-C Hon","year":"2017","unstructured":"Hon C-C, et al. An atlas of human long non-coding RNAs with accurate 5\u2032 ends. Nature. 2017;543(7644):199.","journal-title":"Nature"},{"issue":"12","key":"4652_CR8","doi-asserted-by":"publisher","first-page":"3205","DOI":"10.1093\/molbev\/msw205","volume":"33","author":"H Alinejad-Rokny","year":"2016","unstructured":"Alinejad-Rokny H, Anwar F, Waters SA, Davenport MP, Ebrahimi D. Source of CpG depletion in the HIV-1 genome. Mol Biol Evol. 2016;33(12):3205\u201312.","journal-title":"Mol Biol Evol"},{"issue":"4","key":"4652_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.celrep.2020.108307","volume":"33","author":"H Alinejad-Rokny","year":"2020","unstructured":"Alinejad-Rokny H, Heng JI, Forrest AR. Brain-enriched coding and long non-coding RNA genes are overrepresented in recurrent neurodevelopmental disorder CNVs. Cell Rep. 2020;33(4): 108307.","journal-title":"Cell Rep"},{"issue":"1","key":"4652_CR10","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0087679","volume":"9","author":"D Ebrahimi","year":"2014","unstructured":"Ebrahimi D, et al. Insights into the motif preference of APOBEC3 enzymes. PLoS ONE. 2014;9(1): e87679.","journal-title":"PLoS ONE"},{"issue":"24","key":"4652_CR11","doi-asserted-by":"publisher","first-page":"14310","DOI":"10.1128\/JVI.02428-14","volume":"88","author":"SL Gooneratne","year":"2014","unstructured":"Gooneratne SL, Alinejad-Rokny H, Ebrahimi D, Bohn PS, Wiseman RW, O\u2019Connor DH, Davenport MP, Kent SJ. Linking pig-tailed macaque major histocompatibility complex class I haplotypes and cytotoxic T lymphocyte escape mutations in simian immunodeficiency virus infection. J Virol. 2014;88(24):14310\u201325.","journal-title":"J Virol"},{"issue":"11","key":"4652_CR12","doi-asserted-by":"publisher","first-page":"1492","DOI":"10.1038\/s41416-018-0109-7","volume":"118","author":"ML Kuijjer","year":"2018","unstructured":"Kuijjer ML, et al. Cancer subtype identification using somatic mutation data. Br J Cancer. 2018;118(11):1492.","journal-title":"Br J Cancer"},{"issue":"1","key":"4652_CR13","doi-asserted-by":"publisher","DOI":"10.1101\/cshperspect.a001008","volume":"2","author":"M Olivier","year":"2010","unstructured":"Olivier M, Hollstein M, Hainaut P. TP53 mutations in human cancers: origins, consequences, and clinical use. Cold Spring Harbor Perspect Biol. 2010;2(1): a001008.","journal-title":"Cold Spring Harbor Perspect Biol"},{"issue":"2","key":"4652_CR14","doi-asserted-by":"publisher","first-page":"186","DOI":"10.3390\/genes12020186","volume":"12","author":"P Rajaei","year":"2021","unstructured":"Rajaei P, et al. VIRMOTIF: A user-friendly tool for viral sequence analysis. Genes. 2021;12(2):186.","journal-title":"Genes"},{"issue":"7","key":"4652_CR15","doi-asserted-by":"publisher","first-page":"3352","DOI":"10.1073\/pnas.97.7.3352","volume":"97","author":"A Rowan","year":"2000","unstructured":"Rowan A, et al. APC mutations in sporadic colorectal tumors: a mutational \u201chotspot\u201d and interdependence of the \u201ctwo hits.\u201d Proc Natl Acad Sci. 2000;97(7):3352\u20137.","journal-title":"Proc Natl Acad Sci"},{"issue":"11","key":"4652_CR16","doi-asserted-by":"publisher","first-page":"2648","DOI":"10.1093\/annonc\/mdx401","volume":"28","author":"E Sanz-Garcia","year":"2017","unstructured":"Sanz-Garcia E, et al. BRAF mutant colorectal cancer: prognosis, treatment, and new perspectives. Ann Oncol. 