{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,20]],"date-time":"2026-04-20T10:29:57Z","timestamp":1776680997186,"version":"3.51.2"},"reference-count":80,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,12,9]],"date-time":"2024-12-09T00:00:00Z","timestamp":1733702400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,9]],"date-time":"2024-12-09T00:00:00Z","timestamp":1733702400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Knowl Inf Syst"],"published-print":{"date-parts":[[2025,1]]},"DOI":"10.1007\/s10115-024-02292-3","type":"journal-article","created":{"date-parts":[[2024,12,9]],"date-time":"2024-12-09T03:38:28Z","timestamp":1733715508000},"page":"633-660","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A graph partitioning-based hybrid feature selection method in microarray datasets"],"prefix":"10.1007","volume":"67","author":[{"given":"Abdelali","family":"Oubaouzine","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tayeb","family":"Ouaderhman","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hasna","family":"Chamlal","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,12,9]]},"reference":[{"key":"2292_CR1","doi-asserted-by":"crossref","unstructured":"Aaboub F, Chamlal H, Ouaderhman T (2023) Analysis of the prediction performance of decision tree-based algorithms. 2023 International Conference on Decision Aid Sciences and Applications (DASA)","DOI":"10.1109\/DASA59624.2023.10286809"},{"key":"2292_CR2","doi-asserted-by":"crossref","unstructured":"Adebayo PO, Jimoh RG, Yahya WB (2023) Hybridization of data-driven threshold algorithm with fuzzy particle swarm optimization technique for gene selection in microarray data. Scientific African. e02012","DOI":"10.1016\/j.sciaf.2023.e02012"},{"key":"2292_CR3","doi-asserted-by":"crossref","first-page":"110249","DOI":"10.1016\/j.knosys.2022.110249","volume":"262","author":"M Akhavan","year":"2023","unstructured":"Akhavan M, Hasheminejad SMH (2023) A two-phase gene selection method using anomaly detection and genetic algorithm for microarray data. Knowl-Based Syst 262:110249","journal-title":"Knowl-Based Syst"},{"issue":"11","key":"2292_CR4","doi-asserted-by":"crossref","first-page":"e0166017","DOI":"10.1371\/journal.pone.0166017","volume":"11","author":"TA Alhaj","year":"2016","unstructured":"Alhaj TA, Siraj MM, Zainal A, Elshoush HT, Elhaj F (2016) Feature selection using information gain for improved structural-based alert correlation. PLoS ONE 11(11):e0166017","journal-title":"PLoS ONE"},{"key":"2292_CR5","doi-asserted-by":"crossref","first-page":"107034","DOI":"10.1016\/j.knosys.2021.107034","volume":"223","author":"OA Alomari","year":"2021","unstructured":"Alomari OA, Makhadmeh SN, Al-Betar MA, Alyasseri ZAA, Doush IA, Abasi AK, Awadallah Mohammed A, Abu ZR (2021) Gene selection for microarray data classification based on gray wolf optimizer enhanced with triz-inspired operators. Knowl-Based Syst 223:107034","journal-title":"Knowl-Based Syst"},{"issue":"12","key":"2292_CR6","doi-asserted-by":"publisher","first-page":"6745","DOI":"10.1073\/pnas.96.12.6745","volume":"96","author":"U Alon","year":"1999","unstructured":"Alon U, Barkai N, Notterman DA, Gish K, Ybarra S, Mack D, Levine AJ (1999) Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays. Proceed Nat Acad Sci 96(12):6745\u20136750. https:\/\/doi.org\/10.1073\/pnas.96.12.6745","journal-title":"Proceed Nat Acad Sci"},{"issue":"16","key":"2292_CR7","doi-asserted-by":"crossref","first-page":"13513","DOI":"10.1007\/s00521-022-07147-y","volume":"34","author":"N Alrefai","year":"2022","unstructured":"Alrefai N, Ibrahim O (2022) Optimized feature selection method using particle swarm intelligence with ensemble learning for cancer classification based on microarray datasets. Neural Comput Appl 34(16):13513\u201313528","journal-title":"Neural Comput Appl"},{"issue":"9","key":"2292_CR8","doi-asserted-by":"crossref","first-page":"e20133","DOI":"10.1016\/j.heliyon.2023.e20133","volume":"9","author":"M