{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,8]],"date-time":"2026-02-08T05:18:32Z","timestamp":1770527912562,"version":"3.49.0"},"reference-count":8,"publisher":"Oxford University Press (OUP)","issue":"13","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2010,7,1]]},"abstract":"Abstract<\/jats:title>\n Summary: SensSB (Sensitivity Analysis for Systems Biology) is an easy to use, MATLAB-based software toolbox, which integrates several local and global sensitivity methods that can be applied to a wide variety of biological models. In addition to addressing the sensitivity analysis problem, SensSB aims to cover all the steps involved during the modeling process. The main features of SensSB are: (i) derivative and variance-based global sensitivity analysis, (ii) pseudo-global identifiability analysis, (iii) optimal experimental design (OED) based on global sensitivities, (iv) robust parameter estimation, (v) local sensitivity and identifiability analysis, (vi) confidence intervals of the estimated parameters and (vii) OED based on the Fisher Information Matrix (FIM). SensSB is also able to import models in the Systems Biology Mark-up Language (SBML) format. Several examples from simple analytical functions to more complex biological pathways have been implemented and can be downloaded together with the toolbox. The importance of using sensitivity analysis techniques for identifying unessential parameters and designing new experiments is quantified by increased identifiability metrics of the models and decreased confidence intervals of the estimated parameters.<\/jats:p>\n Availability: SensSB is a software toolbox freely downloadable from http:\/\/www.iim.csic.es\/\u223cgingproc\/SensSB.html. The web site also contains several examples and an extensive documentation.<\/jats:p>\n Contact: \u00a0mrodriguez@iim.csic.es<\/jats:p>\n Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btq242","type":"journal-article","created":{"date-parts":[[2010,5,6]],"date-time":"2010-05-06T00:50:39Z","timestamp":1273107039000},"page":"1675-1676","source":"Crossref","is-referenced-by-count":40,"title":["SensSB: a software toolbox for the development and sensitivity analysis of systems biology models"],"prefix":"10.1093","volume":"26","author":[{"given":"Maria","family":"Rodriguez-Fernandez","sequence":"first","affiliation":[{"name":"(Bio)Process Engineering Group, IIM-CSIC C\/Eduardo Cabello 6, 36208 Vigo, Spain"}]},{"given":"Julio R.","family":"Banga","sequence":"additional","affiliation":[{"name":"(Bio)Process Engineering Group, IIM-CSIC C\/Eduardo Cabello 6, 36208 Vigo, Spain"}]}],"member":"286","published-online":{"date-parts":[[2010,5,5]]},"reference":[{"key":"2023012507581117600_B1","doi-asserted-by":"crossref","first-page":"2037","DOI":"10.1093\/bioinformatics\/btn350","article-title":"Dynamical modeling and multi-experiment fitting with PottersWheel","volume":"24","author":"Maiwald","year":"2008","journal-title":"Bioinformatics"},{"key":"2023012507581117600_B2","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1186\/1471-2105-7-483","article-title":"Novel metaheuristic for parameter estimation in nonlinear dynamic biological systems","volume":"7","author":"Rodriguez-Fernandez","year":"2006","journal-title":"BMC Bioinformatics"},{"key":"2023012507581117600_B3","doi-asserted-by":"crossref","first-page":"3619","DOI":"10.1098\/rsta.2008.0108","article-title":"A new strategy for assessing sensitivities in biochemical models","volume":"366","author":"Sahle","year":"2008","journal-title":"Phil. 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