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PubMed1995

The mobility analog for modeling the intra-arterial pressure wave parameters.

To assist in the identification of physical/physiological parameters obtained from in vivo rat aortic artery dynamic pressure data, the natural (mobility) mechanical circuit model was constructed. The direct electrical analog of the model thus obtained was then analyzed using SPICE. The experimental data were obtained using a Multifunction Pressure Generator (MPG), appropriate pressure probes, and a high-speed video camera. Two 486 computers were used for system control and data recording and computation. Transfer functions in rational form of the ratio of the MPG input pressure (Pi) to the intra-arterial pressure (Po) were then generated in the s-domain. The mechanical circuit described by these rational functions was then constructed and transformed into its equivalent electrical model for analysis. On this basis, physiological pressures are represented by electrical currents, and volume flow rates by electrical voltages. The results obtained through steady-state (Bode plot) and transient analysis of the model developed suggest a compartmental model that explains the experimental observations. The mobility model is an improvement over previous models in that the mass element is referred to a single frame of reference, which agrees with the physical property that mass is a one-terminal device.

Animals↗

PubMed2004

Use of an anaerobic sequencing batch reactor for parameter estimation in modelling of anaerobic digestion.

The model structure in anaerobic digestion has been clarified following publication of the IWA Anaerobic Digestion Model No. 1 (ADM1). However, parameter values are not well known, and uncertainty and variability in the parameter values given is almost unknown. Additionally, platforms for identification of parameters, namely continuous-flow laboratory digesters, and batch tests suffer from disadvantages such as long run times, and difficulty in defining initial conditions, respectively. Anaerobic sequencing batch reactors (ASBRs) are sequenced into fill-react-settle-decant phases, and offer promising possibilities for estimation of parameters, as they are by nature, dynamic in behaviour, and allow repeatable behaviour to establish initial conditions, and evaluate parameters. In this study, we estimated parameters describing winery wastewater (most COD as ethanol) degradation using data from sequencing operation, and validated these parameters using unsequenced pulses of ethanol and acetate. The model used was the ADM1, with an extension for ethanol degradation. Parameter confidence spaces were found by non-linear, correlated analysis of the two main Monod parameters; maximum uptake rate (k(m)), and half saturation concentration (K(S)). These parameters could be estimated together using only the measured acetate concentration (20 points per cycle). From interpolating the single cycle acetate data to multiple cycles, we estimate that a practical "optimal" identifiability could be achieved after two cycles for the acetate parameters, and three cycles for the ethanol parameters. The parameters found performed well in the short term, and represented the pulses of acetate and ethanol (within 4 days of the winery-fed cycles) very well. The main discrepancy was poor prediction of pH dynamics, which could be due to an unidentified buffer with an overall influence the same as a weak base (possibly CaCO3). Based on this work, ASBR systems are effective for parameter estimation, especially for comparative wastewater characterisation. The main disadvantages are heavy computational requirements for multiple cycles, and difficulty in establishing the correct biomass concentration in the reactor, though the last is also a disadvantage for continuous fixed film reactors, and especially, batch tests.

Acetates↗

PubMed1998

Multiple parameter cross-species protein identification using MultiIdent--a world-wide web accessible tool.

Recent increases in the number of genome sequencing projects means that the amount of protein sequence in databases is increasing at an astonishing pace. In proteome studies, this is facilitating the identification of proteins from molecularly well-defined organisms. However, in studies of proteins from the majority of organisms, proteins must be identified by comparing analytical data to sequences in databases from other species. This process is known as cross-species protein identification. Here we present a new program, MultiIdent, which uses multiple protein parameters such as amino acid composition, peptide masses, sequence tags, estimated protein pI and mass, to achieve cross-species protein identification. The program is structured so that protein amino acid composition, which is highly conserved across species boundaries, first generates a set of candidate proteins. These proteins are then queried with other protein parameters such as sequence tags and peptide masses. A final list of database entries which considers all analytical parameters is presented, ranked by an integrated score. We illustrate the power of the approach with the identification of a set of standard proteins, and the identification of proteins from dog heart separated by two-dimensional gel electrophoresis. The MultiIdent program is available on the world-wide web at: http://www.expasy.ch/sprot/multiident.h tml.

