Computational systems biology group

Mathematical modeling can tell us what is possible and what impossible and the reasons why. It is extremely useful to avoid unnecessary experiments from the long list of opportunities.

Modeling sheds the light on something that is not obvious, thus allowing to conduct LESS USELESS experiments.


COMPUTATIONAL SYSTEMS BIOLOGY GROUP uses mathematical modeling to find the way how interactions of components form a biological system. The SCIENTIFIC INTERESTS OF THE GROUP include:

  • stoichiometric and kinetic modeling and optimization of metabolism,
  • metabolic reconstructions,
  • modeling of signaling networks,
  • modeling of microbial communities, and
  • software development

in the areas of:

  • microbial biotechnology,
  • medicine, and
  • environment.


Team Egils Stalidzāns Agris Pentjušs Atis Elsts Elīna Dāce Ivars Mozga Vitālijs Komašilovs Jānis Kurlovičs Dārta Maija Zaķe Kristaps Bērziņš Rūdolfs Petrovs



2019 - 2022, Crypthecodinium cohnii and Zymomonas mobilis syntrophy for production of omega 3 fatty acid from byproducts of biofuel and sugar industry, funded by European Regional Development Fund (project No. LV EN

2015 - 2018, LEANPROT: Systems biology platform for the creation of lean-proteome Esherichia coli strains, funded by FP7 EraSysApp (2nd call). 2018 - 2020, Mathematical model of pharmacokinetics for personalized optimization of metformin therapy, funded by Latvian Council of Science (project No: lzp-2018/2-0088).

2018 - 2021, RHODOLIVE: Biovalorization of olive oil mill wastewater to microbial lipids and other products via Rhodotula glutinis fermentation, funded by Horizon 2020 research and innovation programme ERA-net CoBioTech (1-st call) (grant No. 722361). 

2015 - 2018, SMARTPLANTS: Control of Engineered Metabolism by Flowering and Temperature Triggered Plant Regulatory Networks, funded by FP7 EraSynBio (2nd call). 

2013 - 2016, Metabolic engineering of Zymomonas mobilis respiratory chain, funded by Latvian Council of Science (grant No. 536/2012).

2013 - 2015, ERA–net project on systems biology ERASysAPP (

2012 - 2014, ERA–net project on synthetic biology ERASynBio (

2009 - 2012, Establishment of Latvian interdisciplinary interuniversity scientific group of systems biology, funded by European Social Fund within activity „Attraction of Human Resources to Science”.




Heirendt, L., Arreckx, S., Pfau, T., Mendoza, S.N., Richelle, A., Heinken, A., Haraldsdottir, H.S., Keating, S.M., Vlasov, V., Wachowiak, J., Magnusdottir, S., Ng, C.Y., Preciat, G., Zagare, A., Chan, S.H.J., Aurich, M.K., Clancy, C.M., Modamio, J., Sauls, J.T., Noronha, A., Bordbar, A., Cousins, B., Assal, D.C. El, Ghaderi, S., Ahookhosh, M., Guebila, M. Ben, Apaolaza, I., Kostromins, A., Le, H.M., Ma, D., Sun, Y., Valcarcel, L. V., Wang, L., Yurkovich, J.T., Vuong, P.T., Assal, L.P. El, Hinton, S., Bryant, W.A., Artacho, F.J.A., Planes, F.J., Stalidzans, E., Maass, A., Vempala, S., Hucka, M., Saunders, M.A., Maranas, C.D., Lewis, N.E., Sauter, T., Palsson, B.Ø., Thiele, I., Fleming, R.M. (2019) Creation and analysis of biochemical constraint-based models: the COBRA Toolbox v3.0. Nature Protocols, 14, 639-702.

Stalidzans E., Landmane K., Sulins J., Sahle S. (2019) Misinterpretation risks of global stochastic optimisation of kinetic models revealed by multiple optimisation runs. Mathematical Biosciences, 307, 25-32.


Zanin, M., Chorbev, I., Stres, B., Stalidzans, E., Vera, J., Tieri, P., Castiglione, F., Groen, D., Zheng, H., Baumbach, J., Schmid, J.A., Basilio, J., Klimek, P., Debeljak, N., Rozman, D., Schmidt, H.H.H.W., (2018) Community effort endorsing multiscale modelling, multiscale data science and multiscale computing for systems medicine. Briefings in Bioinformatics, bbx160.

Stalidzans E., Seiman A., Peebo K., Komasilovs V., Pentjuss A. (2018) Model based metabolism design: constraints for kinetic and stoichiometric models, Biochemical Society Transactions, 46 (2), 261-267.


Komasilovs V., Pentjuss A., Elsts A., Stalidzans E. (2017) Total enzyme activity constraint and homeostatic constraint impact on the optimization potential of a kinetic model. Biosystems,162, 128-134.

Elsts, A., Pentjuss, A., Stalidzans, E. (2017) SpaceScanner: COPASI wrapper for automated management of global stochastic optimization experiments. Bioinformatics, 33, 2966-2967.

Stalidzans, E., Mozga, I., Sulins, J., Zikmanis, P., (2017) Search for a Minimal Set of Parameters by Assessing the Total Optimization Potential for a Dynamic Model of a Biochemical Network. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 14(4), 978–985.

Pentjuss, A., Stalidzans, E., Liepins, J., Kokina, A., Martynova, J., Zikmanis, P., Mozga, I., Scherbaka, R., Hartman, H., Poolman, M.G., Fell, D.A., Vigants, A., (2017) Model-based biotechnological potential analysis of Kluyveromyces marxianus central metabolism. Journal of Industrial Microbiology & Biotechnology, 44(8), 1177–1190.


