{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,26]],"date-time":"2026-09-26T22:05:16Z","timestamp":1790460316856,"version":"4.1.0"},"reference-count":34,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2012,6,26]],"date-time":"2012-06-26T00:00:00Z","timestamp":1340668800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJMS"],"abstract":"<jats:p>Two artificial intelligence techniques, namely artificial neural network (ANN) and genetic algorithm (GA) were combined to be used as a tool for optimizing the covalent immobilization of cellulase on a smart polymer, Eudragit L-100. 1-Ethyl-3-(3-dimethyllaminopropyl) carbodiimide (EDC) concentration, N-hydroxysuccinimide (NHS) concentration and coupling time were taken as independent variables, and immobilization efficiency was taken as the response. The data of the central composite design were used to train ANN by back-propagation algorithm, and the result showed that the trained ANN fitted the data accurately (correlation coefficient R2 = 0.99). Then a maximum immobilization efficiency of 88.76% was searched by genetic algorithm at a EDC concentration of 0.44%, NHS concentration of 0.37% and a coupling time of 2.22 h, where the experimental value was 87.97 \u00b1 6.45%. The application of ANN based optimization by GA is quite successful.<\/jats:p>","DOI":"10.3390\/ijms13077952","type":"journal-article","created":{"date-parts":[[2012,6,27]],"date-time":"2012-06-27T09:59:06Z","timestamp":1340791146000},"page":"7952-7962","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Artificial Intelligence Techniques to Optimize the EDC\/NHS-Mediated Immobilization of Cellulase on Eudragit L-100"],"prefix":"10.3390","volume":"13","author":[{"given":"Yu","family":"Zhang","sequence":"first","affiliation":[{"name":"Key Laboratory of Renewable Energy and Gas Hydrate & Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing-Liang","family":"Xu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Renewable Energy and Gas Hydrate & Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhen-Hong","family":"Yuan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Renewable Energy and Gas Hydrate & Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Qi","sequence":"additional","affiliation":[{"name":"Key Laboratory of Renewable Energy and Gas Hydrate & Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yun-Yun","family":"Liu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Renewable Energy and Gas Hydrate & Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Min-Chao","family":"He","sequence":"additional","affiliation":[{"name":"Key Laboratory of Renewable Energy and Gas Hydrate & Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2012,6,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1289","DOI":"10.1002\/adsc.200700082","article-title":"Enzyme immobilization: The quest for optimum performance","volume":"349","author":"Sheldon","year":"2007","journal-title":"Adv. Synth. Catal"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1007\/3-540-68116-7_4","article-title":"Immobilized enzymes: Methods and applications","volume":"200","author":"Tischer","year":"1999","journal-title":"Top. Curr. Chem"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"151","DOI":"10.5004\/dwt.2009.114","article-title":"Progress of enzyme immobilization and its potential application","volume":"1","author":"Wang","year":"2009","journal-title":"Desalin. Water Treat"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1451","DOI":"10.1016\/j.enzmictec.2007.01.018","article-title":"Improvement of enzyme activity, stability and selectivity via immobilization techniques","volume":"40","author":"Mateo","year":"2007","journal-title":"Enzyme Microb. Technol"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1016\/0168-1656(89)90015-1","article-title":"Immobilized cellulases for cellulose utilization","volume":"11","author":"Woodward","year":"1989","journal-title":"J. Biotechnol"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Galaev, I., and Mattiasson, B (2002). Smart Polymers for Bioseparation and Bioprocessing, Taylor & Francis Inc.. [1st ed].","DOI":"10.4324\/9780203302989"},{"key":"ref_7","first-page":"159","article-title":"Smart biocatalysts: Design and applications","volume":"86","author":"Roy","year":"2004","journal-title":"Adv. Biochem. Eng. Biotechnol"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1092","DOI":"10.1002\/bit.260340810","article-title":"Properties of a reversible soluble insoluble cellulase and its application to repeated hydrolysis of crystalline cellulose","volume":"34","author":"Taniguchi","year":"1989","journal-title":"Biotechnol. Bioeng"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"3153","DOI":"10.1016\/j.biortech.2009.12.080","article-title":"Artificial neural network-genetic algorithm based optimization for the immobilization of cellulase on the smart polymer Eudragit L-100","volume":"101","author":"Zhang","year":"2010","journal-title":"Bioresour. Technol"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"313","DOI":"10.3109\/10242422.2010.516391","article-title":"Preparation and properties of an immobilized cellulase on the reversibly soluble matrix Eudragit L-100","volume":"28","author":"Zhang","year":"2010","journal-title":"Biocatal. Biotransform"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"965","DOI":"10.1016\/j.talanta.2008.05.019","article-title":"Response surface methodology (RSM) as a tool for optimization in analytical chemistry","volume":"76","author":"Bezerra","year":"2008","journal-title":"Talanta"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"836","DOI":"10.1016\/j.jfoodeng.2005.11.024","article-title":"Modeling and optimization I: Usability of response surface methodology","volume":"78","author":"Bas","year":"2007","journal-title":"J. Food Eng"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/S1003-6326(08)60221-6","article-title":"Comparison of RSM with ANN in predicting tensile strength of friction stir welded AA7039 aluminium alloy joints","volume":"19","author":"Lakshminarayanan","year":"2009","journal-title":"T. Nonferr. Metal. Soc"},{"key":"ref_14","first-page":"355","article-title":"Kinetic model study on enzymatic hydrolysis of cellulose using artificial