{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T20:22:24Z","timestamp":1776284544595,"version":"3.50.1"},"reference-count":53,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2016,8,26]],"date-time":"2016-08-26T00:00:00Z","timestamp":1472169600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2016,8,26]],"date-time":"2016-08-26T00:00:00Z","timestamp":1472169600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"crossref","award":["14ZZ2240"],"award-info":[{"award-number":["14ZZ2240"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>DNA-binding proteins (DBPs) play fundamental roles in many biological processes. Therefore, the developing of effective computational tools for identifying DBPs is becoming highly desirable.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>In this study, we proposed an accurate method for the prediction of DBPs. Firstly, we focused on the challenge of improving DBP prediction accuracy with information solely from the sequence. Secondly, we used multiple informative features to encode the protein. These features included evolutionary conservation profile, secondary structure motifs, and physicochemical properties. Thirdly, we introduced a novel improved Binary Firefly Algorithm (BFA) to remove redundant or noisy features as well as select optimal parameters for the classifier. The experimental results of our predictor on two benchmark datasets outperformed many state-of-the-art predictors, which revealed the effectiveness of our method. The promising prediction performance on a new-compiled independent testing dataset from PDB and a large-scale dataset from UniProt proved the good generalization ability of our method. In addition, the BFA forged in this research would be of great potential in practical applications in optimization fields, especially in feature selection problems.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>A highly accurate method was proposed for the identification of DBPs. A user-friendly web-server named iDbP (identification of DNA-binding Proteins) was constructed and provided for academic use.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12859-016-1201-8","type":"journal-article","created":{"date-parts":[[2016,8,26]],"date-time":"2016-08-26T13:02:04Z","timestamp":1472216524000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Identification of DNA-binding proteins using multi-features fusion and binary firefly optimization algorithm"],"prefix":"10.1186","volume":"17","author":[{"given":"Jian","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haiting","family":"Chai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiqiang","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guifu","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2016,8,26]]},"reference":[{"key":"1201_CR1","first-page":"gkq061","volume":"15","author":"RE Langlois","year":"2010","unstructured":"Langlois RE, Lu H. Boosting the prediction and understanding of DNA-binding domains from sequence. Nucleic Acids Res. 2010;15:gkq061.","journal-title":"Nucleic Acids Res"},{"key":"1201_CR2","doi-asserted-by":"publisher","first-page":"379","DOI":"10.1146\/annurev.biophys.34.040204.144537","volume":"34","author":"A Sarai","year":"2005","unstructured":"Sarai A, Kono H. Protein-DNA recognition patterns and predictions. Annu Rev Biophys Biomol Struct. 2005;34:379\u201398.","journal-title":"Annu Rev Biophys Biomol Struct"},{"issue":"3","key":"1201_CR3","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1089\/ars.1999.1.3-255","volume":"1","author":"M Parola","year":"1999","unstructured":"Parola M, Bellomo G, Robino G, Barrera G, Dianzani MU. 4-Hydroxynonenal as a biological signal: molecular basis and pathophysiological implications. Antioxid Redox Signal. 