Tiina Manninen

Valmistuin Tampereen teknillisestä yliopistosta diplomi-insinööriksi syyskuussa 2003 ja tekniikan tohtoriksi joulukuussa 2007, kummassakin pääaineenani oli matematiikka. Tällä hetkellä olen yliopistotutkijana Laskennallisen neurotieteen ryhmässä Tampereen yliopistossa ja vierailevana tutkijana Gladstone Instituutissa.

Laskennallisten mallien kehitys hermosolu- ja gliasoluryhmille. Katso tarkempia tietoja Laskennallinen neurotieteen ryhmän sivuilta.

Laskennallinen neurotiede

H.-J. Jiang, J. Aćimović, T. Manninen, I. Ahokainen, J. Stapmanns, M. Lehtimäki, M. Diesmann, S. J. van Albada, H. E. Plesser, and M.-L. Linne. Modeling neuron-astrocyte interactions in neural networks using distributed simulation. PLoS Computational Biology 21(9): e1013503, 2025. https://doi.org/10.1371/journal.pcbi.1013503

T. Mäki-Marttunen, J. F. Kismul, K. Pajo, J. M. Schulz, T. Manninen, G. T. Einevoll, M.-L. Linne, O. A. Andreassen, and J. Hellgren Kotaleski. Pre- and post-synaptic mechanisms of neuronal inhibition assessed through biochemically detailed modeling of GABAB receptor signaling. Journal of Neuroscience 45(36): e0544252025, 2025. https://doi.org/10.1523/JNEUROSCI.0544-25.2025

F. Lu, C. Yen, C. D. Corley, J. G. McDonald, T. Manninen, N. R. Stewart, C. M. Zhu, D. M. Ferriero, and X. Jiang. Dysregulation of brain cholesterol biosynthetic pathway following hypoxia ischemia in neonatal mice. Developmental Neuroscience 47(5): 333–349, 2025. https://doi.org/10.1159/000543254

M. Rangel-Gomez, C. M. Alberini, B. Deneen, G. T. Drummond, T. Manninen, M. Sur, and A. Vicentic. Neuron-glial interactions: Implications for plasticity, behavior, and cognition. Journal of Neuroscience 44(40): e1231242024, 2024. https://doi.org/10.1523/JNEUROSCI.1231-24.2024

X. Liu, T. Manninen, A. Mikrogeorgiou Capper, X. Jiang, J. Ellison, Y. Kim, G. Gurler, D. Xu, and D. M. Ferriero. Brain metabolism after therapeutic hypothermia for murine hypoxia-ischemia using hyperpolarized [1-13C] pyruvate magnetic resonance spectroscopy. NMR in Biomedicine 37:e5196, 2024. https://doi.org/10.1002/nbm.5196

L. Keto and T. Manninen. CellRemorph: A toolkit for transforming, selecting, and slicing 3D cell structures on the road to morphologically detailed astrocyte simulations. Neuroinformatics 21(3):483–500, 2023. https://doi.org/10.1007/s12021-023-09627-5  

T. Manninen, J. Aćimović, and M.-L. Linne. Analysis of network models with neuron-astrocyte interactions. Neuroinformatics 21(2): 375–406, 2023. https://doi.org/10.1007/s12021-023-09622-w 

M.-L. Linne, J. Aćimović, A. Saudargiene, and T. Manninen. Neuron-glia interactions and brain circuits. Computational Modelling of the Brain, (M. Giugliano, M. Negrello, and D. Linaro eds.), Springer Series in Advances in Experimental Medicine and Biology, vol. 1359, 87-103, 2022. https://doi.org/10.1007/978-3-030-89439-9_4 

T. Manninen, A. Saudargiene, and M.-L. Linne. Astrocyte-mediated spike-timing-dependent long-term depression modulates synaptic properties in the developing cortex. PLoS Computational Biology 16(11):e1008360, 2020. https://doi.org/10.1371/journal.pcbi.1008360 

H. L. Payne, R. L. French, C. C. Guo, T. D. B. Nguyen-Vu, T. Manninen, and J. L. Raymond. Cerebellar Purkinje cells control eye movements with a rapid rate code that is invariant to spike irregularity. eLife 8:e37102, 2019. https://doi.org/10.7554/eLife.37102 

T. Manninen, R. Havela, and M.-L. Linne. Computational models of astrocytes and astrocyte-neuron interactions: Characterization, reproducibility, and future perspectives. Computational Glioscience, (M. De Pittà and H. Berry eds.), Springer Series in Computational Neuroscience, 423 - 454, 2019. https://doi.org/10.1007/978-3-030-00817-8_16 

