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Items: 6

1.

Data-driven multiscale modeling reveals the role of metabolic coupling for the spatio-temporal growth dynamics of yeast colonies.

Intosalmi J, Scott AC, Hays M, Flann N, Yli-Harja O, Lähdesmäki H, Dudley AM, Skupin A.

BMC Mol Cell Biol. 2019 Dec 19;20(1):59. doi: 10.1186/s12860-019-0234-z.

2.

A Probabilistic Framework for Molecular Network Structure Inference by Means of Mechanistic Modeling.

Timonen J, Mannerstrom H, Lahdesmaki H, Intosalmi J.

IEEE/ACM Trans Comput Biol Bioinform. 2019 Nov-Dec;16(6):1843-1854. doi: 10.1109/TCBB.2018.2825327. Epub 2018 Apr 10.

PMID:
29993837
3.

A subpopulation model to analyze heterogeneous cell differentiation dynamics.

Chan YH, Intosalmi J, Rautio S, Lähdesmäki H.

Bioinformatics. 2016 Nov 1;32(21):3306-3313. Epub 2016 Jul 10.

PMID:
27402901
4.

Data-driven mechanistic analysis method to reveal dynamically evolving regulatory networks.

Intosalmi J, Nousiainen K, Ahlfors H, Lähdesmäki H.

Bioinformatics. 2016 Jun 15;32(12):i288-i296. doi: 10.1093/bioinformatics/btw274.

5.

Analyzing Th17 cell differentiation dynamics using a novel integrative modeling framework for time-course RNA sequencing data.

Intosalmi J, Ahlfors H, Rautio S, Mannerstöm H, Chen ZJ, Lahesmaa R, Stockinger B, Lähdesmäki H.

BMC Syst Biol. 2015 Nov 17;9:81. doi: 10.1186/s12918-015-0223-6.

6.

Computational study of noise in a large signal transduction network.

Intosalmi J, Manninen T, Ruohonen K, Linne ML.

BMC Bioinformatics. 2011 Jun 21;12:252. doi: 10.1186/1471-2105-12-252.

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