Outputs (37)

AMP: a new time-frequency feature extraction method for intermittent time-series data (2015)
Presentation / Conference Contribution
Barrack, D. S., Goulding, J., Hopcraft, K., Preston, S., & Smith, G. AMP: a new time-frequency feature extraction method for intermittent time-series data. Presented at 1st International Workshop on Mining and Learning from Time Series (MiLeTS)

The characterisation of time-series data via their most salient features is extremely important in a range of machine learning task, not least of all with regards to classification and clustering. While there exist many feature extraction techniques... Read More about AMP: a new time-frequency feature extraction method for intermittent time-series data.

Exploiting heterogeneous environments: does photosynthetic acclimation optimize carbon gain in fluctuating light? (2015)
Journal Article
Retkute, R., Smith-Unna, S. E., Smith, R. W., Burgess, A. J., Jensen, O. E., Johnson, G. N., Preston, S. P., & Murchie, E. H. (2015). Exploiting heterogeneous environments: does photosynthetic acclimation optimize carbon gain in fluctuating light?. Journal of Experimental Botany, 66(9), 2437-2447. https://doi.org/10.1093/jxb/erv055

Plants have evolved complex mechanisms to balance the efficient use of absorbed light energy in photosynthesis with the capacity to use that energy in assimilation, so avoiding potential damage from excess light. This is particularly important under... Read More about Exploiting heterogeneous environments: does photosynthetic acclimation optimize carbon gain in fluctuating light?.

Piecewise Approximate Bayesian Computation: fast inference for discretely observed Markov models using a factorised posterior distribution (2013)
Journal Article
White, S. R., Kypraios, T., & Preston, S. P. (2015). Piecewise Approximate Bayesian Computation: fast inference for discretely observed Markov models using a factorised posterior distribution. Statistics and Computing, 25(2), 289-301. https://doi.org/10.1007/s11222-013-9432-2

© 2013, The Author(s). Many modern statistical applications involve inference for complicated stochastic models for which the likelihood function is difficult or even impossible to calculate, and hence conventional likelihood-based inferential techni... Read More about Piecewise Approximate Bayesian Computation: fast inference for discretely observed Markov models using a factorised posterior distribution.

Modelling the regulation of telomere length: the effects of telomerase and G-quadruplex stabilising drugs (2013)
Journal Article
Hirt, B. V., Wattis, J. A., & Preston, S. P. (2014). Modelling the regulation of telomere length: the effects of telomerase and G-quadruplex stabilising drugs. Journal of Mathematical Biology, 68(6), 1521-1552. https://doi.org/10.1007/s00285-013-0678-2

Telomeres are guanine-rich sequences at the end of chromosomes which shorten during each replication event and trigger cell cycle arrest and/or controlled death (apoptosis) when reaching a threshold length. The enzyme telomerase replenishes the ends... Read More about Modelling the regulation of telomere length: the effects of telomerase and G-quadruplex stabilising drugs.

The effects of a telomere destabilising agent on cancer cell-cycle dynamics - integrated modelling and experiments (2012)
Journal Article
Hirt, B. V., Wattis, J. A., Preston, S. P., & Laughton, C. A. (2012). The effects of a telomere destabilising agent on cancer cell-cycle dynamics - integrated modelling and experiments. Journal of Theoretical Biology, 295, https://doi.org/10.1016/j.jtbi.2011.10.038

The pentacyclic acridinium salt RHPS4 displays anti-tumour properties in vitro as well as in vivo and is potentially cell-cycle specific. We have collected experimental data and formulated a compartmental model using ordinary differential equations t... Read More about The effects of a telomere destabilising agent on cancer cell-cycle dynamics - integrated modelling and experiments.

A data-based power transformation for compositional data (2011)
Presentation / Conference Contribution
Tsagris, M., Preston, S., & Wood, A. T. A data-based power transformation for compositional data. Presented at CoDaWork'11: 4th international workshop on Compositional Data Analysis

Predicting arsenic solubility in contaminated soils using isotopic dilution techniques (2002)
Journal Article
Tye, A. M., Young, S. D., Crout, N. M., Zhang, H., Preston, S., Bailey, E. H., Davison, W., McGrath, S. P., Paton, G. I., & Kilham, K. (2002). Predicting arsenic solubility in contaminated soils using isotopic dilution techniques. Environmental Science and Technology, 36(5), 982-988. https://doi.org/10.1021/es0101633

An isotopic dilution assay was developed to measure radiolabile As concentration in a diverse range of soils (pH 3.30-7.62; % C = 1.00-6.55). Soils amended with 50 mg of As kg-1 (as Na2HAsO4·7H2O) were incubated for over 800 d in an aerated "microcos... Read More about Predicting arsenic solubility in contaminated soils using isotopic dilution techniques.