Alweshah","year":"2023","unstructured":"Alweshah M, Aldabbas Y, Abu-Salih B, Oqeil S, Hasan HS, Alkhalaileh S, Kassaymeh S (2023) Hybrid black widow optimization with iterated greedy algorithm for gene selection problems. Heliyon 9(9):e20133","journal-title":"Heliyon"},{"issue":"1","key":"2292_CR9","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1038\/ng765","volume":"30","author":"SA Armstrong","year":"2002","unstructured":"Armstrong SA, Staunton JE, Silverman LB, Pieters R, den Boer ML, Minden MD, Sallan SE, Lander ES, Golub TR, Korsmeyer SJ (2002) Mll translocations specify a distinct gene expression profile that distinguishes a unique leukemia. Nat Genet 30(1):41\u201347","journal-title":"Nat Genet"},{"key":"2292_CR10","doi-asserted-by":"crossref","first-page":"105766","DOI":"10.1016\/j.compbiomed.2022.105766","volume":"147","author":"S Azadifar","year":"2022","unstructured":"Azadifar S, Rostami M, Berahmand K, Moradi P, Oussalah M (2022) Graph-based relevancy-redundancy gene selection method for cancer diagnosis. Comput Biol Med 147:105766","journal-title":"Comput Biol Med"},{"issue":"1","key":"2292_CR11","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1049\/trit.2019.0028","volume":"5","author":"HS Basavegowda","year":"2020","unstructured":"Basavegowda HS, Dagnew G (2020) Deep learning approach for microarray cancer data classification. CAAI Trans Intell Technol 5(1):22\u201333","journal-title":"CAAI Trans Intell Technol"},{"issue":"4","key":"2292_CR12","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1109\/72.298224","volume":"5","author":"R Battiti","year":"1994","unstructured":"Battiti R (1994) Using mutual information for selecting features in supervised neural net learning. IEEE Trans Neural Netw 5(4):537\u2013550","journal-title":"IEEE Trans Neural Netw"},{"issue":"4","key":"2292_CR13","first-page":"391","volume":"8","author":"M Bazzi","year":"2019","unstructured":"Bazzi M, Chamlal H, Ouaderhman T et al (2019) Intelligent credit scoring system using knowledge management. IAES Int J Artif Intell 8(4):391","journal-title":"IAES Int J Artif Intell"},{"issue":"1","key":"2292_CR14","first-page":"130","volume":"30","author":"S Begum","year":"2020","unstructured":"Begum S, Sarkar R, Chakraborty D, Maulik U (2020) Identification of biomarker on biological and gene expression data using fuzzy preference based rough set. J Intell Syst 30(1):130\u2013141","journal-title":"J Intell Syst"},{"issue":"24","key":"2292_CR15","doi-asserted-by":"crossref","first-page":"13790","DOI":"10.1073\/pnas.191502998","volume":"98","author":"A Bhattacharjee","year":"2001","unstructured":"Bhattacharjee A, Richards WG, Staunton J, Li C, Monti S, Vasa P, Ladd C, Beheshti J, Bueno R, Gillette M et al (2001) Classification of human lung carcinomas by mRna expression profiling reveals distinct adenocarcinoma subclasses. Proc Natl Acad Sci 98(24):13790\u201313795","journal-title":"Proc Natl Acad Sci"},{"key":"2292_CR16","doi-asserted-by":"crossref","first-page":"106839","DOI":"10.1016\/j.csda.2019.106839","volume":"143","author":"A Bommert","year":"2020","unstructured":"Bommert A, Sun X, Bischl B, Rahnenf\u00fchrer J, Lang M (2020) Benchmark for filter methods for feature selection in high-dimensional classification data. Comput Stat Data Anal 143:106839","journal-title":"Comput Stat Data Anal"},{"key":"2292_CR17","doi-asserted-by":"crossref","unstructured":"Bruno P, Calimeri F (2019) Using heatmaps for deep learning based disease classification. In 2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), pages 1\u20137. IEEE","DOI":"10.1109\/CIBCB.2019.8791493"},{"key":"2292_CR18","doi-asserted-by":"crossref","first-page":"122958","DOI":"10.1016\/j.eswa.2023.122958","volume":"244","author":"H Chamlal","year":"2024","unstructured":"Chamlal H, Benzmane A, Ouaderhman T (2024) Elastic net-based high dimensional data selection for regression. Expert Syst Appl 