Structural and practical identifiability analysis of S-system
In the field of systems biology, biological reaction networks are usually modelled by ordinary differential equations. A sub-class, the S-systems representation, is a widely used form of modelling. Existing S-systems identification techniques assume that the system itself is always structurally identifiable. However, due to practical limitations, biological reaction networks are often only partially measured. In addition, the captured data only covers a limited trajectory, therefore data can only be considered as a local snapshot of the system responses with respect to the complete set of state trajectories over the entire...
Source: IET Systems Biology - November 20, 2015 Category: Biology Source Type: research
Modelling the role of catastrophe, crossover and katanin-mediated severing in the self-organisation of plant cortical microtubules
Plant cortical microtubules can form ordered arrays through interactions among themselves. When an incident microtubule collides with a barrier microtubule it may entrain if below a certain angle. Else it undergoes collision induced catastrophe (CIC) or crosses over the barrier microtubule. It has been proposed that katanin is necessary to create order by severing these crossover sites. The authors present a three-state computational model using Arabidopsis thaliana data to show how spontaneous catastrophe, the probability of CIC versus crossover, and katanin-mediated severing at the crossover sites affect microtubule orde...
Source: IET Systems Biology - November 20, 2015 Category: Biology Source Type: research
Investigating receptor enzyme activity using time-scale analysis
At early drug discovery, purified protein-based assays are often used to characterise compound potency. In the context of dose response, it is often perceived that a time-independent inhibitor is reversible and a time-dependent inhibitor is irreversible. The legitimacy of this argument is investigated using a simple kinetics model, where it is revealed by model-based analytical analysis and numerical studies that dose response of an irreversible inhibitor may appear time-independent under certain parametric conditions. Hence, the observation of time-independence cannot be used as sole evidence for identification of inhibit...
Source: IET Systems Biology - November 20, 2015 Category: Biology Source Type: research
Theoretical cross-comparative analysis on dynamics of small intestine and colon crypts during cancer initiation
Epigenetics is emerging as a fundamentally important area of biological and medical research that has implications for our understanding of human diseases including cancer, autoimmune and neuropsychiatric disorders. In the context of recent efforts on personalised medicine, a novel research direction is concerned with identification of intra-individual epigenetic variation linked to disease predisposition and development, i.e. epigenome-wide association studies. A computational model has been developed to describe the dynamics and structure of human intestinal crypts and to perform a comparative analysis on aberrant DNA me...
Source: IET Systems Biology - November 20, 2015 Category: Biology Source Type: research
Integrated dopaminergic neuronal model with reduced intracellular processes and inhibitory autoreceptors
In this study, the authors aim to develop a realistic yet efficient computational model of a dopaminergic pre-synaptic terminal. They first systematically perturb the variables/substrates of an established computational model of DA synthesis, release and uptake, and based on their relative dynamical timescales and steady-state changes, approximate and reduce the model into two versions: one for simulating hourly timescale, and another for millisecond timescale. They show that the original and reduced models exhibit rather similar steady and perturbed states, whereas the reduced models are more computationally efficient and...
Source: IET Systems Biology - November 20, 2015 Category: Biology Source Type: research
Deploying swarm intelligence in medical imaging identifying metastasis, micro-calcifications and brain image segmentation
This study proposes an umbrella deployment of swarm intelligence algorithm, such as stochastic diffusion search for medical imaging applications. After summarising the results of some previous works which shows how the algorithm assists in the identification of metastasis in bone scans and microcalcifications on mammographs, for the first time, the use of the algorithm in assessing the CT images of the aorta is demonstrated along with its performance in detecting the nasogastric tube in chest X-ray. The swarm intelligence algorithm presented in this study is adapted to address these particular tasks and its functionality i...
Source: IET Systems Biology - November 20, 2015 Category: Biology Source Type: research
Computational approaches for understanding the diagnosis and treatment of Parkinson's disease
This study describes how the application of evolutionary algorithms (EAs) can be used to study motor function in humans with Parkinson's disease (PD) and in animal models of PD. Human data is obtained using commercially available sensors via a range of non-invasive procedures that follow conventional clinical practice. EAs can then be used to classify human data for a range of uses, including diagnosis and disease monitoring. New results are presented that demonstrate how EAs can also be used to classify fruit flies with and without genetic mutations that cause Parkinson's by using measurements of the proboscis extension r...