T. Manninen, J. Aćimović, R. Havela, H. Teppola, and M.-L. Linne. Challenges in reproducibility, replicability, and comparability of computational models and tools for neuronal and glial networks, cells, and subcellular structures. Frontiers in Neuroinformatics (Part of Research Topic: Reproducibility and Rigour in Computational Neuroscience) 12:20, 2018. https://doi.org/10.3389/fninf.2018.00020 

T. Manninen, R. Havela, and M.-L. Linne. Computational models for calcium-mediated astrocyte functions. Frontiers in Computational Neuroscience 12:14, 2018. https://doi.org/10.3389/fncom.2018.00014 

N. P. Rougier, K. Hinsen, F. Alexandre, T. Arildsen, L. A. Barba, F. C. Y. Benureau, C. T. Brown, P. de Buyl, O. Caglayan, A. P. Davison, M.-A. Delsuc, G. Detorakis, A. K. Diem, D. Drix, P. Enel, B. Girard, O. Guest, M. G. Hall, R. N. Henriques, X. Hinaut, K. S. Jaron, M. Khamassi, A. Klein, T. Manninen, P. Marchesi, D. McGlinn, C. Metzner, O. Petchey, H. E. Plesser, T. Poisot, K. Ram, Y. Ram, E. Roesch, C. Rossant, V. Rostami, A. Shifman, J. Stachelek, M. Stimberg, F. Stollmeier, F. Vaggi, G. Viejo, J. Vitay, A. E. Vostinar, R. Yurchak, and T. Zito. Sustainable computational science: the ReScience initiative. PeerJ Computer Science 3:e142, 2017. https://doi.org/10.7717/peerj-cs.142 

T. Manninen, R. Havela, and M.-L. Linne. Reproducibility and comparability of computational models for astrocyte calcium excitability. Frontiers in Neuroinformatics 11:11, 2017. https://doi.org/10.3389/fninf.2017.00011 

J. Intosalmi, T. Manninen, K. Ruohonen, and M.-L. Linne. Computational study of noise in a large signal transduction network. BMC Bioinformatics 12:252, 2011. https://doi.org/10.1186/1471-2105-12-252 

E. Toivari, T. Manninen, A. K. Nahata, T. O. Jalonen, and M.-L. Linne. Effects of transmitters and amyloid-beta peptide on calcium signals in rat cortical astrocytes: Fura-2AM measurements and stochastic model simulations. PLoS ONE 6(3): e17914, 2011. https://doi.org/10.1371/journal.pone.0017914 

T. Manninen, K. Hituri, E. Toivari, and M.-L. Linne. Modeling signal transduction leading to synaptic plasticity: evaluation and comparison of five models. EURASIP Journal on Bioinformatics and Systems Biology 2011: 797250, 2011. https://bsb-eurasipjournals.springeropen.com/articles/10.1155/2011/797250 

T. Manninen, K. Hituri, J. Hellgren Kotaleski, K. T. Blackwell, and M.-L. Linne. Postsynaptic signal transduction models for long-term potentiation and depression. Frontiers in Computational Neuroscience 4:152, 2010. https://doi.org/10.3389/fncom.2010.00152 

T. Manninen, M.-L. Linne, and K. Ruohonen. Developing Itô stochastic differential equation models for neuronal signal transduction pathways. Computational Biology and Chemistry 30(4): 280 – 291, 2006. https://doi.org/10.1016/j.compbiolchem.2006.04.002 

T. Manninen, M.-L. Linne, and K. Ruohonen. A novel approach to model neuronal signal transduction using stochastic differential equations. Neurocomputing 69(10 – 12): 1066 – 1069, 2006. https://doi.org/10.1016/j.neucom.2005.12.047 

A. Pettinen, T. Aho, O.-P. Smolander, T. Manninen, A. Saarinen, K.-L. Taattola, O. Yli-Harja, and M.-L. Linne. Simulation tools for biochemical networks: evaluation of performance and usability. Bioinformatics 21(3): 357 – 363, 2005. https://doi.org/10.1093/bioinformatics/bti018 

M.-L. Linne, T. Manninen, and T. O. Jalonen. A model integrating the cerebellar granule neuron excitability and calcium signaling pathways. Neurocomputing 58 – 60: 569 – 574, 2004. https://doi.org/10.1016/j.neucom.2004.01.096