244:122958","journal-title":"Expert Syst Appl"},{"key":"2292_CR19","doi-asserted-by":"crossref","first-page":"109899","DOI":"10.1016\/j.knosys.2022.109899","volume":"257","author":"H Chamlal","year":"2022","unstructured":"Chamlal H, Ouaderhman T, Aaboub F (2022) A graph based preordonnances theoretic supervised feature selection in high dimensional data. Knowl-Based Syst 257:109899","journal-title":"Knowl-Based Syst"},{"key":"2292_CR20","doi-asserted-by":"crossref","first-page":"106963","DOI":"10.1016\/j.compeleceng.2020.106963","volume":"90","author":"A Chaudhuri","year":"2021","unstructured":"Chaudhuri A, Sahu TP (2021) A hybrid feature selection method based on Binary Jaya algorithm for micro-array data classification. Comput Electr Eng 90:106963","journal-title":"Comput Electr Eng"},{"key":"2292_CR21","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/j.comcom.2021.01.005","volume":"168","author":"Z Chen","year":"2021","unstructured":"Chen Z, Chen Q, Zhang Y, Zhou L, Jiang J, Chaozhong W, Huang Z (2021) Clustering-based feature subset selection with analysis on the redundancy-complementarity dimension. Comput Commun 168:65\u201374","journal-title":"Comput Commun"},{"key":"2292_CR22","doi-asserted-by":"crossref","first-page":"106323","DOI":"10.1016\/j.knosys.2020.106323","volume":"205","author":"V Coleto-Alcudia","year":"2020","unstructured":"Coleto-Alcudia V, Vega-Rodr\u00edguez MA (2020) Artificial bee colony algorithm based on dominance (ABCD) for a hybrid gene selection method. Knowl-Based Syst 205:106323","journal-title":"Knowl-Based Syst"},{"key":"2292_CR23","doi-asserted-by":"crossref","first-page":"114012","DOI":"10.1016\/j.eswa.2020.114012","volume":"166","author":"A Dabba","year":"2021","unstructured":"Dabba A, Tari A, Meftali S, Mokhtari R (2021) Gene selection and classification of microarray data method based on mutual information and moth flame algorithm. Expert Syst Appl 166:114012","journal-title":"Expert Syst Appl"},{"key":"2292_CR24","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.eswa.2017.06.032","volume":"88","author":"AK Das","year":"2017","unstructured":"Das AK, Goswami S, Chakrabarti A, Chakraborty B (2017) A new hybrid feature selection approach using feature association map for supervised and unsupervised classification. Expert Syst Appl 88:81\u201394","journal-title":"Expert Syst Appl"},{"issue":"6","key":"2292_CR25","first-page":"3851","volume":"34","author":"H Das","year":"2022","unstructured":"Das H, Naik B, Behera HS (2022) A Jaya algorithm based wrapper method for optimal feature selection in supervised classification. J King Saud Univ-Comput Inform Sci 34(6):3851\u20133863","journal-title":"J King Saud Univ-Comput Inform Sci"},{"issue":"02","key":"2292_CR26","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1142\/S0219720005001004","volume":"3","author":"C Ding","year":"2005","unstructured":"Ding C, Peng H (2005) Minimum redundancy feature selection from microarray gene expression data. J Bioinform Comput Biol 3(02):185\u2013205","journal-title":"J Bioinform Comput Biol"},{"key":"2292_CR27","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1007\/s10115-010-0288-x","volume":"26","author":"A El Akadi","year":"2011","unstructured":"El Akadi A, Amine A, El Ouardighi A, Aboutajdine D (2011) A two-stage gene selection scheme utilizing MRMR filter and GA wrapper. Knowl Inf Syst 26:487\u2013500","journal-title":"Knowl Inf Syst"},{"key":"2292_CR28","doi-asserted-by":"crossref","first-page":"109071","DOI":"10.1016\/j.compbiomed.2024.109071","volume":"181","author":"A Esfandiari","year":"2024","unstructured":"Esfandiari A, Nasiri N (2024) Gene selection and cancer classification using interaction-based feature clustering and improved-binary bat algorithm. Comput Biol Med 181:109071","journal-title":"Comput Biol Med"},{"issue":"18","key":"2292_CR29","doi-asserted-by":"crossref","first-page":"6503","DOI":"10.1158\/0008-5472.CAN-04-0452","volume":"64","author":"WA