1999;1(3):255\u201384.","journal-title":"Antioxid Redox Signal"},{"issue":"14","key":"1201_CR4","doi-asserted-by":"publisher","first-page":"4066","DOI":"10.1128\/JB.185.14.4066-4073.2003","volume":"185","author":"CC Chou","year":"2003","unstructured":"Chou CC, Lin TW, Chen CY, Wang AH. Crystal structure of the hyperthermophilic archaeal DNA-binding protein Sso10b2 at a resolution of 1.85 Angstroms. J Bacteriol. 2003;185(14):4066\u201373.","journal-title":"J Bacteriol"},{"issue":"4","key":"1201_CR5","doi-asserted-by":"crossref","first-page":"1253","DOI":"10.1093\/genetics\/141.4.1253","volume":"141","author":"K Freeman","year":"1995","unstructured":"Freeman K, Gwadz M, Shore D. Molecular and genetic analysis of the toxic effect of RAP1 overexpression in yeast. Genetics. 1995;141(4):1253\u201362.","journal-title":"Genetics"},{"issue":"12","key":"1201_CR6","doi-asserted-by":"publisher","first-page":"3978","DOI":"10.1093\/nar\/gkn332","volume":"36","author":"M Gao","year":"2008","unstructured":"Gao M, Skolnick J. DBD-Hunter: a knowledge-based method for the prediction of DNA\u2013protein interactions. Nucleic Acids Res. 2008;36(12):3978\u201392.","journal-title":"Nucleic Acids Res"},{"issue":"15","key":"1201_CR7","doi-asserted-by":"publisher","first-page":"1857","DOI":"10.1093\/bioinformatics\/btq295","volume":"26","author":"H Zhao","year":"2010","unstructured":"Zhao H, Yang Y, Zhou Y. Structure-based prediction of DNA-binding proteins by structural alignment and a volume-fraction corrected DFIRE-based energy function. Bioinformatics. 2010;26(15):1857\u201363.","journal-title":"Bioinformatics"},{"issue":"4","key":"1201_CR8","doi-asserted-by":"publisher","first-page":"1040","DOI":"10.1016\/j.jmb.2009.02.023","volume":"387","author":"G Nimrod","year":"2009","unstructured":"Nimrod G, Szil\u00e1gyi A, Leslie C, Ben-Tal N. Identification of DNA-binding proteins using structural, electrostatic and evolutionary features. J Mol Biol. 2009;387(4):1040\u201353.","journal-title":"J Mol Biol"},{"issue":"1","key":"1201_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1471-2105-8-463","volume":"8","author":"M Kumar","year":"2007","unstructured":"Kumar M, Gromiha MM, Raghava GP. Identification of DNA-binding proteins using support vector machines and evolutionary profiles. BMC Bioinformatics. 2007;8(1):1.","journal-title":"BMC Bioinformatics"},{"issue":"6","key":"1201_CR10","doi-asserted-by":"publisher","first-page":"679","DOI":"10.1080\/07391102.2009.10507281","volume":"26","author":"KK Kumar","year":"2009","unstructured":"Kumar KK, Pugalenthi G, Suganthan PN. DNA-Prot: identification of DNA binding proteins from protein sequence information using random forest. J Biomol Struct Dynam. 2009;26(6):679\u201386.","journal-title":"J Biomol Struct Dynam"},{"issue":"9","key":"1201_CR11","doi-asserted-by":"publisher","first-page":"e24756","DOI":"10.1371\/journal.pone.0024756","volume":"6","author":"WZ Lin","year":"2011","unstructured":"Lin WZ, Fang JA, Xiao X, Chou KC. iDNA-Prot: identification of DNA binding proteins using random forest with grey model. PLoS One. 2011;6(9):e24756.","journal-title":"PLoS One"},{"issue":"1","key":"1201_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1471-2105-15-298","volume":"15","author":"L Song","year":"2014","unstructured":"Song L, Li D, Zeng X, Wu Y, Guo L, Zou Q. nDNA-prot: identification of DNA-binding proteins based on unbalanced classification. BMC Bioinformatics. 2014;15(1):1.","journal-title":"BMC Bioinformatics"},{"key":"1201_CR13","doi-asserted-by":"crossref","unstructured":"Xu R, Zhou J, Liu B, Yao L, He Y, Zou Q, Wang X. enDNA-Prot: identification of DNA-binding proteins by applying ensemble learning. BioMed Res Int. 2014.","DOI":"10.1155\/2014\/294279"},{"issue":"1","key":"1201_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2013\/191586","volume":"14","author":"C Zou","year":"2013","unstructured":"Zou C, Gong J, Li H. An improved sequence based prediction protocol for DNA-binding proteins using SVM and comprehensive feature analysis. BMC Bioinformatics. 