Cvijovic, M., Höfer, T., Aćimović, J., Alberghina, L., Almaas, E., Besozzi, D., Blomberg, A., Bretschneider, T., Cascante, M., Collin, O., de Atauri, P., Depner, C., Dickinson, R., Dobrzynski, M., Fleck, C., Garcia-Ojalvo, J., Gonze, D., Hahn, J., Hess, H., Hollmann, S., Krantz, M., Kummer, U., Lundh, T., Martial, G., dos Santos, V.M., Mauer-Oberthür, A., Regierer, B., Skene, B., Stalidzans, E., Stelling, J., Teusink, B., Workman, C.T., Hohmann, S. (2016) Strategies for structuring interdisciplinary education in Systems Biology: an European perspective. npj Systems Biology and Applications, 2, Article number: 16011.


Meitalovs J., Stalidzans E. (2015) Impact of Thermodynamic Constraint to the Solution Space of Metabolic Pathway Design Using sAnalyzer Tool. Baltic Journal of Modern Computing, 3(3), pp.164-178.


Kalnenieks, U., Pentjuss, A., Rutkis, R., Stalidzans, E., Fell, D. A. (2014) Modeling of Zymomonas mobilis central metabolism for novel metabolic engineering strategies. Frontiers in Microbiology, 5, 42.

Mozga I., Stalidzans E (2014) Reduction of Combinatorial Space of Adjustable Kinetic Parameters of Biochemical Network Models in Optimisation Task. Baltic Journal of Modern Computing, 2(3), pp.150-159.


Rubina T., Stalidzans E. (2013) BINESA – a software tool for evolution modelling of biochemical networks structure. In Proceedings of IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI), November 19-21, 2013, Budapest, Hungary. INSPEC Accession Number: 14030108, 345-350.

Rubina T., Mednis M., Stalidzans E. (2013) Agreement assessment of biochemical pathway models by structural analysis of their intersection. In Proceedings of IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI), November 19-21, 2013, Budapest, Hungary, INSPEC Accession Number: 14030115, 411-418.

Pentjuss, A., Kalnenieks, U. (2013) Assessment of Zymomonas mobilis biotechnological potential in ethanol production by flux variability analysis. Biosystems and Information Technology, 3(1), 1–5.   

Rutkis, R., Kalnenieks, U., Stalidzans, E., & Fell, D. A. (2013) Kinetic modeling of Zymomonas mobilis Entner-Doudoroff pathway: insights into control and functionality. Microbiology, 159, 2674-2689.

Mednis, M., Vigants A., (2013) Automatic comparison of metabolites names: impact of criteria thresholds. Biosystems and Information technology, 2(1), 1-5,   

Pentjuss A., Odzina I., Kostromins A., Fell D., Stalidzans E., Kalnenieks U. (2013) Biotechnological potential of respiring Zymomonas mobilis: A stoichiometric analysis of its central metabolism. Journal of Biotechnology, 165, 1-10.

Meitalovs, J., Stalidzans, E. (2013) Connectivity analysis of metabolites in synthetic metabolic pathways. In Proceedings of the 12th International Scientific Conference “Engineering for Rural Development”, May 23-25, 2013, Jelgava, Latvia, 435–440.


Stalidzans E., Kostromins A., Sulins J. (2012) Two stage optimization of biochemical pathways using parallel runs of global stochastic optimization methods. In Proceedings of IEEE 13th International Symposium on Computational Intelligence and Informatics, Budapest, Hungary, November 20-22, 2012. INSPEC Accession Number: 13446430, 365-369.

Mednis, M., Brusbardis, V., Galvanauskas, V. (2012) Comparison of genome-scale reconstructions using ModeRator. In Proceedings of IEEE 13th International Symposium on Computational Intelligence and Informatics, Budapest, Hungary, November 20-22, 2012. INSPEC Accession Number: 13446376, 79-84. 

Kostromins A., Mozga I., Stalidzans E. (2012) ConvAn: a convergence analyzing tool for optimization of biochemical networks, Biosystems, 108(1–3), 73-77.

Kostromins A., Stalidzans E. (2012) Paint4Net: COBRA Toolbox extension for visualization of stoichiometric models of metabolism, Biosystems, 109(2), 233-239.

Sulins J., Stalidzans E. (2012) Corunner: multiple optimization run manager for Copasi software. In Proceedings of the International Scientific Conference "Applied Information and Communication Technologies", April 26-27, 2012, Jelgava, Latvia, 312-316.

Mednis, M., Aurich, M.K., (2012) Application of string similarity ratio and edit distance in automatic metabolite reconciliation comparing reconstructions and models, Biosystems and Information technology, 1(1), 14-18.


Mozga I., Stalidzans E. (2011) Convergence Dynamics of Biochemical Models To The Global Optimum. In Proceedings of 2011 E-Health and Bioengineering Conference (EHB), Iasi, Romania, November 24-26, 2011. INSPEC Accession Number: 12542531.

Mozga I., Stalidzans E. (2011) Optimization protocol of biochemical networks for effective collaboration between industry representatives, biologists and modellers. 9th International Industrial Simulation Conference (ISC'2011), Venice, Italy, June 6-8, 2011, 91–96.



Head of the group Egils Stalidzans

Phone: +371 29575510