2017;28(11):2648\u201357.","journal-title":"Ann Oncol"},{"key":"4652_CR17","doi-asserted-by":"crossref","unstructured":"Dashti H, Dehzangi A, Bayati M, Breen J, Lovell N, Ebrahimi D, Alinejad-Rokny H. Integrative analysis of mutated genes and mutational processes reveals seven colorectal cancer subtypes. bioRxiv 2020.","DOI":"10.1101\/2020.05.18.101022"},{"issue":"2","key":"4652_CR18","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1016\/j.jcmgh.2019.04.002","volume":"8","author":"L Fennell","year":"2019","unstructured":"Fennell L, et al. Integrative genome-scale DNA methylation analysis of a large and unselected cohort reveals 5 distinct subtypes of colorectal adenocarcinomas. Cell Mol Gastroenterol Hepatol. 2019;8(2):269\u201390.","journal-title":"Cell Mol Gastroenterol Hepatol"},{"issue":"17","key":"4652_CR19","doi-asserted-by":"publisher","first-page":"4376","DOI":"10.3390\/cancers13174376","volume":"13","author":"A Ghareyazi","year":"2021","unstructured":"Ghareyazi A, et al. Whole-genome analysis of de novo somatic point mutations reveals novel mutational biomarkers in pancreatic cancer. Cancers. 2021;13(17):4376.","journal-title":"Cancers"},{"key":"4652_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.mrrev.2021.108375","volume":"787","author":"R Heidari","year":"2021","unstructured":"Heidari R, et al. A systematic review of long non-coding RNAs with a potential role in Breast Cancer. Mutat Res Rev Mutat Res. 2021;787: 108375.","journal-title":"Mutat Res Rev Mutat Res"},{"issue":"7463","key":"4652_CR21","doi-asserted-by":"publisher","first-page":"415","DOI":"10.1038\/nature12477","volume":"500","author":"LB Alexandrov","year":"2013","unstructured":"Alexandrov LB, et al. Signatures of mutational processes in human cancer. Nature. 2013;500(7463):415.","journal-title":"Nature"},{"issue":"1","key":"4652_CR22","doi-asserted-by":"publisher","first-page":"289","DOI":"10.32614\/RJ-2016-021","volume":"8","author":"L Scrucca","year":"2016","unstructured":"Scrucca L, et al. mclust 5: clustering, classification and density estimation using Gaussian finite mixture models. R J. 2016;8(1):289.","journal-title":"R J"},{"key":"4652_CR23","doi-asserted-by":"publisher","first-page":"1725","DOI":"10.1038\/s41467-018-04129-4","volume":"9","author":"Z Kan","year":"2018","unstructured":"Kan Z, et al. Multi-omics profiling of younger Asian breast cancers reveals distinctive molecular signatures. Nature Commun. 2018;9:1725.","journal-title":"Nature Commun"},{"issue":"4","key":"4652_CR24","doi-asserted-by":"publisher","first-page":"367","DOI":"10.1038\/s41587-019-0055-9","volume":"37","author":"J Zhang","year":"2019","unstructured":"Zhang J, Bajari R, Andric D, Gerthoffert F, Lepsa A, Nahal-Bose H, Stein LD, Ferretti VT. The international cancer genome consortium data portal. Nature Biotechnol. 2019;37(4):367\u20139.","journal-title":"Nature Biotechnol"},{"key":"4652_CR25","volume-title":"Probabilistic techniques in exposure assessment: a handbook for dealing with variability and uncertainty in models and inputs","author":"AC Cullen","year":"1999","unstructured":"Cullen AC, Frey HC, Frey CH. Probabilistic techniques in exposure assessment: a handbook for dealing with variability and uncertainty in models and inputs. Berlin: Springer; 1999."},{"key":"4652_CR26","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4939-2818-7","volume-title":"Vector generalized linear and additive models: with an implementation in R","author":"TW Yee","year":"2015","unstructured":"Yee TW. Vector generalized linear and additive models: with an implementation in R. Berlin: Springer; 2015."},{"key":"4652_CR27","first-page":"226","volume":"96","author":"M Ester","year":"1996","unstructured":"Ester M, et al. A density-based algorithm for discovering clusters in large spatial databases with noise. Kdd. 1996;96:226\u201331.","journal-title":"Kdd"},{"issue":"11","key":"4652_CR28","doi-asserted-by":"publisher","first-page":"205","DOI":"10.21105\/joss.00205","volume":"2","author":"L McInnes","year":"2017","unstructured":"McInnes L, Healy J, Astels S. hdbscan: hierarchical density based clustering. J Open Source Softw. 