2013;14(1):1.","journal-title":"BMC Bioinformatics"},{"issue":"1","key":"1201_CR15","doi-asserted-by":"publisher","first-page":"e86703","DOI":"10.1371\/journal.pone.0086703","volume":"9","author":"W Lou","year":"2014","unstructured":"Lou W, Wang X, Chen F, Chen Y, Jiang B, Zhang H. Sequence based prediction of DNA-binding proteins based on hybrid feature selection using random forest and Gaussian naive Bayes. PLoS One. 2014;9(1):e86703.","journal-title":"PLoS One"},{"key":"1201_CR16","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1146\/annurev-biochem-060408-091030","volume":"79","author":"R Rohs","year":"2010","unstructured":"Rohs R, Jin X, West SM, Joshi R, Honig B, Mann RS. Origins of specificity in protein-DNA recognition. Annu Rev Biochem. 2010;79:233.","journal-title":"Annu Rev Biochem"},{"issue":"1","key":"1201_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.ab.2007.07.006","volume":"370","author":"KC Chou","year":"2007","unstructured":"Chou KC, Shen HB. Recent progress in protein subcellular location prediction. Anal Biochem. 2007;370(1):1\u201316.","journal-title":"Anal Biochem"},{"issue":"suppl 2","key":"1201_CR18","doi-asserted-by":"publisher","first-page":"W94","DOI":"10.1093\/nar\/gki402","volume":"33","author":"G Wang","year":"2005","unstructured":"Wang G, Dunbrack RL. PISCES: recent improvements to a PDB sequence culling server. Nucleic Acids Res. 2005;33 suppl 2:W94\u20138.","journal-title":"Nucleic Acids Res"},{"issue":"1","key":"1201_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13040-014-0034-0","volume":"8","author":"J Zhang","year":"2015","unstructured":"Zhang J, Chen W, Sun P, Zhao X, Ma Z. Prediction of protein solvent accessibility using PSO-SVR with multiple sequence-derived features and weighted sliding window scheme. BioData Min. 2015;8(1):1\u201315.","journal-title":"BioData Min"},{"key":"1201_CR20","doi-asserted-by":"crossref","unstructured":"Zhang J, Zhao X, Sun P, Gao B, Ma Z. Conformational B-cell epitopes prediction from sequences using cost-sensitive ensemble classifiers and spatial clustering. BioMed Res Int. 2014.","DOI":"10.1155\/2014\/689219"},{"key":"1201_CR21","doi-asserted-by":"publisher","first-page":"3389","DOI":"10.1093\/nar\/25.17.3389","volume":"25","author":"SF Altschul","year":"1997","unstructured":"Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 1997;25:3389\u2013402.","journal-title":"Nucleic Acids Res"},{"issue":"11","key":"1201_CR22","doi-asserted-by":"publisher","first-page":"770","DOI":"10.1038\/nrg3296","volume":"13","author":"ML Bochman","year":"2012","unstructured":"Bochman ML, Paeschke K, Zakian VA. DNA secondary structures: stability and function of G-quadruplex structures. Nat Rev Genet. 2012;13(11):770\u201380.","journal-title":"Nat Rev Genet"},{"key":"1201_CR23","doi-asserted-by":"crossref","unstructured":"Greive SJ, Fung HK, Chechik M, Jenkins HT, Weitzel SE, Aguiar PM, Brentnall AS, Glousieau M, Gladyshev GV, Potts JR, Antson AA. DNA recognition for virus assembly through multiple sequence-independent interactions with a helix-turn-helix motif. Nucleic Acids Res. 2016;44(2):776-789.","DOI":"10.1093\/nar\/gkv1467"},{"issue":"2","key":"1201_CR24","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1006\/jmbi.1999.3091","volume":"292","author":"DT Jones","year":"1999","unstructured":"Jones DT. Protein secondary structure prediction based on position-specific scoring matrices. J Mol Biol. 1999;292(2):195\u2013202.","journal-title":"J Mol Biol"},{"issue":"13","key":"1201_CR25","doi-asserted-by":"publisher","first-page":"1616","DOI":"10.1093\/bioinformatics\/btq253","volume":"26","author":"ZP Liu","year":"2010","unstructured":"Liu ZP, Wu LY, Wang Y, Zhang XS, Chen L. Prediction of protein\u2013RNA binding sites by a random forest method with combined features. Bioinformatics. 