Displaying publications 1 - 20 of 602 in total

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  1. Quek A, Kassim NK, Lim PC, Tan DC, Mohammad Latif MA, Ismail A, et al.
    Pharm Biol, 2021 Dec;59(1):964-973.
    PMID: 34347568 DOI: 10.1080/13880209.2021.1948065
    CONTEXT: Melicope latifolia (DC.) T. G. Hartley (Rutaceae) was reported to contain various phytochemicals including coumarins, flavonoids, and acetophenones.

    OBJECTIVE: This study investigates the antidiabetic and antioxidant effects of M. latifolia bark extracts, fractions, and isolated constituents.

    MATERIALS AND METHODS: Melicope latifolia extracts (hexane, chloroform, and methanol), fractions, and isolated constituents with varying concentrations (0.078-10 mg/mL) were subjected to in vitro α-amylase and dipeptidyl peptidase-4 (DPP-4) inhibitory assay. Molecular docking was performed to study the binding mechanism of active compounds towards α-amylase and DPP-4 enzymes. The antioxidant activity of M. latifolia fractions and compounds were determined by 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging and β-carotene bleaching assays.

    RESULTS: Melicope latifolia chloroform extract showed the highest antidiabetic activity (α-amylase IC50: 1464.32 μg/mL; DPP-4 IC50: 221.58 μg/mL). Fractionation of chloroform extract yielded four major fractions (CF1-CF4) whereby CF3 showed the highest antidiabetic activity (α-amylase IC50: 397.68 μg/mL; DPP-4 IC50: 37.16 μg/mL) and resulted in β-sitosterol (1), halfordin (2), methyl p-coumarate (3), and protocatechuic acid (4). Isolation of compounds 2-4 from the species and their DPP-4 inhibitory were reported for the first time. Compound 2 showed the highest α-amylase (IC50: 197.53 μM) and β-carotene (88.48%) inhibition, and formed the highest number of molecular interactions with critical amino acid residues of α-amylase. The highest DPP-4 inhibition was exhibited by compound 3 (IC50: 911.44 μM).

    DISCUSSION AND CONCLUSIONS: The in vitro and in silico analyses indicated the potential of M. latifolia as an alternative source of α-amylase and DPP-4 inhibitors. Further pharmacological studies on the compounds are recommended.

