A stochastic hybrid model of a biological filter

Autor: Andrea Ocone, Guido Sanguinetti

Publikováno v: Electronic Proceedings in Theoretical Computer Science, Vol 124, Iss Proc. HAS 2013, Pp 100-108 (2013)

We present a hybrid model of a biological filter, a genetic circuit which removes fast fluctuations in the cell's internal representation of the extra cellular environment. The model takes the classic feed-forward loop (FFL) motif and represents it a

Externí odkaz: https://doaj.org/article/e841aa24609944d1bb85ab19fe907fd9

Systems analysis of transcription factor activities in environments with stable and dynamic oxygen concentrations

Autor: Matthew D. Rolfe, Andrea Ocone, Melanie R. Stapleton, Simon Hall, Eleanor W. Trotter, Robert K. Poole, Guido Sanguinetti, Jeffrey Green

Publikováno v: Open Biology, Vol 2, Iss 7 (2012)

Understanding gene regulation requires knowledge of changes in transcription factor (TF) activities. Simultaneous direct measurement of numerous TF activities is currently impossible. Nevertheless, statistical approaches to infer TF activities have y

Externí odkaz: https://doaj.org/article/82b26df86a774ee28989f3dbb78f3b4a

A subsystems approach for parameter estimation of ODE models of hybrid systems

Autor: Allan Clark, Anastasis Georgoulas, Stephen Gilmore, Andrea Ocone, Guido Sanguinetti

Publikováno v: Electronic Proceedings in Theoretical Computer Science, Vol 92, Iss Proc. HSB 2012, Pp 30-41 (2012)
Georgoulas, A, Clark, A, Ocone, A, Gilmore, S & Sanguinetti, G 2012, ' A subsystems approach for parameter estimation of ODE models of hybrid systems ', Electronic Proceedings in Theoretical Computer Science, vol. 92, pp. 30-41 . https://doi.org/10.4204/EPTCS.92.3
HSB

We present a new method for parameter identification of ODE system descriptions based on data measurements. Our method works by splitting the system into a number of subsystems and working on each of them separately, thereby being easily parallelisab

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::af1f7e7662985c324637788f276e5bb4
https://doaj.org/article/07adbb88aed04f61af0f58b707d7d80f

Reconstructing gene regulatory dynamics from high-dimensional single-cell snapshot data

Autor: Andrea Ocone, Laleh Haghverdi, Fabian J. Theis, Nikola S. Mueller

Publikováno v: Bioinformatics 31, i89-i96 (2015)
Bioinformatics

Motivation: High-dimensional single-cell snapshot data are becoming widespread in the systems biology community, as a mean to understand biological processes at the cellular level. However, as temporal information is lost with such data, mathematical

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d7f937656bb4b82ae3cb1a157837d76f
https://push-zb.helmholtz-muenchen.de/frontdoor.php?source_opus=45238