2010;26(13):1616\u201322.","journal-title":"Bioinformatics"},{"issue":"3","key":"1201_CR26","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1002\/prot.20433","volume":"60","author":"AJ Bordner","year":"2005","unstructured":"Bordner AJ, Abagyan R. Statistical analysis and prediction of protein\u2013protein interfaces. Proteins Struct Funct Bioinf. 2005;60(3):353\u201366.","journal-title":"Proteins Struct Funct Bioinf"},{"issue":"1","key":"1201_CR27","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1006\/jcph.1998.6173","volume":"151","author":"B Jayaram","year":"1999","unstructured":"Jayaram B, McConnell KJ, Dixit SB, Beveridge DL. Free energy analysis of protein\u2013DNA binding: the EcoRI endonuclease\u2013DNA complex. J Comput Phys. 1999;151(1):333\u201357.","journal-title":"J Comput Phys"},{"issue":"7","key":"1201_CR28","doi-asserted-by":"publisher","first-page":"2047","DOI":"10.1021\/bi952812r","volume":"35","author":"JB Chaires","year":"1996","unstructured":"Chaires JB, Satyanarayana S, Suh D, Fokt I, Przewloka T, Priebe W. Parsing the free energy of anthracycline antibiotic binding to DNA. Biochemistry. 1996;35(7):2047\u201353.","journal-title":"Biochemistry"},{"issue":"13","key":"1201_CR29","doi-asserted-by":"publisher","first-page":"5330","DOI":"10.1073\/pnas.0606198104","volume":"104","author":"S Liu","year":"2007","unstructured":"Liu S, Liu S, Zhu X, Liang H, Cao A, Chang Z, Lai L. Nonnatural protein\u2013protein interaction-pair design by key residues grafting. Proc Natl Acad Sci. 2007;104(13):5330\u20135.","journal-title":"Proc Natl Acad Sci"},{"issue":"1","key":"1201_CR30","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1016\/j.jmb.2004.05.058","volume":"341","author":"S Ahmad","year":"2004","unstructured":"Ahmad S, Sarai A. Moment-based prediction of DNA-binding proteins. J Mol Biol. 2004;341(1):65\u201371.","journal-title":"J Mol Biol"},{"issue":"4860","key":"1201_CR31","doi-asserted-by":"publisher","first-page":"1759","DOI":"10.1126\/science.3289117","volume":"240","author":"WH Landschulz","year":"1988","unstructured":"Landschulz WH, Johnson PF, McKnight SL. The leucine zipper: a hypothetical structure common to a new class of DNA binding proteins. Science. 1988;240(4860):1759\u201364.","journal-title":"Science"},{"issue":"2","key":"1201_CR32","doi-asserted-by":"publisher","first-page":"439","DOI":"10.1016\/0092-8674(91)90651-E","volume":"64","author":"YT Ip","year":"1991","unstructured":"Ip YT, Kraut R, Levine M, Rushlow CA. The dorsal morphogen is a sequence-specific DNA-binding protein that interacts with a long-range repression element in Drosophila. Cell. 1991;64(2):439\u201346.","journal-title":"Cell"},{"issue":"2","key":"1201_CR33","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1016\/j.jtbi.2005.09.018","volume":"240","author":"X Yu","year":"2016","unstructured":"Yu X, Cao J, Cai Y, Shi T, Li Y. Predicting rRNA-, RNA-, and DNA-binding proteins from primary structure with support vector machines. J Theor Biol. 2016;240(2):175\u201384.","journal-title":"J Theor Biol"},{"issue":"6","key":"1201_CR34","doi-asserted-by":"publisher","first-page":"1270","DOI":"10.1016\/j.cell.2011.10.053","volume":"147","author":"M Slattery","year":"2011","unstructured":"Slattery M, Riley T, Liu P, Abe N, Gomez-Alcala P, Dror I, Zhou T, Rohs R, Honig B, Bussemaker HJ, Mann RS. Cofactor binding evokes latent differences in DNA binding specificity between Hox proteins. Cell. 2011;147(6):1270\u201382.","journal-title":"Cell"},{"key":"1201_CR35","doi-asserted-by":"publisher","first-page":"594","DOI":"10.1006\/jmbi.1996.0804","volume":"266","author":"I