2017;2(11):205.","journal-title":"J Open Source Softw"},{"issue":"4","key":"4652_CR29","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v033.i04","volume":"33","author":"F Chang","year":"2010","unstructured":"Chang F, et al. clues: an R package for nonparametric clustering based on local shrinking. J Stat Softw. 2010;33(4):1\u201316.","journal-title":"J Stat Softw"},{"issue":"14","key":"4652_CR30","doi-asserted-by":"publisher","first-page":"22305","DOI":"10.18632\/oncotarget.15724","volume":"8","author":"T Hamada","year":"2017","unstructured":"Hamada T, Nowak JA, Ogino S. PIK3CA mutation and colorectal cancer precision medicine. Oncotarget. 2017;8(14):22305.","journal-title":"Oncotarget"},{"issue":"3","key":"4652_CR31","doi-asserted-by":"publisher","first-page":"271","DOI":"10.1002\/humu.10175","volume":"21","author":"B Iacopetta","year":"2003","unstructured":"Iacopetta B. TP53 mutation in colorectal cancer. Hum Mutat. 2003;21(3):271\u20136.","journal-title":"Hum Mutat"},{"issue":"37","key":"4652_CR32","first-page":"5171","volume":"18","author":"C Tan","year":"2012","unstructured":"Tan C, Du X. KRAS mutation testing in metastatic colorectal cancer. World J Gastroenterol. 2012;18(37):5171.","journal-title":"World J Gastroenterol"},{"issue":"10","key":"4652_CR33","doi-asserted-by":"publisher","first-page":"4060","DOI":"10.1073\/pnas.0611665104","volume":"104","author":"X Zhang","year":"2007","unstructured":"Zhang X, et al. Identification of STAT3 as a substrate of receptor protein tyrosine phosphatase T. Proc Natl Acad Sci. 2007;104(10):4060\u20134.","journal-title":"Proc Natl Acad Sci"},{"issue":"6","key":"4652_CR34","doi-asserted-by":"publisher","first-page":"779","DOI":"10.1016\/S0092-8674(00)80789-8","volume":"97","author":"Q Wu","year":"1999","unstructured":"Wu Q, Maniatis T. A striking organization of a large family of human neural cadherin-like cell adhesion genes. Cell. 1999;97(6):779\u201390.","journal-title":"Cell"},{"issue":"1","key":"4652_CR35","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1002\/cam4.335","volume":"4","author":"KH Wang","year":"2015","unstructured":"Wang KH, et al. Global methylation silencing of clustered proto-cadherin genes in cervical cancer: serving as diagnostic markers comparable to HPV. Cancer Med. 2015;4(1):43\u201355.","journal-title":"Cancer Med"},{"issue":"9","key":"4652_CR36","doi-asserted-by":"publisher","first-page":"1046","DOI":"10.1002\/humu.22611","volume":"35","author":"C Chauveau","year":"2014","unstructured":"Chauveau C, Rowell J, Ferreiro A. A rising titan: TTN review and mutation update. Hum Mutat. 2014;35(9):1046\u201359.","journal-title":"Hum Mutat"},{"issue":"1","key":"4652_CR37","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1038\/35094067","volume":"1","author":"R Fodde","year":"2001","unstructured":"Fodde R, Smits R, Clevers H. APC, signal transduction and genetic instability in colorectal cancer. Nat Rev Cancer. 2001;1(1):55\u201367.","journal-title":"Nat Rev Cancer"},{"issue":"4","key":"4652_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.heliyon.2017.e00277","volume":"3","author":"LE Peterson","year":"2017","unstructured":"Peterson LE, Kovyrshina T. Progression inference for somatic mutations in cancer. Heliyon. 2017;3(4): e00277.","journal-title":"Heliyon"},{"issue":"18","key":"4652_CR39","doi-asserted-by":"publisher","first-page":"3719","DOI":"10.1242\/jcs.03085","volume":"119","author":"H Ohno","year":"2006","unstructured":"Ohno H. Clathrin-associated adaptor protein complexes. J Cell Sci. 2006;119(18):3719\u201321.","journal-title":"J Cell Sci"},{"issue":"11","key":"4652_CR40","doi-asserted-by":"publisher","first-page":"2510","DOI":"10.1182\/blood-2011-11-393272","volume":"119","author":"SB Ting","year":"2012","unstructured":"Ting SB, et al. Asymmetric segregation and self-renewal of hematopoietic stem and progenitor cells with endocytic Ap2a2. Blood. 