Freije","year":"2004","unstructured":"Freije WA, Edmundo Castro-Vargas F, Fang Z, Horvath S, Cloughesy T, Liau LM, Mischel PS, Nelson SF (2004) Gene expression profiling of gliomas strongly predicts survival. Can Res 64(18):6503\u20136510","journal-title":"Can Res"},{"issue":"6","key":"2292_CR30","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1016\/j.gpb.2017.08.002","volume":"15","author":"L Gao","year":"2017","unstructured":"Gao L, Ye M, Xiaojie L, Huang D (2017) Hybrid method based on information gain and support vector machine for gene selection in cancer classification. Genom Proteom Bioinform 15(6):389\u2013395","journal-title":"Genom Proteom Bioinform"},{"issue":"1","key":"2292_CR31","first-page":"1","volume":"2","author":"BL Golden","year":"1989","unstructured":"Golden BL, Wasil EA, Harker PT (1989) The analytic hierarchy process. Appl Stud, Berlin, Heidelberg 2(1):1\u2013273","journal-title":"Appl Stud, Berlin, Heidelberg"},{"issue":"5439","key":"2292_CR32","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1126\/science.286.5439.531","volume":"286","author":"TR Golub","year":"1999","unstructured":"Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP, Coller H, Loh ML, Downing JR, Caligiuri MA et al (1999) Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286(5439):531\u2013537","journal-title":"Science"},{"key":"2292_CR33","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12859-019-3325-0","volume":"21","author":"J Guo","year":"2020","unstructured":"Guo J, Jin M, Chen Y, Liu J (2020) An embedded gene selection method using knockoffs optimizing neural network. BMC Bioinform 21:1\u201319","journal-title":"BMC Bioinform"},{"key":"2292_CR34","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.jtbi.2016.03.034","volume":"400","author":"S Guo","year":"2016","unstructured":"Guo S, Guo D, Chen L, Jiang Q (2016) A centroid-based gene selection method for microarray data classification. J Theor Biol 400:32\u201341","journal-title":"J Theor Biol"},{"key":"2292_CR35","unstructured":"Hall Mark\u00a0A (2000)Correlation-based feature selection of discrete and numeric class machine learning"},{"key":"2292_CR36","unstructured":"He X, Cai D, Niyogi P (2005) Laplacian score for feature selection. Advances in Neural Information Processing Systems. 18"},{"key":"2292_CR37","doi-asserted-by":"crossref","first-page":"64895","DOI":"10.1109\/ACCESS.2021.3075942","volume":"9","author":"EH Houssein","year":"2021","unstructured":"Houssein EH, Abdelminaam DS, Hassan HN, Al-Sayed MM, Nabil E (2021) A hybrid barnacles mating optimizer algorithm with support vector machines for gene selection of microarray cancer classification. IEEE Access 9:64895\u201364905","journal-title":"IEEE Access"},{"key":"2292_CR38","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1007\/978-3-642-48318-9_3","volume":"186","author":"CL Hwang","year":"1981","unstructured":"Hwang CL, Yoon K, Hwang CL, Yoon K (1981) Methods for multiple attribute decision making. Multip Attrib Decis Making: Methods Appl State-of-the-Art Survey 186:58\u2013191","journal-title":"Multip Attrib Decis Making: Methods Appl State-of-the-Art Survey"},{"key":"2292_CR39","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1472-6947-6-27","volume":"6","author":"P Jafari","year":"2006","unstructured":"Jafari P, Azuaje F (2006) An assessment of recently published gene expression data analyses: reporting experimental design and statistical factors. BMC Med Inform Decis Mak 6:1\u20138","journal-title":"BMC Med Inform Decis Mak"},{"key":"2292_CR40","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/j.asoc.2017.09.038","volume":"62","author":"I Jain","year":"2018","unstructured":"Jain I, Jain VK, Jain R (2018) Correlation feature selection based improved-binary particle swarm optimization for gene selection and cancer classification. Appl Soft Comput 62:203\u2013215","journal-title":"Appl Soft