    Matched MeSH terms: Computer Simulation
  2. Uddin MJ, Khan WA, Amin NS
    PLoS One, 2014;9(6):e99384.
    PMID: 24927277 DOI: 10.1371/journal.pone.0099384
    The unsteady two-dimensional laminar g-Jitter mixed convective boundary layer flow of Cu-water and Al2O3-water nanofluids past a permeable stretching sheet in a Darcian porous is studied by using an implicit finite difference numerical method with quasi-linearization technique. It is assumed that the plate is subjected to velocity and thermal slip boundary conditions. We have considered temperature dependent viscosity. The governing boundary layer equations are converted into non-similar equations using suitable transformations, before being solved numerically. The transport equations have been shown to be controlled by a number of parameters including viscosity parameter, Darcy number, nanoparticle volume fraction, Prandtl number, velocity slip, thermal slip, suction/injection and mixed convection parameters. The dimensionless velocity and temperature profiles as well as friction factor and heat transfer rates are presented graphically and discussed. It is found that the velocity reduces with velocity slip parameter for both nanofluids for fluid with both constant and variable properties. It is further found that the skin friction decreases with both Darcy number and momentum slip parameter while it increases with viscosity variation parameter. The surface temperature increases as the dimensionless time increases for both nanofluids. Nusselt numbers increase with mixed convection parameter and Darcy numbers and decreases with the momentum slip. Excellent agreement is found between the numerical results of the present paper with published results.
    Matched MeSH terms: Computer Simulation
  3. Salehi Z, Ya Ali NK, Yusoff AL
    Appl Radiat Isot, 2012 Nov;70(11):2586-9.
    PMID: 22940409 DOI: 10.1016/j.apradiso.2011.12.007
    BEAMnrc was used to derive the X-ray spectra, from which HVL and homogeneity coefficient were determined, for different kVp and filtration settings. Except for the peak at 61 keV, the spectra are in good agreement with the IPEM report 78 data for the case of filtered beams, whereas the unfiltered beams exhibit softer spectra. Although the current attenuation data deviates from the IPEM 78 data by ~±0.5%, this has negligible effects on the calculated HVL values.
    Matched MeSH terms: Computer Simulation
  4. Al-Saiagh W, Tiun S, Al-Saffar A, Awang S, Al-Khaleefa AS
    PLoS One, 2018;13(12):e0208695.
    PMID: 30571777 DOI: 10.1371/journal.pone.0208695
    Word sense disambiguation (WSD) is the process of identifying an appropriate sense for an ambiguous word. With the complexity of human languages in which a single word could yield different meanings, WSD has been utilized by several domains of interests such as search engines and machine translations. The literature shows a vast number of techniques used for the process of WSD. Recently, researchers have focused on the use of meta-heuristic approaches to identify the best solutions that reflect the best sense. However, the application of meta-heuristic approaches remains limited and thus requires the efficient exploration and exploitation of the problem space. Hence, the current study aims to propose a hybrid meta-heuristic method that consists of particle swarm optimization (PSO) and simulated annealing to find the global best meaning of a given text. Different semantic measures have been utilized in this model as objective functions for the proposed hybrid PSO. These measures consist of JCN and extended Lesk methods, which are combined effectively in this work. The proposed method is tested using a three-benchmark dataset (SemCor 3.0, SensEval-2, and SensEval-3). Results show that the proposed method has superior performance in comparison with state-of-the-art approaches.
    Matched MeSH terms: Computer Simulation
  5. Wahab HA, Amaro RE, Cournia Z
    J Chem Inf Model, 2018 11 26;58(11):2175-2177.
    PMID: 30277769 DOI: 10.1021/acs.jcim.8b00642
    Matched MeSH terms: Computer Simulation
  6. Al-Samman AM, Azmi MH, Rahman TA, Khan I, Hindia MN, Fattouh A
