Memote: A community driven effort towards a standardized genome-scale metabolic model test suite. Lieven, C., Beber, M., Olivier, B., Bergmann, F., Ataman, M., Babaei, P., Bartell, J., Blank, L., Chauhan, S., Correia, K., Diener, C., Dräger, A., Ebert, B., Edirisinghe, J., Faria, J., Feist, A., Fengos, G., Fleming, R., García-Jiménez, B., Hatzimanikatis, V., van Helvoirt, W., Henry, C., Hermjakob, H., Herrgård, M., Kim, H., King, Z., Koehorst, J., Klamt, S., Klipp, E., Lakshmanan, M., Le Novère, N., Lee, D., Lee, S., Lee, S., Lewis, N., Ma, H., Machado, D., Mahadevan, R., Maia, P., Mardinoglu, A., Medlock, G., Monk, J., Nielsen, J., Nielsen, L., Nogales, J., Nookaew, I., Resendis-Antonio, O., Palsson, B., Papin, J., Patil, K., Poolman, M., Price, N., Richelle, A., Rocha, I., Sanchez, B., Schaap, P., Malik Sheriff, R., Shoaie, S., Sonnenschein, N., Teusink, B., Vilaça, P., Vik, J., Wodke, J., Xavier, J., Yuan, Q., Zakhartsev, M., & Zhang, C. 2018. doi abstract bibtex 2 downloads The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license. Several studies have shown that neither the formal representation nor the functional requirements of genome-scale metabolic models (GEMs) are precisely defined. Without a consistent standard, comparability, reproducibility, and interoperability of models across groups and software tools cannot be guaranteed.Here, we present memote (https://github.com/opencobra/memote) an open-source software containing a community-maintained, standardized set of metabolic model tests. The tests cover a range of aspects from annotations to conceptual integrity and can be extended to include experimental datasets for automatic model validation. In addition to testing a model once, memote can be configured to do so automatically, i.e., while building a GEM. A comprehensive report displays the model’s performance parameters, which supports informed model development and facilitates error detection.Memote provides a measure for model quality that is consistent across reconstruction platforms and analysis software and simplifies collaboration within the community by establishing workflows for publicly hosted and version controlled models.
@misc{
title = {Memote: A community driven effort towards a standardized genome-scale metabolic model test suite},
type = {misc},
year = {2018},
source = {bioRxiv},
id = {50c018fd-9348-3bae-a815-5b7b0442fdc2},
created = {2020-12-23T17:02:17.880Z},
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group_id = {ff1f9038-dd83-321a-9605-910d757253bb},
last_modified = {2020-12-23T17:02:17.880Z},
read = {false},
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abstract = {The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license. Several studies have shown that neither the formal representation nor the functional requirements of genome-scale metabolic models (GEMs) are precisely defined. Without a consistent standard, comparability, reproducibility, and interoperability of models across groups and software tools cannot be guaranteed.Here, we present memote (https://github.com/opencobra/memote) an open-source software containing a community-maintained, standardized set of metabolic model tests. The tests cover a range of aspects from annotations to conceptual integrity and can be extended to include experimental datasets for automatic model validation. In addition to testing a model once, memote can be configured to do so automatically, i.e., while building a GEM. A comprehensive report displays the model’s performance parameters, which supports informed model development and facilitates error detection.Memote provides a measure for model quality that is consistent across reconstruction platforms and analysis software and simplifies collaboration within the community by establishing workflows for publicly hosted and version controlled models.},
bibtype = {misc},
author = {Lieven, C. and Beber, M.E. and Olivier, B.G. and Bergmann, F.T. and Ataman, M. and Babaei, P. and Bartell, J.A. and Blank, L.M. and Chauhan, S. and Correia, K. and Diener, C. and Dräger, A. and Ebert, B.E. and Edirisinghe, J.N. and Faria, J.P. and Feist, A. and Fengos, G. and Fleming, R.M.T. and García-Jiménez, B. and Hatzimanikatis, V. and van Helvoirt, W. and Henry, C.S. and Hermjakob, H. and Herrgård, M.J. and Kim, H.U. and King, Z. and Koehorst, J.J. and Klamt, S. and Klipp, E. and Lakshmanan, M. and Le Novère, N. and Lee, D.-Y. and Lee, S.Y. and Lee, S. and Lewis, N.E. and Ma, H. and Machado, D. and Mahadevan, R. and Maia, P. and Mardinoglu, A. and Medlock, G.L. and Monk, J.M. and Nielsen, J. and Nielsen, L.K. and Nogales, J. and Nookaew, I. and Resendis-Antonio, O. and Palsson, B.O. and Papin, J.A. and Patil, K.R. and Poolman, M. and Price, N.D. and Richelle, A. and Rocha, I. and Sanchez, B.J. and Schaap, P.J. and Malik Sheriff, R.S. and Shoaie, S. and Sonnenschein, N. and Teusink, B. and Vilaça, P. and Vik, J.O. and Wodke, J.A. and Xavier, J.C. and Yuan, Q. and Zakhartsev, M. and Zhang, C.},
doi = {10.1101/350991}
}
Downloads: 2
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