Comput"},{"issue":"6","key":"2292_CR41","doi-asserted-by":"crossref","first-page":"580","DOI":"10.1016\/j.knosys.2010.03.016","volume":"23","author":"SS Kannan","year":"2010","unstructured":"Kannan SS, Ramaraj N (2010) A novel hybrid feature selection via symmetrical uncertainty ranking based local memetic search algorithm. Knowl-Based Syst 23(6):580\u2013585","journal-title":"Knowl-Based Syst"},{"issue":"6","key":"2292_CR42","doi-asserted-by":"crossref","first-page":"673","DOI":"10.1038\/89044","volume":"7","author":"J Khan","year":"2001","unstructured":"Khan J, Wei JS, Ringner M, Saal LH, Ladanyi M, Westermann F, Berthold F, Schwab M, Antonescu CR, Peterson C et al (2001) Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks. Nat Med 7(6):673\u2013679","journal-title":"Nat Med"},{"key":"2292_CR43","doi-asserted-by":"crossref","first-page":"105349","DOI":"10.1016\/j.compbiomed.2022.105349","volume":"144","author":"R Kundu","year":"2022","unstructured":"Kundu R, Chattopadhyay S, Cuevas E, Sarkar R (2022) Altwoa: Altruistic whale optimization algorithm for feature selection on microarray datasets. Comput Biol Med 144:105349","journal-title":"Comput Biol Med"},{"key":"2292_CR44","doi-asserted-by":"crossref","first-page":"106994","DOI":"10.1016\/j.asoc.2020.106994","volume":"100","author":"C-M Lai","year":"2021","unstructured":"Lai C-M, Huang H-P (2021) A gene selection algorithm using simplified swarm optimization with multi-filter ensemble technique. Appl Soft Comput 100:106994","journal-title":"Appl Soft Comput"},{"key":"2292_CR45","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1016\/j.neucom.2016.08.089","volume":"218","author":"C-M Lai","year":"2016","unstructured":"Lai C-M, Yeh W-C, Chang C-Y (2016) Gene selection using information gain and improved simplified swarm optimization. Neurocomputing 218:331\u2013338","journal-title":"Neurocomputing"},{"issue":"4","key":"2292_CR46","doi-asserted-by":"crossref","first-page":"1106","DOI":"10.1109\/TCBB.2012.33","volume":"9","author":"C Lazar","year":"2012","unstructured":"Lazar C, Taminau J, Meganck S, Steenhoff D, Coletta A, Molter C, de Schaetzen V, Duque R, Bersini H, Nowe A (2012) A survey on filter techniques for feature selection in gene expression microarray analysis. IEEE\/ACM Trans Comput Biol Bioinf 9(4):1106\u20131119","journal-title":"IEEE\/ACM Trans Comput Biol Bioinf"},{"key":"2292_CR47","doi-asserted-by":"crossref","first-page":"113971","DOI":"10.1016\/j.eswa.2020.113971","volume":"166","author":"J Lee","year":"2021","unstructured":"Lee J, Choi IY, Jun C-H (2021) An efficient multivariate feature ranking method for gene selection in high-dimensional microarray data. Expert Syst Appl 166:113971","journal-title":"Expert Syst Appl"},{"key":"2292_CR48","doi-asserted-by":"crossref","first-page":"113971","DOI":"10.1016\/j.eswa.2020.113971","volume":"166","author":"J Lee","year":"2021","unstructured":"Lee J, Choi IY, Jun C-H (2021) An efficient multivariate feature ranking method for gene selection in high-dimensional microarray data. Expert Syst Appl 166:113971","journal-title":"Expert Syst Appl"},{"key":"2292_CR49","doi-asserted-by":"crossref","first-page":"2362","DOI":"10.1109\/JBHI.2024.3357979","volume":"28","author":"G Li","year":"2024","unstructured":"Li G, Zhao B, Su X, Yang Y, Hu P, Zhou X, Hu L (2024) Discovering consensus regions for interpretable identification of RNA n6-methyladenosine modification sites via graph contrastive clustering. IEEE J Biomed Health Inform 28:2362\u20132372","journal-title":"IEEE J Biomed Health Inform"},{"issue":"6","key":"2292_CR50","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3136625","volume":"50","author":"J Li","year":"2017","unstructured":"Li J, Cheng K, Wang S, Morstatter F, Trevino RP, Tang J, Liu H (2017) Feature selection: a data perspective. ACM Comput Surv (CSUR) 50(6):1\u201345","journal-title":"ACM Comput Surv (CSUR)"},{"key":"2292_CR51","doi-asserted-by":"crossref","first-page":"110250","DOI":"10.1016\/j.knosys.2022.110250","volume":"262","author":"M