    PLoS One, 2016;11(12):e0164944.
    PMID: 27992445 DOI: 10.1371/journal.pone.0164944
    This work proposes channel impulse response (CIR) prediction for time-varying ultra-wideband (UWB) channels by exploiting the fast movement of channel taps within delay bins. Considering the sparsity of UWB channels, we introduce a window-based CIR (WB-CIR) to approximate the high temporal resolutions of UWB channels. A recursive least square (RLS) algorithm is adopted to predict the time evolution of the WB-CIR. For predicting the future WB-CIR tap of window wk, three RLS filter coefficients are computed from the observed WB-CIRs of the left wk-1, the current wk and the right wk+1 windows. The filter coefficient with the lowest RLS error is used to predict the future WB-CIR tap. To evaluate our proposed prediction method, UWB CIRs are collected through measurement campaigns in outdoor environments considering line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios. Under similar computational complexity, our proposed method provides an improvement in prediction errors of approximately 80% for LOS and 63% for NLOS scenarios compared with a conventional method.
    Matched MeSH terms: Computer Simulation
  7. Zainuddin Z, Wan Daud WR, Pauline O, Shafie A
    Bioresour Technol, 2011 Dec;102(23):10978-86.
    PMID: 21996481 DOI: 10.1016/j.biortech.2011.09.080
    In the organosolv pulping of the oil palm fronds, the influence of the operational variables of the pulping reactor (viz. cooking temperature and time, ethanol and NaOH concentration) on the properties of the resulting pulp (yield and kappa number) and paper sheets (tensile index and tear index) was investigated using a wavelet neural network model. The experimental results with error less than 0.0965 (in terms of MSE) were produced, and were then compared with those obtained from the response surface methodology. Performance assessment indicated that the neural network model possessed superior predictive ability than the polynomial model, since a very close agreement between the experimental and the predicted values was obtained.
    Matched MeSH terms: Computer Simulation
  8. Shalayel MH, Al-Mazaideh GM, Aladaileh SH, Al-Swailmi FK, Al-Thiabat MG
    Pak J Pharm Sci, 2020 Sep;33(5):2179-2186.
    PMID: 33824127
    Novel coronavirus disease (COVID-19) has become a pandemic threat to public health. Vaccines and targeted therapeutics to prevent infections and stop virus proliferation are currently lacking. Endoribonuclease Nsp15 plays a vital role in the life cycle, including replication and transcription as well as virulence of the virus. Here, we investigated Vitamin D for its in silico potential inhibition of the binding sites of SARS-CoV-2 endoribonuclease Nsp15. In this study, we selected Remdesivir, Chloroquine, Hydroxychloroquine and Vitamin D to study the potential binding affinity with the putative binding sites of endoribonuclease Nsp15 of COVID-19. The docking study was applied to rationalize the possible interactions of the target compounds with the active site of endoribonuclease Nsp 15. Among the results, Vitamin D was found to have the highest potency with strongest interaction in terms of LBE, lowest RMSD, and lowest inhibition intensity Ki than the other standard compounds. The investigation results of endoribonuclease Nsp15 on the PrankWeb server showed that there are three prospective binding sites with the ligands. The singularity of Vitamin D interaction with the three pockets, particularly in the second pocket, may write down Vitamin D as a potential inhibitor of COVID-19 Nsp15 endoribonuclease binding sites and favour addition of Vitamin D in the treatment plan for COVID-19 alone or in combination with the other used drugs in this purpose, which deserves exploration in further in vitro and in vivo studies.
    Matched MeSH terms: Computer Simulation
  9. Athani A, Ghazali NNN, Anjum Badruddin I, Kamangar S, Salman Ahmed NJ, Honnutagi A
    Biomed Mater Eng, 2023;34(1):13-35.
    PMID: 36278331 DOI: 10.3233/BME-211333
    BACKGROUND: Coronary arteries disease has been reported as one of the principal roots of deaths worldwide.