2012;119(11):2510\u201322.","journal-title":"Blood"},{"issue":"10","key":"4652_CR41","doi-asserted-by":"publisher","first-page":"607","DOI":"10.1038\/nrgastro.2013.120","volume":"10","author":"S Kaur","year":"2013","unstructured":"Kaur S, et al. Mucins in pancreatic cancer and its microenvironment. Nat Rev Gastroenterol Hepatol. 2013;10(10):607.","journal-title":"Nat Rev Gastroenterol Hepatol"},{"issue":"suppl_1","key":"4652_CR42","first-page":"D428","volume":"33","author":"G Joshi-Tope","year":"2005","unstructured":"Joshi-Tope G, et al. Reactome: a knowledgebase of biological pathways. Nucleic Acids Res. 2005;33(suppl_1):D428\u201332.","journal-title":"Nucleic Acids Res"},{"issue":"1","key":"4652_CR43","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1046\/j.1471-4159.2000.0750109.x","volume":"75","author":"A Kashiwa","year":"2000","unstructured":"Kashiwa A, et al. Isolation and characterization of novel presenilin binding protein. J Neurochem. 2000;75(1):109\u201316.","journal-title":"J Neurochem"},{"issue":"1","key":"4652_CR44","doi-asserted-by":"publisher","first-page":"118","DOI":"10.1523\/JNEUROSCI.3985-08.2009","volume":"29","author":"Q Chen","year":"2009","unstructured":"Chen Q, et al. Loss of modifier of cell adhesion reveals a pathway leading to axonal degeneration. J Neurosci. 2009;29(1):118\u201330.","journal-title":"J Neurosci"},{"issue":"3","key":"4652_CR45","doi-asserted-by":"publisher","first-page":"510","DOI":"10.1016\/j.cell.2008.09.043","volume":"135","author":"V Sanz-Moreno","year":"2008","unstructured":"Sanz-Moreno V, et al. Rac activation and inactivation control plasticity of tumor cell movement. Cell. 2008;135(3):510\u201323.","journal-title":"Cell"},{"issue":"2","key":"4652_CR46","doi-asserted-by":"publisher","first-page":"2059","DOI":"10.3892\/ol.2017.6457","volume":"14","author":"NN Phan","year":"2017","unstructured":"Phan NN, et al. Voltage-gated calcium channels: Novel targets for cancer therapy. Oncol Lett. 2017;14(2):2059\u201374.","journal-title":"Oncol Lett"},{"issue":"8","key":"4652_CR47","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0022645","volume":"6","author":"PJ de Koning","year":"2011","unstructured":"de Koning PJ, et al. Intracellular serine protease inhibitor SERPINB4 inhibits granzyme M-induced cell death. PLoS ONE. 2011;6(8): e22645.","journal-title":"PLoS ONE"},{"issue":"4","key":"4652_CR48","doi-asserted-by":"publisher","first-page":"1102","DOI":"10.3390\/ijms19041102","volume":"19","author":"K Izuhara","year":"2018","unstructured":"Izuhara K, et al. Squamous cell carcinoma antigen 2 (SCCA2, SERPINB4): an emerging biomarker for skin inflammatory diseases. Int J Mol Sci. 2018;19(4):1102.","journal-title":"Int J Mol Sci"},{"issue":"25","key":"4652_CR49","doi-asserted-by":"publisher","first-page":"7743","DOI":"10.1073\/pnas.1509193112","volume":"112","author":"MA Ali","year":"2015","unstructured":"Ali MA, et al. Transcriptional modulator ZBED6 affects cell cycle and growth of human colorectal cancer cells. Proc Natl Acad Sci. 2015;112(25):7743\u20138.","journal-title":"Proc Natl Acad Sci"},{"issue":"4","key":"4652_CR50","doi-asserted-by":"publisher","first-page":"1149","DOI":"10.1073\/pnas.1417064112","volume":"112","author":"K Guda","year":"2015","unstructured":"Guda K, et al. Novel recurrently mutated genes in African American colon cancers. Proc Natl Acad Sci. 2015;112(4):1149\u201354.","journal-title":"Proc Natl Acad Sci"},{"issue":"3","key":"4652_CR51","doi-asserted-by":"publisher","first-page":"565","DOI":"10.1182\/blood-2010-12-325381","volume":"118","author":"J Kinzfogl","year":"2011","unstructured":"Kinzfogl J, Hangoc G, Broxmeyer HE. Neurexophilin 1 suppresses the proliferation of hematopoietic progenitor cells. Blood. 