PSORT","year":"1997","unstructured":"PSORT I. PSORT: a program for detecting sorting signals in proteins and predicting their subcellular localization. J Mol Biol. 1997;266:594\u2013600.","journal-title":"J Mol Biol"},{"issue":"12","key":"1201_CR36","doi-asserted-by":"publisher","first-page":"1331","DOI":"10.1038\/ng1473","volume":"36","author":"S Mukherjee","year":"2004","unstructured":"Mukherjee S, Berger MF, Jona G, Wang XS, Muzzey D, Snyder M, Young RA, Bulyk ML. Rapid analysis of the DNA-binding specificities of transcription factors with DNA microarrays. Nat Genet. 2004;36(12):1331\u20139.","journal-title":"Nat Genet"},{"issue":"4","key":"1201_CR37","doi-asserted-by":"publisher","first-page":"477","DOI":"10.1093\/bioinformatics\/btg432","volume":"20","author":"S Ahmad","year":"2004","unstructured":"Ahmad S, Gromiha MM, Sarai A. Analysis and prediction of DNA-binding proteins and their binding residues based on composition, sequence and structural information. Bioinformatics. 2004;20(4):477\u201386.","journal-title":"Bioinformatics"},{"issue":"5","key":"1201_CR38","doi-asserted-by":"publisher","first-page":"727","DOI":"10.1021\/jm00155a023","volume":"29","author":"D Goodsell","year":"2004","unstructured":"Goodsell D, Dickerson RE. Isohelical analysis of DNA groove-binding drugs. J Med Chem. 2004;29(5):727\u201333.","journal-title":"J Med Chem"},{"issue":"1","key":"1201_CR39","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.abb.2006.03.027","volume":"453","author":"JB Chaires","year":"2006","unstructured":"Chaires JB. A thermodynamic signature for drug\u2013DNA binding mode. Arch Biochem Biophys. 2006;453(1):26\u201331.","journal-title":"Arch Biochem Biophys"},{"issue":"5209","key":"1201_CR40","doi-asserted-by":"publisher","first-page":"439","DOI":"10.1126\/science.7716551","volume":"268","author":"MW Nowak","year":"1995","unstructured":"Nowak MW, Kearney PC, Saks ME, Labarca CG, Silverman SK, Zhong W, Thorson J, Abelson JN, Davidson N. Nicotinic receptor binding site probed with unnatural amino acid incorporation in intact cells. Science. 1995;268(5209):439\u201342.","journal-title":"Science"},{"key":"1201_CR41","doi-asserted-by":"publisher","first-page":"412","DOI":"10.1016\/j.jtbi.2014.08.002","volume":"363","author":"J Zhang","year":"2014","unstructured":"Zhang J, Sun P, Zhao X, Ma Z. PECM: Prediction of extracellular matrix proteins using the concept of Chou\u2019s pseudo amino acid composition. J Theor Biol. 2014;363:412\u20138.","journal-title":"J Theor Biol"},{"key":"1201_CR42","series-title":"Springer science & business media","volume-title":"The nature of statistical learning theory","author":"V Vapnik","year":"2013","unstructured":"Vapnik V. The nature of statistical learning theory, Springer science & business media. 2013."},{"issue":"3","key":"1201_CR43","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1145\/1961189.1961199","volume":"2","author":"CC Chang","year":"2011","unstructured":"Chang CC, Lin CJ. LIBSVM: a library for support vector machines. ACM Trans Intell Syst Technol. 2011;2(3):27.","journal-title":"ACM Trans Intell Syst Technol"},{"key":"1201_CR44","doi-asserted-by":"crossref","unstructured":"Yang XS. Firefly algorithms for multimodal optimization. In Stochastic algorithms: foundations and applications. Springer Berlin Heidelberg; 2009: 169\u2013178.","DOI":"10.1007\/978-3-642-04944-6_14"},{"issue":"1","key":"1201_CR45","doi-asserted-by":"publisher","first-page":"75","DOI":"10.9790\/0661-1117578","volume":"11","author":"A Hashmi","year":"2013","unstructured":"Hashmi A, Goel N, Goel S, Gupta D. Firefly algorithm for unconstrained optimization. IOSR J Comput Eng. 2013;11(1):75\u20138.","journal-title":"IOSR J Comput Eng"},{"issue":"1","key":"1201_CR46","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1504\/IJSI.2013.055801","volume":"1","author":"XS Yang","year":"2013","unstructured":"Yang XS, He X. Firefly algorithm: recent advances and applications. Int J Swarm Intell. 