Li","year":"2023","unstructured":"Li M, Ke L, Wang L, Deng S, Xiang Yu (2023) A novel hybrid gene selection for tumor identification by combining multifilter integration and a recursive flower pollination search algorithm. Knowl-Based Syst 262:110250","journal-title":"Knowl-Based Syst"},{"issue":"6","key":"2292_CR52","doi-asserted-by":"crossref","first-page":"5381","DOI":"10.1007\/s11227-020-03480-y","volume":"77","author":"H-Y Lin","year":"2021","unstructured":"Lin H-Y (2021) Feature clustering and feature discretization assisting gene selection for molecular classification using fuzzy c-means and expectation-maximization algorithm. J Supercomput 77(6):5381\u20135397","journal-title":"J Supercomput"},{"issue":"5","key":"2292_CR53","doi-asserted-by":"crossref","first-page":"bbaa395","DOI":"10.1093\/bib\/bbaa395","volume":"22","author":"J Liu","year":"2021","unstructured":"Liu J, Ran S, Zhang J, Wei L (2021) Classification and gene selection of triple-negative breast cancer subtype embedding gene connectivity matrix in deep neural network. Brief Bioinform 22(5):bbaa395","journal-title":"Brief Bioinform"},{"key":"2292_CR54","unstructured":"Hall MA (2000) Correlation-based feature selection for discrete and numeric class machine learning. Proceedings of the Seventeenth International Conference on Machine Learning"},{"key":"2292_CR55","doi-asserted-by":"crossref","first-page":"564","DOI":"10.1016\/j.ins.2022.08.067","volume":"611","author":"X-A Ma","year":"2022","unstructured":"Ma X-A, Chunhua J (2022) Fuzzy information-theoretic feature selection via relevance, redundancy, and complementarity criteria. Inf Sci 611:564\u2013590","journal-title":"Inf Sci"},{"issue":"1","key":"2292_CR56","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1137\/0405004","volume":"5","author":"H Nagamochi","year":"1992","unstructured":"Nagamochi H, Ibaraki T (1992) Computing edge-connectivity in multigraphs and capacitated graphs. SIAM J Discr Math 5(1):54\u201366","journal-title":"SIAM J Discr Math"},{"key":"2292_CR57","doi-asserted-by":"crossref","first-page":"122504","DOI":"10.1016\/j.eswa.2023.122504","volume":"240","author":"T Ouaderhman","year":"2024","unstructured":"Ouaderhman T, Chamlal H, Janane FZ (2024) A new filter-based gene selection approach in the DNA microarray domain. Expert Syst Appl 240:122504","journal-title":"Expert Syst Appl"},{"issue":"3","key":"2292_CR58","doi-asserted-by":"crossref","first-page":"733","DOI":"10.23939\/mmc2023.03.733","volume":"10","author":"T Ouaderhman","year":"2023","unstructured":"Ouaderhman T, Chamlal H, Oubaouzine A (2023) Important subgraph discovery using non-dominance criterion. Math Model Comput 10(3):733\u2013747","journal-title":"Math Model Comput"},{"key":"2292_CR59","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1007\/s10618-008-0109-y","volume":"17","author":"AN Papadopoulos","year":"2008","unstructured":"Papadopoulos AN, Lyritsis A, Manolopoulos Y (2008) Skygraph: an algorithm for important subgraph discovery in relational graphs. Data Min Knowl Disc 17:57\u201376","journal-title":"Data Min Knowl Disc"},{"key":"2292_CR60","doi-asserted-by":"crossref","first-page":"110034","DOI":"10.1016\/j.asoc.2023.110034","volume":"135","author":"SK Pati","year":"2023","unstructured":"Pati SK, Banerjee A, Manna S (2023) Gene selection of microarray data using heatmap analysis and graph neural network. Appl Soft Comput 135:110034","journal-title":"Appl Soft Comput"},{"issue":"9306","key":"2292_CR61","doi-asserted-by":"crossref","first-page":"572","DOI":"10.1016\/S0140-6736(02)07746-2","volume":"359","author":"EF Petricoin","year":"2002","unstructured":"Petricoin EF, Ardekani AM, Hitt BA, Levine PJ, Fusaro VA, Steinberg SM, Mills GB, Simone C, Fishman DA, Kohn EC et al (2002) Use of proteomic patterns in serum to identify ovarian cancer. The Lancet 359(9306):572\u2013577","journal-title":"The