    OBJECTIVE: The aim of this study is to analyze the multiphase pulsatile blood flow in the left coronary artery tree with stenosis.

    METHODS: The 3D left coronary artery model was reconstructed using 2D computerized tomography (CT) scan images. The Red Blood Cell (RBC) and varying hemodynamic parameters for single and multiphase blood flow conditions were analyzed.

    RESULTS: Results asserted that the multiphase blood flow modeling has a maximum velocity of 1.017 m/s and1.339 m/s at the stenosed region during the systolic and diastolic phases respectively. The increase in Wall Shear Stress (WSS) observed at the stenosed region during the diastole phase as compared during the systolic phase. It was also observed that the highest Oscillatory Shear Index (OSI) regions are found in the downstream area of stenosis and across the bifurcations. The increase in RBCs velocity from 0.45 m/s to 0.6 m/s across the stenosis was also noticed.

    CONCLUSION: The computational multiphase blood flow analysis improves the understanding and accuracy of the complex flow conditions of blood elements (RBC and Plasma) and provides the progression of the disease development in the coronary arteries. This study helps to enhance the diagnosis of the blocked (stenosed) arteries more precisely compared to the single-phase blood flow modeling.

    Matched MeSH terms: Computer Simulation
  10. Yap HJ, Taha Z, Dawal SZ, Chang SW
    PLoS One, 2014;9(10):e109692.
    PMID: 25360663 DOI: 10.1371/journal.pone.0109692
    Traditional robotic work cell design and programming are considered inefficient and outdated in current industrial and market demands. In this research, virtual reality (VR) technology is used to improve human-robot interface, whereby complicated commands or programming knowledge is not required. The proposed solution, known as VR-based Programming of a Robotic Work Cell (VR-Rocell), consists of two sub-programmes, which are VR-Robotic Work Cell Layout (VR-RoWL) and VR-based Robot Teaching System (VR-RoT). VR-RoWL is developed to assign the layout design for an industrial robotic work cell, whereby VR-RoT is developed to overcome safety issues and lack of trained personnel in robot programming. Simple and user-friendly interfaces are designed for inexperienced users to generate robot commands without damaging the robot or interrupting the production line. The user is able to attempt numerous times to attain an optimum solution. A case study is conducted in the Robotics Laboratory to assemble an electronics casing and it is found that the output models are compatible with commercial software without loss of information. Furthermore, the generated KUKA commands are workable when loaded into a commercial simulator. The operation of the actual robotic work cell shows that the errors may be due to the dynamics of the KUKA robot rather than the accuracy of the generated programme. Therefore, it is concluded that the virtual reality based solution approach can be implemented in an industrial robotic work cell.
    Matched MeSH terms: Computer Simulation
  11. Ang CYS, Chiew YS, Wang X, Ooi EH, Nor MBM, Cove ME, et al.
    Comput Methods Programs Biomed, 2023 Oct;240:107728.
    PMID: 37531693 DOI: 10.1016/j.cmpb.2023.107728
    BACKGROUND AND OBJECTIVE: Healthcare datasets are plagued by issues of data scarcity and class imbalance. Clinically validated virtual patient (VP) models can provide accurate in-silico representations of real patients and thus a means for synthetic data generation in hospital critical care settings. This research presents a realistic, time-varying mechanically ventilated respiratory failure VP profile synthesised using a stochastic model.

    METHODS: A stochastic model was developed using respiratory elastance (Ers) data from two clinical cohorts and averaged over 30-minute time intervals. The stochastic model was used to generate future Ers data based on current Ers values with added normally distributed random noise. Self-validation of the VPs was performed via Monte Carlo simulation and retrospective Ers profile fitting. A stochastic VP cohort of temporal Ers evolution was synthesised and then compared to an independent retrospective patient cohort data in a virtual trial across several measured patient responses, where similarity of profiles validates the realism of stochastic model generated VP profiles.

    RESULTS: A total of 120,000 3-hour VPs for pressure control (PC) and volume control (VC) ventilation modes are generated using stochastic simulation. Optimisation of the stochastic simulation process yields an ideal noise percentage of 5-10% and simulation iteration of 200,000 iterations, allowing the simulation of a realistic and diverse set of Ers profiles. Results of self-validation show the retrospective Ers profiles were able to be recreated accurately with a mean squared error of only 0.099 [0.009-0.790]% for the PC cohort and 0.051 [0.030-0.126]% for the VC cohort. A virtual trial demonstrates the ability of the stochastic VP cohort to capture Ers trends within and beyond the retrospective patient cohort providing cohort-level validation.

    CONCLUSION: VPs capable of temporal evolution demonstrate feasibility for use in designing, developing, and optimising bedside MV guidance protocols through in-silico simulation and validation. Overall, the temporal VPs developed using stochastic simulation alleviate the need for lengthy, resource intensive, high cost clinical trials, while facilitating statistically robust virtual trials, ultimately leading to improved patient care and outcomes in mechanical ventilation.