2013;1(1):36\u201350.","journal-title":"Int J Swarm Intell"},{"key":"1201_CR47","first-page":"428","volume":"2","author":"S Palit","year":"2011","unstructured":"Palit S, Sinha SN, Molla MA, Khanra A, Kule M. A cryptanalytic attack on the knapsack cryptosystem using binary firefly algorithm. In Int Conf Comput Commun Technol (ICCCT). 2011;2:428\u201332.","journal-title":"In Int Conf Comput Commun Technol (ICCCT)"},{"issue":"1","key":"1201_CR48","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1016\/j.jmsy.2012.06.004","volume":"32","author":"MK Sayadi","year":"2013","unstructured":"Sayadi MK, Hafezalkotob A, Naini SGJ. Firefly-inspired algorithm for discrete optimization problems: an application to manufacturing cell formation. J Manuf Syst. 2013;32(1):78\u201384.","journal-title":"J Manuf Syst"},{"key":"1201_CR49","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1016\/j.anucene.2015.02.047","volume":"81","author":"N Poursalehi","year":"2015","unstructured":"Poursalehi N, Zolfaghari A, Minuchehr A. A novel optimization method, Effective Discrete Firefly Algorithm, for fuel reload design of nuclear reactors. Ann Nuclear Energy. 2015;81:263\u201375.","journal-title":"Ann Nuclear Energy"},{"issue":"1","key":"1201_CR50","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1016\/j.compbiolchem.2007.09.005","volume":"32","author":"LY Chuang","year":"2008","unstructured":"Chuang LY, Chang HW, Tu CJ, Yang CH. Improved binary PSO for feature selection using gene expression data. Comput Biol Chem. 2008;32(1):29\u201338.","journal-title":"Comput Biol Chem"},{"issue":"1","key":"1201_CR51","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1016\/j.compeleceng.2013.11.024","volume":"40","author":"G Chandrashekar","year":"2014","unstructured":"Chandrashekar G, Sahin F. A survey on feature selection methods. Comput Electr Eng. 2014;40(1):16\u201328.","journal-title":"Comput Electr Eng"},{"issue":"02","key":"1201_CR52","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1142\/S0219720005001004","volume":"3","author":"C Ding","year":"2005","unstructured":"Ding C, Peng H. Minimum redundancy feature selection from microarray gene expression data. J Bioinform Comput Biol. 2005;3(02):185\u2013205.","journal-title":"J Bioinform Comput Biol"},{"issue":"11","key":"1201_CR53","doi-asserted-by":"publisher","first-page":"e1000567","DOI":"10.1371\/journal.pcbi.1000567","volume":"5","author":"M Gao","year":"2009","unstructured":"Gao M, Skolnick J. A threading-based method for the prediction of DNA-binding proteins with application to the human genome. PLoS Comput Biol. 2009;5(11):e1000567.","journal-title":"PLoS Comput Biol"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-016-1201-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12859-016-1201-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-016-1201-8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-016-1201-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T18:21:33Z","timestamp":1706811693000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/s12859-016-1201-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,8,26]]},"references-count":53,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2016,12]]}},"alternative-id":["1201"],"URL":"https:\/\/doi.org\/10.1186\/s12859-016-1201-8","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,8,26]]},"assertion":[{"value":"21 January 2016","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 August 2016","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 August 2016","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"323"}}