Amino Acid Sequence↗

PubMed1987

A graphical approach to the identification and estimation of causal parameters in mortality studies with sustained exposure periods.

In observational cohort mortality studies with prolonged periods of exposure to the agent under study, independent risk factors for death commonly determine subsequent exposure to the study agent. For example, in occupational mortality studies, date of termination of employment is both a determinant of subsequent exposure to the chemical agent under study (since terminated individuals receive no further exposure) and an independent risk factor for death (since disabled individuals tend to leave employment). When a risk factor determines subsequent exposure and is determined by previous exposure, standard analyses that estimate age-specific mortality rates as a function of cumulative exposure can underestimate the true effect of exposure on mortality, whether or not one adjusts for the risk factor in the analysis. This observation raises the question, "Which, if any, empirical population parameter can be causally interpreted as the true effect of exposure in observational mortality studies?" In answer, we offer a graphical approach to the identification and estimation of causal parameters in mortality studies with sustained exposure periods. We reanalyze the mortality experience of a cohort of arsenic-exposed copper smelter workers using our approach and compare our results with those obtained using standard methods. We find an adverse effect of arsenic exposure on all cause and lung cancer mortality, which standard methods failed to detect. The analytic approach introduced in this paper may be necessary to control bias in any epidemiologic study in which there exists a risk factor which both determines subsequent exposure and is determined by previous exposure to the agent under study.

Epidemiologic Methods↗

PubMed2000

Cerebral hemodynamics during arterial and CO(2) pressure changes: in vivo prediction by a mathematical model.

The aim of this work was to analyze changes in cerebral hemodynamics and intracranial pressure (ICP) evoked by mean systemic arterial pressure (SAP) and arterial CO(2) pressure (Pa(CO(2))) challenges in patients with acute brain damage. The study was performed by means of a new simple mathematical model of intracranial hemodynamics, particularly aimed at routine clinical investigation. The model was validated by comparing its results with data from transcranial Doppler velocity in the middle cerebral artery (V(MCA)) and ICP measured in 44 tracings on 13 different patients during mean SAP and Pa(CO(2)) challenges. The validation consisted of individual identification of 6 parameters in all 44 tracings by means of a best fitting algorithm. The parameters chosen for the identification summarize the main aspects of intracranial dynamics, i.e., cerebrospinal fluid circulation, intracranial elastance, and cerebrovascular control. The results suggest that the model is able to reproduce the measured time patterns of V(MCA) and ICP in all 44 tracings by using values for the parameters that lie within the ranges reported in the pathophysiological literature. The meaning of parameter estimates is discussed, and comments on the main virtues and limitations of the present approach are offered.

Adolescent↗

PubMed2006

Closed-loop nonlinear system identification via the vector optimal parameter search algorithm: application to heart rate baroreflex control.

The vector optimal parameter search (VOPS) and the constrained optimal parameter search (COPS) are recently developed algorithms for closed-loop linear system identification. We extend both algorithms to be applicable to a closed-loop nonlinear system, which is characterized by a vector nonlinear autoregressive model. Monte Carlo simulations of nonlinear closed-loop systems were performed to compare the performance of the VOPS to the widely utilized vector least squares (VLS), the COPS and the total least squares (TLS) approaches. The relative error and linear transfer functions are computed to determine the accuracy of each method. The comparative results show that both the VOPS and COPS algorithms provide far superior parameter estimates than does the VLS for all simulation examples considered. The TLS provides better estimates than the VOPS, COPS and VLS when there is only observation noise present in the data. However, the performance of the TLS degrades considerably when the data are corrupted by dynamic noise. The clinical applicability of the two extended methods is examined by applying them to a classical physiological closed-loop system, the heart rate baroreflex. It was found that while both control and blockade of parasympathetic system conditions are dominated by linear dynamics, more nonlinearity was observed in the latter. This observation is statistically supported by the calculation of the mutual information of the data and their surrogates.

Algorithms↗

PubMed1989

On-line identification of the state and parameters for fed-batch penicillin fermentation process.