Lancet"},{"key":"2292_CR62","doi-asserted-by":"crossref","first-page":"102228","DOI":"10.1016\/j.artmed.2021.102228","volume":"123","author":"M Rostami","year":"2022","unstructured":"Rostami M, Forouzandeh S, Berahmand K, Soltani M, Shahsavari M, Oussalah M (2022) Gene selection for microarray data classification via multi-objective graph theoretic-based method. Artif Intell Med 123:102228","journal-title":"Artif Intell Med"},{"issue":"19","key":"2292_CR63","doi-asserted-by":"crossref","first-page":"2507","DOI":"10.1093\/bioinformatics\/btm344","volume":"23","author":"Y Saeys","year":"2007","unstructured":"Saeys Y, Inza I, Larranaga P (2007) A review of feature selection techniques in bioinformatics. bioinformatics 23(19):2507\u20132517","journal-title":"bioinformatics"},{"issue":"1","key":"2292_CR64","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1038\/nm0102-68","volume":"8","author":"MA Shipp","year":"2002","unstructured":"Shipp MA, Ross KN, Tamayo P, Weng AP, Kutok JL, Aguiar RCT, Gaasenbeek M, Angelo M, Reich M, Pinkus GS et al (2002) Diffuse large b-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning. Nat Med 8(1):68\u201374","journal-title":"Nat Med"},{"issue":"2","key":"2292_CR65","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/S1535-6108(02)00030-2","volume":"1","author":"D Singh","year":"2002","unstructured":"Singh D, Febbo PG, Ross K, Jackson DG, Manola J, Ladd C, Tamayo P, Renshaw AA, D\u2019Amico AV, Richie JP et al (2002) Gene expression correlates of clinical prostate cancer behavior. Cancer Cell 1(2):203\u2013209","journal-title":"Cancer Cell"},{"key":"2292_CR66","doi-asserted-by":"crossref","first-page":"104396","DOI":"10.1016\/j.chemolab.2021.104396","volume":"217","author":"N Singh","year":"2021","unstructured":"Singh N, Singh P (2021) A hybrid ensemble-filter wrapper feature selection approach for medical data classification. Chemom Intell Lab Syst 217:104396","journal-title":"Chemom Intell Lab Syst"},{"issue":"4","key":"2292_CR67","doi-asserted-by":"crossref","first-page":"585","DOI":"10.1145\/263867.263872","volume":"44","author":"M Stoer","year":"1997","unstructured":"Stoer M, Wagner F (1997) A simple min-cut algorithm. J ACM (JACM) 44(4):585\u2013591","journal-title":"J ACM (JACM)"},{"issue":"7","key":"2292_CR68","doi-asserted-by":"crossref","first-page":"e102541","DOI":"10.1371\/journal.pone.0102541","volume":"9","author":"S Sun","year":"2014","unstructured":"Sun S, Peng Q, Shakoor A (2014) A kernel-based multivariate feature selection method for microarray data classification. PLoS ONE 9(7):e102541","journal-title":"PLoS ONE"},{"key":"2292_CR69","doi-asserted-by":"crossref","first-page":"1024","DOI":"10.1016\/j.neucom.2015.05.022","volume":"168","author":"S Tabakhi","year":"2015","unstructured":"Tabakhi S, Najafi A, Ranjbar R, Moradi P (2015) Gene selection for microarray data classification using a novel ant colony optimization. Neurocomputing 168:1024\u20131036","journal-title":"Neurocomputing"},{"key":"2292_CR70","unstructured":"Tang J, Alelyani S, Liu H (2014) Feature selection for classification: a review. Data Classification: Algorithms and Applications. 37"},{"key":"2292_CR71","doi-asserted-by":"crossref","first-page":"278","DOI":"10.1016\/j.ins.2021.02.061","volume":"565","author":"O Tarkhaneh","year":"2021","unstructured":"Tarkhaneh O, Nguyen TT, Mazaheri S (2021) A novel wrapper-based feature subset selection method using modified binary differential evolution algorithm. Inf Sci 565:278\u2013305","journal-title":"Inf Sci"},{"issue":"3","key":"2292_CR72","doi-asserted-by":"crossref","first-page":"528","DOI":"10.1016\/j.ejor.2010.02.032","volume":"206","author":"A Unler","year":"2010","unstructured":"Unler A, Murat A (2010) A discrete particle swarm optimization method for feature selection in binary classification problems. Eur J Oper Res 206(3):528\u2013539","journal-title":"Eur J Oper