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When the target model is stiff, the computational time for reaching a solution increases further.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>In an attempt to solve this problem, we explored a learning technique that uses radial basis function networks (RBFN) to achieve a parameter estimation for biochemical models. RBFN reduce the number of numerical integrations by replacing derivatives with slopes derived from the distribution of searching points. To introduce a slight search bias, we implemented additional data selection using a GA that searches data-sparse areas at low computational cost. In addition, we adopted logarithmic transformation that smoothes the fitness surface to obtain a solution simply. We conducted numerical experiments to validate our methods and compared the results with those obtained by GA. We found that the calculation time decreased by more than 50% and the convergence rate increased from 60% to 90%.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>In this work, our RBFN technique was effective for parameter optimization of stiff biochemical models.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1471-2105-7-230","type":"journal-article","created":{"date-parts":[[2006,4,28]],"date-time":"2006-04-28T09:34:08Z","timestamp":1146216848000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Parameter estimation for stiff equations of biosystems using radial basis function networks"],"prefix":"10.1186","volume":"7","author":[{"given":"Yoshiya","family":"Matsubara","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shinichi","family":"Kikuchi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Masahiro","family":"Sugimoto","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Masaru","family":"Tomita","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2006,4,27]]},"reference":[{"key":"969_CR1","doi-asserted-by":"publisher","first-page":"7714","DOI":"10.1073\/pnas.1332628100","volume":"100","author":"FJ Isaacs","year":"2003","unstructured":"Isaacs FJ, Hasty J, Cantor CR, Collins JJ: Prediction and measurement of an autoregulatory genetic module. 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