2011;118(3):565\u201375.","journal-title":"Blood"},{"issue":"9","key":"4652_CR52","doi-asserted-by":"publisher","first-page":"872","DOI":"10.1038\/nbt.3947","volume":"35","author":"D De Rie","year":"2017","unstructured":"De Rie D, et al. An integrated expression atlas of miRNAs and their promoters in human and mouse. Nat Biotechnol. 2017;35(9):872.","journal-title":"Nat Biotechnol"},{"issue":"39","key":"4652_CR53","doi-asserted-by":"publisher","first-page":"63793","DOI":"10.18632\/oncotarget.11690","volume":"7","author":"X Mao","year":"2016","unstructured":"Mao X, et al. NKAIN2 functions as a novel tumor suppressor in prostate cancer. Oncotarget. 2016;7(39):63793.","journal-title":"Oncotarget"},{"issue":"10","key":"4652_CR54","doi-asserted-by":"publisher","first-page":"1694","DOI":"10.1080\/09168451.2018.1484271","volume":"82","author":"G Yu","year":"2018","unstructured":"Yu G, et al. The proliferation of colorectal cancer cells is suppressed by silencing of EIF3H. Biosci Biotechnol Biochem. 2018;82(10):1694\u2013701.","journal-title":"Biosci Biotechnol Biochem"},{"key":"4652_CR55","doi-asserted-by":"crossref","unstructured":"Hamidi H, Alinejad-Rokny H, Coorens T, Sanghvi R, Lindsay SJ, Rahbari R, Ebrahimi D. Signatures of mutational processes in human DNA evolution. bioRxiv. 2021.","DOI":"10.1101\/2021.01.09.426041"},{"issue":"9","key":"4652_CR56","doi-asserted-by":"publisher","first-page":"585","DOI":"10.1038\/nrg3729","volume":"15","author":"T Helleday","year":"2014","unstructured":"Helleday T, Eshtad S, Nik-Zainal S. Mechanisms underlying mutational signatures in human cancers. Nat Rev Genet. 2014;15(9):585.","journal-title":"Nat Rev Genet"},{"issue":"1","key":"4652_CR57","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-020-58107-2","volume":"10","author":"M Bayati","year":"2020","unstructured":"Bayati M, et al. CANCERSIGN: a user-friendly and robust tool for identification and classification of mutational signatures and patterns in cancer genomes. Sci Rep. 2020;10(1):1\u201311.","journal-title":"Sci Rep"},{"issue":"1","key":"4652_CR58","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1038\/75556","volume":"25","author":"M Ashburner","year":"2000","unstructured":"Ashburner M, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet. 2000;25(1):25\u20139.","journal-title":"Nat Genet"},{"issue":"D1","key":"4652_CR59","doi-asserted-by":"publisher","first-page":"D865","DOI":"10.1093\/nar\/gkw1039","volume":"45","author":"S Kohler","year":"2017","unstructured":"Kohler S, et al. The human phenotype ontology in 2017. Nucleic Acids Res. 2017;45(D1):D865-d876.","journal-title":"Nucleic Acids Res"},{"issue":"D1","key":"4652_CR60","doi-asserted-by":"publisher","first-page":"D833","DOI":"10.1093\/nar\/gkw943","volume":"45","author":"J Pinero","year":"2017","unstructured":"Pinero J, et al. DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants. Nucleic Acids Res. 2017;45(D1):D833-d839.","journal-title":"Nucleic Acids Res"},{"issue":"W1","key":"4652_CR61","doi-asserted-by":"publisher","first-page":"W130","DOI":"10.1093\/nar\/gkx356","volume":"45","author":"J Wang","year":"2017","unstructured":"Wang J, et al. WebGestalt 2017: a more comprehensive, powerful, flexible and interactive gene set enrichment analysis toolkit. Nucleic Acids Res. 2017;45(W1):W130\u20137.","journal-title":"Nucleic Acids Res"},{"issue":"12","key":"4652_CR62","doi-asserted-by":"publisher","first-page":"2684","DOI":"10.1158\/1078-0432.CCR-14-2329","volume":"21","author":"M Touat","year":"2015","unstructured":"Touat M, et al. Targeting FGFR signaling in cancer. Clin Cancer Res. 2015;21(12):2684\u201394.","journal-title":"Clin Cancer Res"},{"issue":"11","key":"4652_CR63","doi-asserted-by":"publisher","first-page":"1660","DOI":"10.1093\/carcin\/bgr189","volume":"32","author":"ML Slattery","year":"2011","unstructured":"Slattery ML, et al. Interferon-signaling pathway: associations with colon and rectal cancer risk and subsequent survival. Carcinogenesis. 