Alida Palmisano

Alida Palmisano
National Cancer Institute (USA) | NCI · Division of Cancer Treatment and Diagnosis

PhD

About

24
Publications
1,456
Reads
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286
Citations
Citations since 2016
1 Research Item
166 Citations
2016201720182019202020212022051015202530
2016201720182019202020212022051015202530
2016201720182019202020212022051015202530
2016201720182019202020212022051015202530
Additional affiliations
June 2014 - present
National Cancer Institute (USA)
Position
  • PostDoc Position
March 2011 - June 2014
Virginia Tech (Virginia Polytechnic Institute and State University)
Position
  • PostDoc Position
May 2007 - December 2010
Università degli Studi di Trento

Publications

Publications (24)
Chapter
The cell division cycle is controlled by a complex regulatory network which ensures that the phases of the cell cycle are executed in the right order. This regulatory network receives signals from the environment, monitors the state of the DNA, and decides timings of cell cycle events. The underlying transcriptional and post-translational regulator...
Article
Full-text available
Background: Most biomolecular reaction modeling tools allow users to build models with a single list of parameter values. However, a common scenario involves different parameterizations of the model to account for the results of related experiments, for example, to define the phenotypes for a variety of mutations (gene knockout, over expression, e...
Article
Full-text available
In this study, we focus on a recent stochastic budding yeast cell cycle model. First, we estimate the model parameters using extensive data sets: phenotypes of 110 genetic strains, single cell statistics of wild type and cln3 strains. Optimization of stochastic model parameters is achieved by an automated algorithm we recently used for a determinis...
Article
Full-text available
Motivation: Building models of molecular regulatory networks is challenging not just because of the intrinsic difficulty of describing complex biological processes. Writing a model is a creative effort that calls for more flexibility and interactive support than offered by many of today's biochemical model editors. Our model editor MSMB - Multistat...
Article
Budding yeast cells are assumed to trigger Start and enter the cell cycle only after they attain a critical size set by external conditions. However, arguing against deterministic models of cell size control, cell volume at Start displays great individual variability even under constant conditions. Here we show that cell size at Start is robustly s...
Article
The cell cycle is controlled by complex regulatory network to ensure that the phases of the cell cycle happen in the right order and transitions between phases happen only if the earlier phase is properly finished. This regulatory network receives signals from the environment, monitors the state of the DNA, and decides when the cell can proceed in...
Chapter
We introduce a programming language called BlenX. It has been specifically designed and implemented to model and simulate biological systems and is strongly inspired to process calculi. We describe all the features of BlenX together with its supporting tools and show the application of the language on real case studies. KeywordsSystems biology-Mod...
Conference Paper
In biology, modelling is mainly grounded in mathematics, and specifically on ordinary differential equations (ODEs). Using programming languages originally thought to describe networks of computers that exchange information is a complementary and emergent approach to analyze the dynamics of biological networks. In this work, we focus on the process...
Article
It is currently attracting the interest of theoretical biologists, biochemicists and experimentalists to attempt to deduce the structure of biochemical networks "ab initio" from routinely available experimental data. The recent advances in systems biology have been driven by the methods that generate in vivo time-course data characterizing biochemi...
Article
Full-text available
Methods for parameter estimation that are robust to experimental uncertainties and to stochastic and biological noise and that require a minimum of a priori input knowledge are of key importance in computational systems biology. The new method presented in this paper aims to ensure an inference model that deduces the rate constants of a system of b...
Article
Full-text available
Cells life follows a cycling behaviour which starts at cell birth and leads to cell division through a number of distinct phases. The transitions through the various cell cycle phases are controlled by a complex network of signalling pathways. Many cell cycle transitions are irreversible: once they are started they must reach completion. In this st...
Article
Full-text available
Modeling in biology is mainly grounded in mathematics, and specifically on ordinary differential equations (ODE). The programming language approach is a complementary and emergent tool to analyze the dynamics of biological networks. Here we focus on BlenX showing how it is possible to easily re-use ODE models within this framework. A budding yeast...
Conference Paper
We present a new method for estimating rate coefficients and level of noise in models of biochemical networks from noisy observations of concentration levels at discrete time points. Its probabilistic formulation, based on maximum likelihood estimation, is key to a principled handling of the noise inherent in biological data, and it allows for a nu...
Conference Paper
We present a new method for estimating rate coefficients from noisy observations of concentration levels at discrete time points. Our inference method is based on a new maximum likelihood approach to the estimation of probability density function of the variations in reactant concentration. The inference procedure returns the rate coefficients with...
Conference Paper
In a deterministic conceptual framework the predictability of the time behavior of a system strongly depends of the exact knowledge of the initial conditions. Since the measures of the initial conditions are always affected by experimental uncertainties, the problem of the predictability of the system's behavior has to be reformulated and the conce...
Article
In this paper we describe a new maximum likelihood approach to infer kinetic rate constants from time-course data and apply it to estimate the rate constants of the synthesis and degradation of the mRNA of Cdc20 protein, and the rate constant of the transcription of the cdc20 gene into Cdc20 protein. The Cdc20 protein plays a crucial role in eukary...
Article
Full-text available
Cells life follows a cycling behaviour which starts at cell birth and leads to cell division through a number of distinct phases. The transitions through the various cell cycle phases are controlled by a complex network of signalling pathways. Many cell cycle transitions are irreversible: once they are started they must reach completion. In this st...
Article
Full-text available
The daily rhythm can influence the proliferation rate of many cell types. In the mammalian system the transcription of the cell cycle regulatory protein Wee1 is controlled by the circadian clock. Zamborszky et al. (2007) present a computational model coupling the cell cycle and circadian rhythm, showing that this coupling can lead to multimodal cel...
Article
Full-text available
The difference between patients with CFS patient and healthy ones could, in principle, be detected by examining a variety of data. We systematically used the CAMDA 2006 available data sets in order to assess the patients’ discrimination using supervised and unsupervised techniques. Our results suggest that data sets that are predictive are the clin...
Article
We present a novel method for estimating rate coefficients from noisy observations of concentration levels at discrete time points. This is traditionally done by computing the least-squares estimator. However, estimation of the error function generally requires solving the reaction rate equations, which can become computationally unfeasible. Here w...
Article
Classical modeling approaches for biology are mainly grounded in mathematics, and specifically on ordinary differential equations (ODE). Process calculi-based conceptual and computational tools are an alternative and emergent approach. Here we focus our analysis on BlenX (a beta-binders inspired programming language) showing how it is possible to e...
Article
The estimation of parameter values (model calibration) is the bottleneck of the computational analysis of biological systems. Modeling approaches are central in systems biology, as they provide a rational framework to guide systematic strategies for key issues in medicine as well as the pharmaceutical and biotechnological industries. Inter- and int...
Article
Dynamical models of inter- and intra-cellular processes contain the rate constants of the biochemical reactions. These kinetic parameters are often not accessible directly through experiments, but they can be inferred from time-resolved data. Time resolved data, that is, measurements of reactant concentration at series of time points, are usually a...

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