A mathematical model with noises which is suitable for penicillin fed-batch fermentation in factory has been presented. By taking the carbon dioxide production rate as an online measured variable, an extended Kalman filter (EKF) was used for the real-time identification of the state and parameters. The study offers a basis for the adaptive optimal control of fermentation processes. It is shown that the estimated values of state by EKF coincide with the experimental data. The results prove that the filter is a better online observer for the state of fermentation process and dynamical parameters.

Algorithms↗

PubMed1993

A simple computational approach to model parameter estimation.

The desire to describe biological data using mathematical models has led to the rapid development of various analytical techniques for model identification and parameter estimation. The procedures used may be non-linear and complex, and require long calculation periods. Thus, the aid of a personal computer renders efficient the application of these rather complicated procedures. In this study we developed a simple identification programme for heparan sulfate pharmacodynamics which can be easily and rapidly implemented on a personal computer. The programme is based on an iterative algorithm performing a non-linear regression analysis by the least-square method. This programme was applied to a clinical measured variables with which it was possible to quantify the pharmacodynamic effect of heparan sulfate.

Aged↗

PubMed1980

Critical parameters in the microcarrier culture of animal cells.

The successful culture of over 60 different cell types on Cytodex TM1 microcarriers has enabled identification of parameters critical for obtaining high cell yields from microcarrier cultures. Careful control of the initial phase of microcarrier culture was found to be critical. Increasing cell density, reducing culture volume and reducing stirring rate during the initial phase all assisted in improving cell yields. Control of pH, inoculum condition, nutrient supply and serum quality, and elimination of mycoplasma were all vital for high cell yields. Knowledge of the in vitro growth properties of the cells made it easier to arrive at optimal conditions for microcarrier culture of each cell type.

Animals↗

PubMed2000

[Rheologic properties of viscoelastic materials--identification of models and estimation of parameters].

The methodology of description and quantification of mechanical properties of visco-elastic materials is particularly important for drug production as well as for pharmaceutical applications. Of similar importance is this methodology for biomechanics and other biological disciplines, as many biological materials belong to the category of visco-elastic bodies. Methods derived from the theory of elastic bodies or hydrodynamics are not adequate for the quantification of mechanical properties of these materials. Application of more general rheological methods is necessary in these cases. In rheology, the so-called creep curves are most frequently used as a source of information on the mechanical behavior of visco-elastic materials. Further, for more exact analysis, rheological models are often derived from the creep curves. Classical methods of identification and parameter estimation of rheological models are not sufficiently general and do not derive all information involved in creep curves. A significant contribution is the application of the general theory of systems, theory of system identification, and mathematical methodology of Laplace transformation to this field. Practical application of these methods is often relatively simple. The paper presents the necessary theoretical background and a practical guide for utilization of this methodology.

Elasticity↗

PubMedDate not supplied

Identification algorithm for systemic arterial parameters with application to total artificial heart control.

A new algorithm for estimating systemic arterial parameters from systolic pressure and flow measurements at the root of the aorta is developed and tested through a systems identification approach. The resulting procedure has direct application to a total artificial heart (TAH) control system currently under development. Identification models, representing the systemic arterial system, are developed from existing work in the area of cardiovascular modeling. The resistive and compliance components of these models are physically significant, representing overall hydraulic properties of the systemic arterial system. A unique method of parameterizing the identification models is designed which operates on the basis of aortic pressure and flow measurements taken exclusively during systole. The estimator is a modified recursive least squares algorithm which utilizes covariance modification to track time-varying parameters and a dead-zone to improve the robustness. Performance of the estimation algorithm was tested on data generated by a higher-order distributed model of the systemic arterial bed using normal canine parameters. Results from model-to-model experiments verify the consistency of the estimates and the ability of the estimator to converge quickly and track dynamically varying parameters.

Adaptation, Physiological↗

PubMed1996

Incorporating Monte Carlo simulation into physiologically based pharmacokinetic models using advanced continuous simulation language (ACSL): a computational method.