2011;32(11):1660\u20137.","journal-title":"Carcinogenesis"},{"key":"4652_CR64","volume-title":"Modeling survival data: extending the Cox model","author":"TM Therneau","year":"2013","unstructured":"Therneau TM, Grambsch PM. Modeling survival data: extending the Cox model. Berlin: Springer; 2013."},{"key":"4652_CR65","unstructured":"Kassambara A et al. Package \u2018survminer\u2019. 2017."},{"issue":"7172","key":"4652_CR66","doi-asserted-by":"publisher","first-page":"1572","DOI":"10.1136\/bmj.317.7172.1572","volume":"317","author":"JM Bland","year":"1998","unstructured":"Bland JM, Altman DG. Survival probabilities (the Kaplan\u2013Meier method). BMJ. 1998;317(7172):1572\u201380.","journal-title":"BMJ"},{"issue":"2","key":"4652_CR67","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1038\/s41588-019-0572-y","volume":"52","author":"F Dietlein","year":"2020","unstructured":"Dietlein F, Weghorn D, Taylor-Weiner A, Richters A, Reardon B, Liu D, Lander ES, Van Allen EM, Sunyaev SR. Identification of cancer driver genes based on nucleotide context. Nat Genet. 2020;52(2):208\u201318.","journal-title":"Nat Genet"},{"issue":"3","key":"4652_CR68","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0058731","volume":"8","author":"AY Shull","year":"2013","unstructured":"Shull AY, et al. Somatic mutations, allele loss, and DNA methylation of the Cub and Sushi Multiple Domains 1 (CSMD1) gene reveals association with early age of diagnosis in colorectal cancer patients. PLoS ONE. 2013;8(3): e58731.","journal-title":"PLoS ONE"},{"issue":"1","key":"4652_CR69","doi-asserted-by":"publisher","first-page":"62","DOI":"10.15252\/embj.201591973","volume":"35","author":"CA Sengelaub","year":"2016","unstructured":"Sengelaub CA, et al. PTPRN2 and PLC\u03b21 promote metastatic breast cancer cell migration through PI (4, 5) P2-dependent actin remodeling. EMBO J. 2016;35(1):62\u201376.","journal-title":"EMBO J"},{"key":"4652_CR70","doi-asserted-by":"publisher","DOI":"10.1016\/j.foodchem.2020.128933","volume":"346","author":"J Sharma","year":"2021","unstructured":"Sharma J, et al. An in-silico evaluation of different bioactive molecules of tea for their inhibition potency against non structural protein-15 of SARS-CoV-2. Food Chem. 2021;346: 128933.","journal-title":"Food Chem"},{"key":"4652_CR71","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2020.104117","volume":"128","author":"VK Bhardwaj","year":"2021","unstructured":"Bhardwaj VK, et al. Evaluation of acridinedione analogs as potential SARS-CoV-2 main protease inhibitors and their comparison with repurposed anti-viral drugs. Comput Biol Med. 2021;128: 104117.","journal-title":"Comput Biol Med"},{"issue":"10","key":"4652_CR72","doi-asserted-by":"publisher","first-page":"3449","DOI":"10.1080\/07391102.2020.1766572","volume":"30","author":"VK Bhardwaj","year":"2021","unstructured":"Bhardwaj VK, et al. Identification of bioactive molecules from tea plant as SARS-CoV-2 main protease inhibitors. J Biomol Struct Dyn. 2021;30(10):3449\u201358.","journal-title":"J Biomol Struct Dyn"},{"key":"4652_CR73","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.104555","volume":"135","author":"R