neural networks","volume":"30","author":"Zhang","year":"2009","journal-title":"Chin. J. Catal"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"8784","DOI":"10.1016\/j.biortech.2010.06.072","article-title":"Medium optimization for ethanol production with Clostridium autoethanogenum with carbon monoxide as sole carbon source","volume":"101","author":"Guo","year":"2010","journal-title":"Bioresour. Technol"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"703","DOI":"10.1007\/s00253-009-2185-3","article-title":"Radial basis function neural networks for modeling growth rates of the basidiomycetes Physisporinus vitreus and Neolentinus lepideus","volume":"85","author":"Schubert","year":"2010","journal-title":"Appl. Microbiol. Biotechnol"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/j.seppur.2010.08.016","article-title":"Modeling and optimization of tartaric acid reactive extraction from aqueous solutions: A comparison between response surface methodology and artificial neural network","volume":"75","author":"Marchitan","year":"2010","journal-title":"Sep. Purif. Technol"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"747","DOI":"10.1007\/s10295-009-0547-6","article-title":"Media optimization for biosurfactant production by Rhodococcus erythropolis MTCC 2794: Artificial intelligence versus a statistical approach","volume":"36","author":"Pal","year":"2009","journal-title":"J. Ind. Microbiol. Biotechnol"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"8201","DOI":"10.1016\/j.biortech.2008.03.038","article-title":"Artificial intelligence based optimization of exocellular glucansucrase production from Leuconostoc dextranicum NRRL B-1146","volume":"99","author":"Singh","year":"2008","journal-title":"Bioresour. Technol"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"250","DOI":"10.1002\/bit.21767","article-title":"Medium factor optimization and fermentation kinetics for phenazine-1-carboxylic acid production by Pseudomonas sp M18G","volume":"100","author":"He","year":"2008","journal-title":"Biotechnol. Bioeng"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"846","DOI":"10.1007\/s12257-010-0001-7","article-title":"Optimization of operational conditions for adipate ester synthesis in a stirred tank reactor","volume":"15","author":"Chaibakhsh","year":"2010","journal-title":"Biotechnol. Bioprocess Eng"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1007\/s12257-010-0119-7","article-title":"Design of experiments and artificial neural network linked genetic algorithm for modeling and optimization of l-asparaginase production by Aspergillus terreus MTCC 1782","volume":"16","author":"Gurunathan","year":"2011","journal-title":"Biotechnol. Bioprocess Eng"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1007\/s12010-009-8581-4","article-title":"Development and validation of a new PCR optimization method by combining experimental design and artificial neural network","volume":"160","author":"Li","year":"2010","journal-title":"Appl. Biochem. Biotechnol"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2884","DOI":"10.1016\/j.biortech.2009.09.093","article-title":"Artificial neural network modeling and genetic algorithm based medium optimization for the improved production of marine biosurfactant","volume":"101","author":"Sivapathasekaran","year":"2010","journal-title":"Bioresour. Technol"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"722","DOI":"10.1007\/s12010-008-8465-z","article-title":"Application of artificial neural network for yield prediction of lipase-catalyzed synthesis of dioctyl adipate","volume":"158","author":"Rahman","year":"2009","journal-title":"Appl. Biochem. Biotechnol"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1253","DOI":"10.1016\/j.ijhydene.2008.11.055","article-title":"Application of desirability function based on neural network for optimizing biohydrogen production process","volume":"34","author":"Wang","year":"2009","journal-title":"Int. J. Hydrog. Energy"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.jfoodeng.2005.08.044","article-title":"Application of genetic algorithm for optimization of vegetable oil hydrogenation process","volume":"78","author":"Izadifar","year":"2007","journal-title":"J. Food Eng"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/S0958-1669(02)00288-4","article-title":"Predictive non-linear modeling of complex data by artificial neural networks","volume":"13","author":"Almeida","year":"2002","journal-title":"Curr. Opin. Biotechnol"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2215","DOI":"10.1080\/03610920008832604","article-title":"A neural network approach to response surface methodology","volume":"29","author":"Balkin","year":"2000","journal-title":"Commun. Stat. Theory Methods"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"266","DOI":"10.1016\/j.bej.2008.05.009","article-title":"Comparison of artificial neural network (ANN) and response surface methodology (RSM) in fermentation media optimization: Case study of fermentative production of scleroglucan","volume":"41","author":"Desai","year":"2008","journal-title":"Biochem. Eng. J"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1351\/pac198759020257","article-title":"Measurements of cellulase activities","volume":"2","author":"Ghose","year":"1987","journal-title":"Pure Appl. Chem"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"3360","DOI":"10.1016\/j.procbio.2005.03.003","article-title":"Effect of alkali pretreatment on cellulase hydrolysis of wheat straw: Kinetic study","volume":"40","author":"Carrillo","year":"2005","journal-title":"Process Biochem"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"672","DOI":"10.1016\/S0141-0229(00)00257-X","article-title":"Simultaneous purification and immobilization of Aspergillus niger xylanase on the reversibly soluble polymer Eudragit\u2122 L-100","volume":"27","author":"Sardar","year":"2000","journal-title":"Enzyme Microb. Technol"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1016\/j.apcata.2007.02.052","article-title":"Predictive performance of \u201chighly complex\u201d artificial neural networks","volume":"324","author":"Tompos","year":"2007","journal-title":"Appl. Catal. 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