Biologically based models with physiological parameters are becoming more popular as a tool to estimate target tissue doses from chemical exposures. However, the majority of current physiologically based pharmacokinetic (PBPK) models do not take into account the uncertainty and/or variability within the various model parameters. Consideration of uncertainty is important to evaluate the predictive ability and complexity of a model as well as identification of parameters which contribute disproportionately to variability in model output. In order to estimate the uncertainty in PBPK model output, a versatile and simple computational method is presented which can be readily incorporated into the majority of PBPK models without extensive additions to model computer code. In this paper, a separate computer program for Monte Carlo simulation is furnished that randomly samples values for model parameters and writes them into a run-time language (command file) format which can then be utilized to execute individual PBPK models. Modifications to the PBPK model allow the desired output to be written to a data file for statistical analysis. The method presented in this paper is applied to a simple PBPK model for benzene disposition.

Algorithms↗

PubMed1996

[Analysis of measurements: arterial blood pressure, pulse rate and oxygen saturation in arterial blood during broncho-fibroscopy and bronchoalveolar lavage in patients with bronchial asthma and chronic bronchitis].

Bronchial asthma and chronic bronchitis in stable period of disease could be an indication for diagnostic bronchofiberoscopy and broncho-alveolar lavage (BAL). 30 patients with bronchial asthma (aged 27.2 +/- 9.3), 30 patients with chronic bronchitis (aged 55.9 +/- 11.0) and subjects of control group (aged 27.0 +/- 9.7) took part in this study. Selected parameters: heart rate (HR), arterial blood pressure (ABP) and arterial O2 saturation (SaO2) monitored by pulsoximetry were measured during the procedure. It was showed that broncho-fibroscopy and BAL could be performed safe in patients with asthma and chronic bronchitis as well. Bronchospasm was observed only in one subject with asthma. The highest decrease of saturation was observed during BAL in every investigated subject. Because of none of recorded parameters allows identification of the patients at risk of poor tolerance of the procedure, we propose close observation of patient, monitoring parameters: HR, ABP and SaO2, and oxygen supplementation during the investigation.

Adult↗

PubMedDate not supplied

A thermodynamic model to predict the thermal response of living beings during pneumoperitoneum procedures.

In this work, hypothermia associated with pneumoperitoneum procedures is studied. A thermodynamic model is developed to allow for the computational simulation of the thermal body response to pneumoperitoneum procedures, which are required by laparoscopic surgery. The numerical results predict the body temperature decay (or loss of energy) in time when the pneumoperitoneum procedures is conducted in patient. The influence of several operating parameters (e.g. inlet air mass flow rate and temperature) on the resulting hypothermia level is analysed. Therefore, the model allows the identification of parameters that have to be controlled to minimize the loss of energy, and consequently, the hypothermia level due to pneumoperitoneum procedures.

Body Temperature Regulation↗

PubMedDate not supplied

Identification of critical batch operating parameters in fed-batch recombinant E. coli fermentations using decision tree analysis.

To develop a useful fermentation process model, it is first necessary to identify which batch operating parameters are critical in determining the process outcome. To identify critical processing inputs in large databases, we have explored the use of Decision Tree Analysis with the decision metrics of Gain (i.e., Shannon Entropy changes), Gain Ratio, and a multiple hypergeometric distribution. The usefulness of this approach lies in its ability to treat "categorical" variables, which are typical of archived fermentation databases, as well as "continuous" variables. In this work, we demonstrate the use of Decision Tree Analysis for the problem of optimizing recombinant green fluorescent protein production in E. coli. A database of 85 fermentations was generated to examine the effect of 15 process input parameters on final biomass yield, maximum recombinant protein concentration, and productivity. The use of Decision Tree Analysis led to a considerable reduction in the fermentation database through the identification of the significant as well as insignificant inputs. However, different decision metrics selected different inputs and different numbers of inputs to classify the data for each output.

Algorithms↗

PubMed2005

GeneLook: a novel ab initio gene identification system suitable for automated annotation of prokaryotic sequences.