Singh","year":"2021","unstructured":"Singh R, et al. A computational approach for rational discovery of inhibitors for non-structural protein 1 of SARS-CoV-2. Comput Biol Med. 2021;135: 104555.","journal-title":"Comput Biol Med"},{"issue":"136","key":"4652_CR74","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.104631","volume":"2021","author":"R Singh","year":"2021","unstructured":"Singh R, et al. Identification of potential plant bioactive as SARS-CoV-2 Spike protein and human ACE2 fusion inhibitors. Comput Biol Med. 2021;2021(136): 104631.","journal-title":"Comput Biol Med"},{"issue":"6","key":"4652_CR75","doi-asserted-by":"publisher","first-page":"8933","DOI":"10.3934\/mbe.2021440","volume":"18","author":"MA Deif","year":"2021","unstructured":"Deif MA, Solyman AA, Kamarposhti MA, Band SS, Hammam RE. A deep bidirectional recurrent neural network for identification of SARS-CoV-2 from viral genome sequences. Math Biosci Eng. 2021;18(6):8933\u201350.","journal-title":"Math Biosci Eng"},{"key":"4652_CR76","doi-asserted-by":"crossref","unstructured":"Alinejad-Rokny H, Sadroddiny E, Scaria V. Machine learning and data mining techniques for medical complex data analysis. Neurocomputing. 2018;276(1).","DOI":"10.1016\/j.neucom.2017.09.027"},{"key":"4652_CR77","doi-asserted-by":"crossref","unstructured":"Alinejad-Rokny H, Ghavami R, Rabiee HR, Rezaei N, Tam KT, Forrest AR. MaxHiC: robust estimation of chromatin interaction frequency in Hi-C and capture Hi-C experiments. bioRxiv. 2020.","DOI":"10.1101\/2020.04.23.056226"},{"issue":"6","key":"4652_CR78","doi-asserted-by":"publisher","first-page":"665","DOI":"10.1166\/jbns.2013.1160","volume":"7","author":"R Javanmard","year":"2013","unstructured":"Javanmard R, et al. Proposed a new method for rules extraction using artificial neural network and artificial immune system in cancer diagnosis. J Bionanosci. 2013;7(6):665\u201372.","journal-title":"J Bionanosci"},{"key":"4652_CR79","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2020.103627","volume":"113","author":"S Shamshirband","year":"2021","unstructured":"Shamshirband S, et al. A review on deep learning approaches in healthcare systems: Taxonomies, challenges, and open issues. J Biomed Inform. 2021;113: 103627.","journal-title":"J Biomed Inform"},{"issue":"2","key":"4652_CR80","first-page":"235","volume":"35","author":"R Singh","year":"2021","unstructured":"Singh R, et al. In-silico evaluation of bioactive compounds from tea as potential SARS-CoV-2 nonstructural protein 16 inhibitors. J Tradit Complement Med. 2021;35(2):235.","journal-title":"J Tradit Complement Med"},{"issue":"5","key":"4652_CR81","first-page":"500","volume":"4","author":"L Esmaeili","year":"2012","unstructured":"Esmaeili L, et al. Hybrid recommender system for joining virtual communities. Res J Appl Sci Eng Technol. 2012;4(5):500\u20139.","journal-title":"Res J Appl Sci Eng Technol"},{"issue":"1","key":"4652_CR82","first-page":"16","volume":"7","author":"E Hasanzadeh","year":"2012","unstructured":"Hasanzadeh E, et al. Text clustering on latent semantic indexing with particle swarm optimization (PSO) algorithm. Int J Phys Sci. 2012;7(1):16\u2013120.","journal-title":"Int J Phys Sci"},{"issue":"3","key":"4652_CR83","doi-asserted-by":"publisher","first-page":"2193","DOI":"10.3934\/mbe.2020117","volume":"17","author":"M Hosseinpoor","year":"2020","unstructured":"Hosseinpoor M, et al. Proposing a novel community detection approach to identify cointeracting genomic regions. Math Biosci Eng. 2020;17(3):2193\u2013217.","journal-title":"Math Biosci Eng"},{"issue":"5","key":"4652_CR84","doi-asserted-by":"publisher","first-page":"1891","DOI":"10.3390\/app10051891","volume":"10","author":"H Niu","year":"2020","unstructured":"Niu H, et al. An ensemble of locally reliable cluster solutions. Appl Sci. 2020;10(5):1891.","journal-title":"Appl Sci"},{"issue":"2","key":"4652_CR85","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1166\/jbic.2013.1016","volume":"1","author":"H Parvin","year":"2012","unstructured":"Parvin H, et al. A heuristic scalable classifier ensemble of binary classifier ensembles. J Bioinform Intell Control. 