    Matched MeSH terms: Computer Simulation
  12. Dawood F, Loo CK
    PLoS One, 2016;11(3):e0152003.
    PMID: 26998923 DOI: 10.1371/journal.pone.0152003
    Mirror neurons are visuo-motor neurons found in primates and thought to be significant for imitation learning. The proposition that mirror neurons result from associative learning while the neonate observes his own actions has received noteworthy empirical support. Self-exploration is regarded as a procedure by which infants become perceptually observant to their own body and engage in a perceptual communication with themselves. We assume that crude sense of self is the prerequisite for social interaction. However, the contribution of mirror neurons in encoding the perspective from which the motor acts of others are seen have not been addressed in relation to humanoid robots. In this paper we present a computational model for development of mirror neuron system for humanoid based on the hypothesis that infants acquire MNS by sensorimotor associative learning through self-exploration capable of sustaining early imitation skills. The purpose of our proposed model is to take into account the view-dependency of neurons as a probable outcome of the associative connectivity between motor and visual information. In our experiment, a humanoid robot stands in front of a mirror (represented through self-image using camera) in order to obtain the associative relationship between his own motor generated actions and his own visual body-image. In the learning process the network first forms mapping from each motor representation onto visual representation from the self-exploratory perspective. Afterwards, the representation of the motor commands is learned to be associated with all possible visual perspectives. The complete architecture was evaluated by simulation experiments performed on DARwIn-OP humanoid robot.
    Matched MeSH terms: Computer Simulation
  13. Kosugi Y, Takanashi S, Yokoyama N, Philip E, Kamakura M
    J Plant Res, 2012 Nov;125(6):735-48.
    PMID: 22644315 DOI: 10.1007/s10265-012-0495-5
    Vertical variation in leaf gas exchange characteristics of trees grown in a lowland dipterocarp forest in Peninsular Malaysia was investigated. Maximum net photosynthetic rate, stomatal conductance, and electron transport rate of leaves at the upper canopy, lower canopy, and forest floor were studied in situ with saturated condition photosynthetic photon flux density. The dark respiration rate of leaves at the various heights was also studied. Relationships among gas exchange characteristics, and also with nitrogen content per unit leaf area and leaf dry matter per area were clearly detected, forming general equations representing the vertical profile of several important parameters related to gas exchange. Numerical analysis revealed that the vertical distribution of gas exchange parameters was well determined showing both larger carbon gain for the whole canopy and at the same time positive carbon gain for the leaves of the lowest layer. For correct estimation of gas exchange at both leaf and canopy scales using multi-layer models, it is essential to consider the vertical distribution of gas exchange parameters with proper scaling coefficients.
    Matched MeSH terms: Computer Simulation
  14. Baha Raja D, Abdul Taib NA, Teo AKJ, Jayaraj VJ, Ting CY
    Int Health, 2023 Jan 03;15(1):37-46.
    PMID: 35265998 DOI: 10.1093/inthealth/ihac005
    BACKGROUND: The computer simulation presented in this study aimed to investigate the effect of contact tracing on coronavirus disease 2019 (COVID-19) transmission and infection in the context of rising vaccination rates.

    METHODS: This study proposed a deterministic, compartmental model with contact tracing and vaccination components. We defined contact tracing effectiveness as the proportion of contacts of a positive case that was successfully traced and the vaccination rate as the proportion of daily doses administered per population in Malaysia. Sensitivity analyses on the untraced and infectious populations were conducted.

    RESULTS: At a vaccination rate of 1.4%, contact tracing with an effectiveness of 70% could delay the peak of untraced asymptomatic cases by 17 d and reduce it by 70% compared with 30% contact tracing effectiveness. A similar trend was observed for symptomatic cases when a similar experiment setting was used. We also performed sensitivity analyses by using different combinations of contact tracing effectiveness and vaccination rates. In all scenarios, the effect of contact tracing on COVID-19 incidence persisted for both asymptomatic and symptomatic cases.

    CONCLUSIONS: While vaccines are progressively rolled out, efficient contact tracing must be rapidly implemented concurrently to reach, find, test, isolate and support the affected populations to bring COVID-19 under control.

