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  1. Fulltext A Biogeography-Based Optimization Algorithm Hybridized with Tabu Search for the Quadratic Assignment Problem
    Lim WL, Wibowo A, Desa MI, Haron H
    Comput Intell Neurosci, 2016;2016:5803893.
    PMID: 26819585 DOI: 10.1155/2016/5803893
    The quadratic assignment problem (QAP) is an NP-hard combinatorial optimization problem with a wide variety of applications. Biogeography-based optimization (BBO), a relatively new optimization technique based on the biogeography concept, uses the idea of migration strategy of species to derive algorithm for solving optimization problems. It has been shown that BBO provides performance on a par with other optimization methods. A classical BBO algorithm employs the mutation operator as its diversification strategy. However, this process will often ruin the quality of solutions in QAP. In this paper, we propose a hybrid technique to overcome the weakness of classical BBO algorithm to solve QAP, by replacing the mutation operator with a tabu search procedure. Our experiments using the benchmark instances from QAPLIB show that the proposed hybrid method is able to find good solutions for them within reasonable computational times. Out of 61 benchmark instances tested, the proposed method is able to obtain the best known solutions for 57 of them.
    Matched MeSH terms: Models, Biological*
  2. Fulltext A Human Corneal Epithelial Cell Line Model for Limbal Stem Cell Biology and Limbal Immunobiology
    Shaharuddin B, Ahmad S, Md Latar N, Ali S, Meeson A
    Stem Cells Transl Med, 2017 03;6(3):761-766.
    PMID: 28297580 DOI: 10.5966/sctm.2016-0175
    Limbal stem cell (LSC) deficiency is a visually debilitating condition caused by abnormal maintenance of LSCs. It is treated by transplantation of donor-derived limbal epithelial cells (LECs), the success of which depends on the presence and quality of LSCs within the transplant. Understanding the immunobiological responses of these cells within the transplants could improve cell engraftment and survival. However, human corneal rings used as a source of LSCs are not always readily available for research purposes. As an alternative, we hypothesized that a human telomerase-immortalized corneal epithelial cell (HTCEC) line could be used as a model for studying LSC immunobiology. HTCEC constitutively expressed human leukocyte antigen (HLA) class I but not class II molecules. However, when stimulated by interferon-γ, HTCECs then expressed HLA class II antigens. Some HTCECs were also migratory in response to CXCL12 and expressed stem cell markers, Nanog, Oct4, and Sox2. In addition because both HTCECs and LECs contain side population (SP) cells, which are an enriched LSC population, we used these SP cells to show that some HTCEC SP cells coexpressed ABCG2 and ABCB5. HTCEC SP and non-side population (NSP) cells also expressed CXCR4, but the SP cells expressed higher levels. Both were capable of colony formation, but the NSP colonies were smaller and contained fewer cells. In addition, HTCECs expressed ΔNp63α. These results suggest the HTCEC line is a useful model for further understanding LSC biology by using an in vitro approach without reliance on a supply of human tissue. Stem Cells Translational Medicine 2017;6:761-766.
    Matched MeSH terms: Models, Biological*
  3. A New Framework for Analysis of Coevolutionary Systems-Directed Graph Representation and Random Walks
    Chong SY, Tiňo P, He J, Yao X
    Evol Comput, 2019;27(2):195-228.
    PMID: 29155606 DOI: 10.1162/evco_a_00218
    Studying coevolutionary systems in the context of simplified models (i.e., games with pairwise interactions between coevolving solutions modeled as self plays) remains an open challenge since the rich underlying structures associated with pairwise-comparison-based fitness measures are often not taken fully into account. Although cyclic dynamics have been demonstrated in several contexts (such as intransitivity in coevolutionary problems), there is no complete characterization of cycle structures and their effects on coevolutionary search. We develop a new framework to address this issue. At the core of our approach is the directed graph (digraph) representation of coevolutionary problems that fully captures structures in the relations between candidate solutions. Coevolutionary processes are modeled as a specific type of Markov chains-random walks on digraphs. Using this framework, we show that coevolutionary problems admit a qualitative characterization: a coevolutionary problem is either solvable (there is a subset of solutions that dominates the remaining candidate solutions) or not. This has an implication on coevolutionary search. We further develop our framework that provides the means to construct quantitative tools for analysis of coevolutionary processes and demonstrate their applications through case studies. We show that coevolution of solvable problems corresponds to an absorbing Markov chain for which we can compute the expected hitting time of the absorbing class. Otherwise, coevolution will cycle indefinitely and the quantity of interest will be the limiting invariant distribution of the Markov chain. We also provide an index for characterizing complexity in coevolutionary problems and show how they can be generated in a controlled manner.
    Matched MeSH terms: Models, Biological*
  4. A Weibull statistics-based lignocellulose saccharification model and a built-in parameter accurately predict lignocellulose hydrolysis performance
    Wang M, Han L, Liu S, Zhao X, Yang J, Loh SK, et al.
