Inference of genetic regulatory networks under the best-fit extension paradigm

@misc{citeulike:485894, abstract = {We address the problem of inferring the structure of genetic regulatory networks using the Boolean network model system. In realistic situations, gene expression measurements are noisy and lead to inconsistent observations. One learning strategy that can incorporate such inconsistencies is called the Best-Fit Extension Problem and its goal is to establish a network structure that would make as few misclassifications as possible. This strategy is a generalization of the well-known Consistency...}, author = {Shmulevich, I. and Saarinen, A. and Harja, Yli O. and Astola, J. }, citeulike-article-id = {485894}, keywords = {boolean\_networks, genetic\_regulatory\_networks, methodology}, posted-at = {2007-01-18 22:26:07}, priority = {3}, title = {Inference of genetic regulatory networks under the best-fit extension paradigm}, url = {http://citeseer.ist.psu.edu/shmulevich02inference.html}, year = {2002} }

TY - GEN ID - citeulike:485894 L3 - citeulike-article-id:485894 TI - Inference of genetic regulatory networks under the best-fit extension paradigm N2 - We address the problem of inferring the structure of genetic regulatory networks using the Boolean network model system. In realistic situations, gene expression measurements are noisy and lead to inconsistent observations. One learning strategy that can incorporate such inconsistencies is called the Best-Fit Extension Problem and its goal is to establish a network structure that would make as few misclassifications as possible. This strategy is a generalization of the well-known Consistency... KW - boolean_networks KW - genetic_regulatory_networks KW - methodology AU - Shmulevich, I AU - Saarinen, A AU - Harja, Yli AU - Astola, J PY - 2002/// UR - http://citeseer.ist.psu.edu/shmulevich02inference.html ER -