    Matched MeSH terms: Computer Simulation
  15. Yu X, Lu L, Guo J, Qin H, Ji C
    Comput Math Methods Med, 2022;2022:4168619.
    PMID: 35087601 DOI: 10.1155/2022/4168619
    Since December 2019, a novel coronavirus (COVID-19) has spread all over the world, causing unpredictable economic losses and public fear. Although vaccines against this virus have been developed and administered for months, many countries still suffer from secondary COVID-19 infections, including the United Kingdom, France, and Malaysia. Observations of COVID-19 infections in the United Kingdom and France and their governance measures showed a certain number of similarities. A further investigation of these countries' COVID-19 transmission patterns suggested that when a turning point appeared, the values of their stringency indices per population density (PSI) were nearly proportional to their absolute infection rate (AIR). To justify our assumptions, we developed a mathematical model named VSHR to predict the COVID-19 turning point for Malaysia. VSHR was first trained on 30-day infection records prior to the United Kingdom, Germany, France, and Belgium's known turning points. It was then transferred to Malaysian COVID-19 data to predict this nation's turning point. Given the estimated AIR parameter values in 5 days, we were now able to locate the turning point's appearance on June 2nd, 2021. VSHR offered two improvements: (1) gathered countries into groups based on their SI patterns and (2) generated a model to identify the turning point for a target country within 5 days with 90% CI. Our research on COVID-19's turning point for a country is beneficial for governments and clinical systems against future COVID-19 infections.
    Matched MeSH terms: Computer Simulation
  16. Abdul Hadi MFR, Abdullah AN, Hashikin NAA, Ying CK, Yeong CH, Yoon TL, et al.
    Med Phys, 2022 Dec;49(12):7742-7753.
    PMID: 36098271 DOI: 10.1002/mp.15980
    PURPOSE: Monte Carlo (MC) simulation is an important technique that can help design advanced and challenging experimental setups. GATE (Geant4 application for tomographic emission) is a useful simulation toolkit for applications in nuclear medicine. Transarterial radioembolization is a treatment for liver cancer, where microspheres embedded with yttrium-90 (90 Y) are administered intra-arterially to the tumor. Personalized dosimetry for this treatment may provide higher dosimetry accuracy compared to the conventional partition model (PM) calculation. However, incorporation of three-dimensional tomographic input data into MC simulation is an intricate process. In this article, 3D Slicer, free and open-source software, was utilized for the incorporation of patient tomographic images into GATE to demonstrate the feasibility of personalized dosimetry in hepatic radioembolization with 90 Y.

    METHODS: In this article, the steps involved in importing, segmenting, and registering tomographic images using 3D Slicer were thoroughly described, before importing them into GATE for MC simulation. The absorbed doses estimated using GATE were then compared with that of PM. SlicerRT, a 3D Slicer extension, was then used to visualize the isodose from the MC simulation.

    RESULTS: A workflow diagram consisting of all the steps taken in the utilization of 3D Slicer for personalized dosimetry in 90 Y radioembolization has been presented in this article. In comparison to the MC simulation, the absorbed doses to the tumor and normal liver were overestimated by PM by 105.55% and 20.23%, respectively, whereas for lungs, the absorbed dose estimated by PM was underestimated by 25.32%. These values were supported by the isodose distribution obtained via SlicerRT, suggesting the presence of beta particles outside the volumes of interest. These findings demonstrate the importance of personalized dosimetry for a more accurate absorbed dose estimation compared to PM.

    CONCLUSION: The methodology provided in this study can assist users (especially students or researchers who are new to MC simulation) in navigating intricate steps required in the importation of tomographic data for MC simulation. These steps can also be utilized for other radiation therapy related applications, not necessarily limited to internal dosimetry.