Source: IET Systems Biology - November 20, 2015 Category: Biology Source Type: research
Ant colony optimisation of decision tree and contingency table models for the discovery of gene–gene interactions
In this study, ant colony optimisation (ACO) algorithm is used to derive near-optimal interactions between a number of single nucleotide polymorphisms (SNPs). This approach is used to discover small numbers of SNPs that are combined into a decision tree or contingency table model. The ACO algorithm is shown to be very robust as it is proven to be able to find results that are discriminatory from a statistical perspective with logical interactions, decision tree and contingency table models for various numbers of SNPs considered in the interaction. A large number of the SNPs discovered here have been already identified in l...
Source: IET Systems Biology - November 20, 2015 Category: Biology Source Type: research
Computational Models & Methods in Systems Biology & Medicine
(Source: IET Systems Biology)
Source: IET Systems Biology - November 20, 2015 Category: Biology Source Type: research
Dynamic model of eicosanoid production with special reference to non-steroidal anti-inflammatory drug-triggered hypersensitivity
The authors developed a mathematical model of arachidonic acid (AA) degradation to prostaglandins (PGs) and leukotrienes (LTs), which are implicated in the processes of inflammation and hypersensitivity to non-steroidal anti-inflammatory drugs (NSAIDs). The model focuses on two PGs (PGE2 and PGD2) and one LT (LTC4), their % increases and their ratios. Results are compared with experimental studies obtained from non-asthmatics (NAs), and asthmatics tolerant (ATA) or intolerant (AIA) to aspirin. Simulations are carried out for predefined model populations NA, ATA and three AIA, based on the differences of two enzymes, PG E s...
Source: IET Systems Biology - September 29, 2015 Category: Biology Source Type: research
Identifying latent dynamic components in biological systems
In computational systems biology, the general aim is to derive regulatory models from multivariate readouts, thereby generating predictions for novel experiments. In the past, many such models have been formulated for different biological applications. The authors consider the scenario where a given model fails to predict a set of observations with acceptable accuracy and ask the question whether this is because of the model lacking important external regulations. Real-world examples for such entities range from microRNAs to metabolic fluxes. To improve the prediction, they propose an algorithm to systematically extend the...
Source: IET Systems Biology - September 29, 2015 Category: Biology Source Type: research
Deterministic inference for stochastic systems using multiple shooting and a linear noise approximation for the transition probabilities
This study presents an extension to the ‘multiple shooting for stochastic systems (MSS)’ method for parameter estimation. The transition probabilities of the likelihood function are approximated with normal distributions. Means and variances are calculated with a linear noise approximation on the interval between succeeding measurements. The fact that the system is only approximated on intervals which are short in comparison with the total observation horizon allows to deal with effects of the intrinsic stochasticity. The study presents scenarios in which the extension is essential for successfully estimating...
Source: IET Systems Biology - September 29, 2015 Category: Biology Source Type: research
Positive selection on D-lactate dehydrogenases of Lactobacillus delbrueckii subspecies bulgaricus
Lactobacillus delbrueckii has been widely used for yogurt fermentation. It has genes encoding both D- and L-type lactate dehydrogenases (LDHs) that catalyse the production of L(+) or D(−) stereoisomer of lactic acid. D-lactic acid is the primary lactate product by L. delbrueckii, yet it cannot be metabolised by human intestine. Since it has been domesticated for long time, an interesting question arises regarding to whether the selection pressure has affected the evolution of both L-LDH and D-LDH genes in the genome. To answer this question, in this study the authors first investigated the evolution of these two gen...
Source: IET Systems Biology - August 11, 2015 Category: Biology Source Type: research
Systematic functional genomics resource and annotation for poplar
Poplar, as a model species for forestry research, has many excellent characteristics. Studies on functional genes have provided the foundation, at the molecular level, for improving genetic traits and cultivating elite lines. Although studies on functional genes have been performed for many years, large amounts of experimental data remain scattered across various reports and have not been unified via comprehensive statistical analysis. This problem can be addressed by employing bioinformatic methodology and technology to gather and organise data to construct a Poplar Functional Gene Database, containing data on 207 poplar ...
Source: IET Systems Biology - August 11, 2015 Category: Biology Source Type: research
Prediction of human disease-associated phosphorylation sites with combined feature selection approach and support vector machine
Phosphorylation is a crucial post-translational modification, which regulates almost all cellular processes in life. It has long been recognised that protein phosphorylation has close relationship with diseases, and therefore many researches are undertaken to predict phosphorylation sites for disease treatment and drug design. However, despite the success achieved by these approaches, no method focuses on disease-associated phosphorylation sites prediction. Herein, for the first time the authors propose a novel approach that is specially designed to identify associations between phosphorylation sites and human diseases. To...
Source: IET Systems Biology - August 11, 2015 Category: Biology Source Type: research