2012;1(2):163\u201370.","journal-title":"J Bioinform Intell Control"},{"issue":"2","key":"4652_CR86","doi-asserted-by":"publisher","first-page":"37","DOI":"10.12785\/ijlms\/010204","volume":"1","author":"H Parvin","year":"2013","unstructured":"Parvin H, et al. A classifier ensemble of binary classifier ensembles. Int J Learn Manag Syst. 2013;1(2):37\u201347.","journal-title":"Int J Learn Manag Syst"},{"issue":"1","key":"4652_CR87","first-page":"51","volume":"3","author":"H Parvin","year":"2011","unstructured":"Parvin H, et al. Using clustering for generating diversity in classifier ensemble. JDCTA. 2011;3(1):51\u20137.","journal-title":"JDCTA"},{"issue":"22","key":"4652_CR88","first-page":"5121","volume":"6","author":"H Parvin","year":"2011","unstructured":"Parvin H, et al. An innovative combination of particle swarm optimization, learning automaton and great deluge algorithms for dynamic environments. Int J Phys Sci. 2011;6(22):5121\u20137.","journal-title":"Int J Phys Sci"},{"issue":"6","key":"4652_CR89","doi-asserted-by":"publisher","first-page":"673","DOI":"10.1166\/jbns.2013.1162","volume":"7","author":"H Parvin","year":"2013","unstructured":"Parvin H, et al. A new imbalanced learning and decision tree method for breast cancer diagnosis. J Bionanosci. 2013;7(6):673\u20138.","journal-title":"J Bionanosci"},{"key":"4652_CR90","doi-asserted-by":"crossref","unstructured":"Sharifrazi D et al. CNN-KCL: automatic myocarditis diagnosis using convolutional neural network combined with k-means clustering. Preprints 2020","DOI":"10.20944\/preprints202007.0650.v1"},{"issue":"1","key":"4652_CR91","doi-asserted-by":"publisher","first-page":"639","DOI":"10.1007\/s10462-020-09862-1","volume":"54","author":"MR Mahmoudi","year":"2021","unstructured":"Mahmoudi MR, et al. Consensus function based on cluster-wise two level clustering. Artif Intell Rev. 2021;54(1):639\u201365.","journal-title":"Artif Intell Rev"},{"key":"4652_CR92","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1016\/j.engappai.2014.08.005","volume":"37","author":"H Parvin","year":"2015","unstructured":"Parvin H, et al. Proposing a classifier ensemble framework based on classifier selection and decision tree. Eng Appl Artif Intell. 2015;37:34\u201342.","journal-title":"Eng Appl Artif Intell"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-022-04652-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12859-022-04652-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-022-04652-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,20]],"date-time":"2022-04-20T09:06:45Z","timestamp":1650445605000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/s12859-022-04652-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,19]]},"references-count":92,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2022,12]]}},"alternative-id":["4652"],"URL":"https:\/\/doi.org\/10.1186\/s12859-022-04652-8","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4,19]]},"assertion":[{"value":"9 July 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 March 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 April 2022","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.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing financial and non-financial interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"138"}}