Res"},{"key":"2292_CR73","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.compbiomed.2016.12.002","volume":"81","author":"A Wang","year":"2017","unstructured":"Wang A, An N, Yang J, Chen G, Li L, Alterovitz G (2017) Wrapper-based gene selection with Markov blanket. Comput Biol Med 81:11\u201323","journal-title":"Comput Biol Med"},{"issue":"9","key":"2292_CR74","first-page":"101731","volume":"35","author":"Z Xu","year":"2023","unstructured":"Xu Z, Yang F, Wang H, Sun J, Zhu H, Wang S, Zhang Y (2023) CGUFS: a clustering-guided unsupervised feature selection algorithm for gene expression data. J King Saud Univ-Comput Inform Sci 35(9):101731","journal-title":"J King Saud Univ-Comput Inform Sci"},{"key":"2292_CR75","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.chemolab.2018.11.010","volume":"184","author":"C Yan","year":"2019","unstructured":"Yan C, Ma J, Luo H, Patel A (2019) Hybrid binary coral reefs optimization algorithm with simulated annealing for feature selection in high-dimensional biomedical datasets. Chemom Intell Lab Syst 184:102\u2013111","journal-title":"Chemom Intell Lab Syst"},{"issue":"2","key":"2292_CR76","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1109\/5254.671091","volume":"13","author":"J Yang","year":"1998","unstructured":"Yang J, Honavar V (1998) Feature subset selection using a genetic algorithm. IEEE Intell Syst Appl 13(2):44\u201349","journal-title":"IEEE Intell Syst Appl"},{"key":"2292_CR77","doi-asserted-by":"crossref","first-page":"1951","DOI":"10.1109\/TFUZZ.2023.3338565","volume":"32","author":"Y Yang","year":"2023","unstructured":"Yang Y, Su X, Zhao B, Li G, Hu P, Zhang J, Hu L (2023) Fuzzy-based deep attributed graph clustering. IEEE Trans Fuzzy Syst 32:1951\u20131964","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"2292_CR78","doi-asserted-by":"crossref","first-page":"789","DOI":"10.1016\/j.procs.2023.08.052","volume":"221","author":"Z Yang","year":"2023","unstructured":"Yang Z, Shi R, Quan P, Zhou R, Niu L (2023) Semi-supervised graph neural networks for graph partitioning problem. Procedia Comput Sci 221:789\u2013796","journal-title":"Procedia Comput Sci"},{"key":"2292_CR79","doi-asserted-by":"crossref","first-page":"1256","DOI":"10.1016\/j.ins.2020.09.022","volume":"546","author":"L Zheng","year":"2021","unstructured":"Zheng L, Chao F, Parthal\u00e1in NM, Zhang D, Shen Q (2021) Feature grouping and selection: a graph-based approach. Inf Sci 546:1256\u20131272","journal-title":"Inf Sci"},{"key":"2292_CR80","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1016\/j.gene.2019.04.060","volume":"706","author":"X Zheng","year":"2019","unstructured":"Zheng X, Zhu W, Tang C, Wang M (2019) Gene selection for microarray data classification via adaptive hypergraph embedded dictionary learning. Gene 706:188\u2013200","journal-title":"Gene"}],"container-title":["Knowledge and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-024-02292-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10115-024-02292-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-024-02292-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,31]],"date-time":"2025-01-31T12:05:21Z","timestamp":1738325121000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10115-024-02292-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,9]]},"references-count":80,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,1]]}},"alternative-id":["2292"],"URL":"https:\/\/doi.org\/10.1007\/s10115-024-02292-3","relation":{},"ISSN":["0219-1377","0219-3116"],"issn-type":[{"value":"0219-1377","type":"print"},{"value":"0219-3116","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,9]]},"assertion":[{"value":"30 June 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 November 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 November 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 December 2024","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no conflict of interest","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}