    Matched MeSH terms: Computer Simulation
  17. Moosavi SMH, Ismail A, Yuen CW
    PLoS One, 2020;15(5):e0232799.
    PMID: 32379848 DOI: 10.1371/journal.pone.0232799
    Bus services naturally tend to be unstable and are not always capable of adhering to schedules without control strategies. Therefore, bus users and bus service providers face travel time variation and irregularity. After a comprehensive review of the literature, a significant gap was recognized in the field of public transportation reliability. According to literature, there is no consistency in reliability definition and indicators. Companies have their own definition of bus service reliability, and they mostly neglect the passengers' perspective of reliability. Therefore, four reliability indicators were selected in this study to fill the gap in the literature and cover both passengers' and operators' perceptions of reliability: waiting time and on-board crowding level from passengers' perspective, and headway regularity index at stops (HRIS) and bus bunching/big gap percentage from operators' perspective. The primary objective of this research is to improve the reliability of high frequency of bus service and simulation tools currently being used by the public transportation companies. Therefore, a simulation model of bus service was developed to study the strategies to alleviate it. Four different types of strategies were selected and implemented according to Route U32 (Kuala Lumpur) specifications. Model out-put showed that control strategies such as headway-based dispatching could significantly improve headway regularity by almost 62% and the waiting time by 51% on average. Both holding strategies at key stops (previous and Prefol holding) have shown an almost similar impact on reliability indicators. Waiting time was reduced by 44% and 43% after the previous and Prefol Headway strategies were adopted, respectively. However, the implementation of the component of headway-based strategies at the terminal and key stops showed the best impact on reliability, in terms of passenger waiting time. Waiting time and excess waiting time were both significantly reduced by 52.86% and 81.44%, respectively. Nevertheless, the strategies did not show any significant positive effect on the level of crowding during morning peak hours.
    Matched MeSH terms: Computer Simulation
  18. Gavai AK, Supandi F, Hettling H, Murrell P, Leunissen JA, van Beek JH
    PLoS One, 2015;10(3):e0119016.
    PMID: 25806817 DOI: 10.1371/journal.pone.0119016
    Predicting the distribution of metabolic fluxes in biochemical networks is of major interest in systems biology. Several databases provide metabolic reconstructions for different organisms. Software to analyze flux distributions exists, among others for the proprietary MATLAB environment. Given the large user community for the R computing environment, a simple implementation of flux analysis in R appears desirable and will facilitate easy interaction with computational tools to handle gene expression data. We extended the R software package BiGGR, an implementation of metabolic flux analysis in R. BiGGR makes use of public metabolic reconstruction databases, and contains the BiGG database and the reconstruction of human metabolism Recon2 as Systems Biology Markup Language (SBML) objects. Models can be assembled by querying the databases for pathways, genes or reactions of interest. Fluxes can then be estimated by maximization or minimization of an objective function using linear inverse modeling algorithms. Furthermore, BiGGR provides functionality to quantify the uncertainty in flux estimates by sampling the constrained multidimensional flux space. As a result, ensembles of possible flux configurations are constructed that agree with measured data within precision limits. BiGGR also features automatic visualization of selected parts of metabolic networks using hypergraphs, with hyperedge widths proportional to estimated flux values. BiGGR supports import and export of models encoded in SBML and is therefore interoperable with different modeling and analysis tools. As an application example, we calculated the flux distribution in healthy human brain using a model of central carbon metabolism. We introduce a new algorithm termed Least-squares with equalities and inequalities Flux Balance Analysis (Lsei-FBA) to predict flux changes from gene expression changes, for instance during disease. Our estimates of brain metabolic flux pattern with Lsei-FBA for Alzheimer's disease agree with independent measurements of cerebral metabolism in patients. This second version of BiGGR is available from Bioconductor.
    Matched MeSH terms: Computer Simulation*
  19. Saratha Sathasivam
    The convergence property for doing logic programming in Hopfield network can be accelerated by using new relaxation method. This paper shows that the performance of the Hopfield network can be improved by using a relaxation rate to control the energy relaxation process. The capacity and performance of these networks is tested by using computer simulations. It was proven by computer simulations that the new approach provides good solutions.
    Matched MeSH terms: Computer Simulation
  20. Zilany MS, Bruce IC, Carney LH
    J Acoust Soc Am, 2014 Jan;135(1):283-6.
    PMID: 24437768 DOI: 10.1121/1.4837815
    A phenomenological model of the auditory periphery in cats was previously developed by Zilany and colleagues [J. Acoust. Soc. Am. 126, 2390-2412 (2009)] to examine the detailed transformation of acoustic signals into the auditory-nerve representation. In this paper, a few issues arising from the responses of the previous version have been addressed. The parameters of the synapse model have been readjusted to better simulate reported physiological discharge rates at saturation for higher characteristic frequencies [Liberman, J. Acoust. Soc. Am. 63, 442-455 (1978)]. This modification also corrects the responses of higher-characteristic frequency (CF) model fibers to low-frequency tones that were erroneously much higher than the responses of low-CF model fibers in the previous version. In addition, an analytical method has been implemented to compute the mean discharge rate and variance from the model's synapse output that takes into account the effects of absolute refractoriness.
    Matched MeSH terms: Computer Simulation*
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