With the rapid increases in the amounts of sequence data for prokaryotic genomes, it has become important to develop systems for automated and accurate genome annotation. We present herein a novel ab initio gene identification system, GeneLook, that predicts protein-coding open reading frames (ORFs) with high sensitivity and specificity with no prior knowledge of the sequence composition. The system predicts protein-coding ORFs in two stages, seed ORF selection and main prediction. In the selection of reliable seed ORFs containing at least 200 codons, GeneLook predicts translation start sites and operon structures through searches for ribosome-binding sites and a novel operon prediction algorithm. The codon and nucleotide frequencies of seed ORFs are then used to determine values for two new coding-potential parameters for identification of protein-coding ORFs of at least 34 codons and for another parameter that improves the prediction accuracy for GC-rich genomes. In the main prediction, GeneLook uses these parameters to identify the most likely genes of a given minimal length. We assessed the performance of GeneLook with two indices, sensitivity and specificity that are defined as true positives (TP)/(TP+false negatives) and TP/(TP+false positives), respectively. This system predicted protein-coding ORFs for Escherichia coli and Bacillus subtilis with sensitivities of 96.5% and 96.2%, respectively, and specificities of 96.9% and 96.1%, respectively. The system also identified 94.1% of annotated genes of the Pseudomonas aeruginosa genome, which is GC-rich, with high specificity (97.2%). Furthermore, GeneLook identified protein-coding ORFs with high accuracy from a wide variety of prokaryotic genomes.

Bacillus subtilis↗

PubMed2005

Protein pI shifts due to posttranslational modifications in the separation and characterization of proteins.

Proteins from breast cancer cell lines are characterized using a 2-D liquid separation technique in which protein pI is used as the first-dimension separation parameter. To effect this protein pI separation, chromatofocusing(CF) is employed whereby a pH gradient is generated on-column using a weak anion exchange medium with the intact proteins fractionated and collected every 0.2 pH unit. It is demonstrated that the pI for expressed intact proteins as generated by CF is an important parameter for identification and characterization of the actual protein modifications occurring in the cancer cell. For most proteins, the experimentally determined pI is very close to that predicted by the databases. In other cases, however, where the pI is observed to be shifted from the expected value, it is shown that this shift is often correlated to protein modifications. The modifications that cause such shifts include truncations and deletions often observed in cancer cells or phosphorylations that can shift the pI by several pH units. It is also shown that the effects of phosphorylation on the observed shift can vary depending upon the protein and the amount of phosphorylation. Moreover, large changes in the pI are often observed for proteins with a pI above 7.0 upon phosphorylation, whereas little change is observed for proteins with a pI of approximately 5.0. The expressed protein's pI value thus becomes an important parameter together with the intact MW value, peptide map, and MS/MS results for identification of the presence and type of posttranslational modifications occurring in the cancer cell.

Amino Acid Sequence↗

PubMed2006

MUSA: a parameter free algorithm for the identification of biologically significant motifs.

MOTIVATION: The ability to identify complex motifs, i.e. non-contiguous nucleotide sequences, is a key feature of modern motif finders. Addressing this problem is extremely important, not only because these motifs can accurately model biological phenomena but because its extraction is highly dependent upon the appropriate selection of numerous search parameters. Currently available combinatorial algorithms have proved to be highly efficient in exhaustively enumerating motifs (including complex motifs), which fulfill certain extraction criteria. However, one major problem with these methods is the large number of parameters that need to be specified. RESULTS: We propose a new algorithm, MUSA (Motif finding using an UnSupervised Approach), that can be used either to autonomously find over-represented complex motifs or to estimate search parameters for modern motif finders. This method relies on a biclustering algorithm that operates on a matrix of co-occurrences of small motifs. The performance of this method is independent of the composite structure of the motifs being sought, making few assumptions about their characteristics. The MUSA algorithm was applied to two datasets involving the bacterium Pseudomonas putida KT2440. The first one was composed of 70 sigma(54)-dependent promoter sequences and the second dataset included 54 promoter sequences of up-regulated genes in response to phenol, as suggested by quantitative proteomics. The results obtained indicate that this approach is very effective at identifying complex motifs of biological significance. AVAILABILITY: The MUSA algorithm is available upon request from the authors, and will be made available via a Web based interface.

Algorithms↗