    Biotechnol J, 2015 Sep;10(9):1424-33.
    PMID: 26121186 DOI: 10.1002/biot.201400723
    Renewable energy from lignocellulosic biomass has been deemed an alternative to depleting fossil fuels. In order to improve this technology, we aim to develop robust mathematical models for the enzymatic lignocellulose degradation process. By analyzing 96 groups of previously published and newly obtained lignocellulose saccharification results and fitting them to Weibull distribution, we discovered Weibull statistics can accurately predict lignocellulose saccharification data, regardless of the type of substrates, enzymes and saccharification conditions. A mathematical model for enzymatic lignocellulose degradation was subsequently constructed based on Weibull statistics. Further analysis of the mathematical structure of the model and experimental saccharification data showed the significance of the two parameters in this model. In particular, the λ value, defined the characteristic time, represents the overall performance of the saccharification system. This suggestion was further supported by statistical analysis of experimental saccharification data and analysis of the glucose production levels when λ and n values change. In conclusion, the constructed Weibull statistics-based model can accurately predict lignocellulose hydrolysis behavior and we can use the λ parameter to assess the overall performance of enzymatic lignocellulose degradation. Advantages and potential applications of the model and the λ value in saccharification performance assessment were discussed.
    Matched MeSH terms: Models, Biological*
  5. A climate distribution model of malaria transmission in Sudan
    Musa MI, Shohaimi S, Hashim NR, Krishnarajah I
    Geospat Health, 2012 Nov;7(1):27-36.
    PMID: 23242678
    Malaria remains a major health problem in Sudan. With a population exceeding 39 million, there are around 7.5 million cases and 35,000 deaths every year. The predicted distribution of malaria derived from climate factors such as maximum and minimum temperatures, rainfall and relative humidity was compared with the actual number of malaria cases in Sudan for the period 2004 to 2010. The predictive calculations were done by fuzzy logic suitability (FLS) applied to the numerical distribution of malaria transmission based on the life cycle characteristics of the Anopheles mosquito accounting for the impact of climate factors on malaria transmission. This information is visualized as a series of maps (presented in video format) using a geographical information systems (GIS) approach. The climate factors were found to be suitable for malaria transmission in the period of May to October, whereas the actual case rates of malaria were high from June to November indicating a positive correlation. While comparisons between the prediction model for June and the case rate model for July did not show a high degree of association (18%), the results later in the year were better, reaching the highest level (55%) for October prediction and November case rate.
    Matched MeSH terms: Models, Biological
  6. A comparative study on complete and implant retained denture treatments: a biomechanics perspective
    Chen J, Ahmad R, Suenaga H, Li W, Swain M, Li Q
    J Biomech, 2015 Feb 5;48(3):512-9.
    PMID: 25560272 DOI: 10.1016/j.jbiomech.2014.11.043
    Although implant-retained overdenture allows edentulous patients to take higher occlusal forces than the conventional complete dentures, the biomechanical influences have not been explored yet. Clinically, there is limited knowledge and means for predicting localized bone remodelling after denture treatment with and without implant support. By using finite element (FE) analysis, this article provides an in-silico approach to exploring the treatment effects on the oral mucosa and potential resorption of residual ridge under three different denture configurations in a patient-specific manner. Based on cone beam computerized tomography (CBCT) scans, a 3D heterogeneous FE model was created; and the supportive tissue, mucosa, was characterized as a hyperelastic material. A measured occlusal load (63N) was applied onto three virtual models, namely complete denture, two and four implant-retained overdentures. Clinically, the bone resorption was measured after one year in the two implant-retained overdenture treatment. Despite the improved stability and enhanced masticatory function, the implant-retained overdentures demonstrated higher hydrostatic stress in mucosa (43.6kPa and 39.9kPa for two and four implants) at the posterior ends of the mandible due to the cantilever effect, than the complete denture (33.4kPa). Hydrostatic pressure in the mucosa signifies a critical indicator and can be correlated with clinically measured bone resorption, pointing to severer mandibular ridge resorption posteriorly with implant-retained overdentures. This study provides a biomechanical basis for denture treatment planning to improve long-term outcomes with minimal residual ridge resorption.
    Matched MeSH terms: Models, Biological
  7. Fulltext A data driven change-point epidemic model for assessing the impact of large gathering and subsequent movement control order on COVID-19 spread in Malaysia
    Dass SC, Kwok WM, Gibson GJ, Gill BS, Sundram BM, Singh S
    PLoS One, 2021;16(5):e0252136.
    PMID: 34043676 DOI: 10.1371/journal.pone.0252136
    The second wave of COVID-19 in Malaysia is largely attributed to a four-day mass gathering held in Sri Petaling from February 27, 2020, which contributed to an exponential rise of COVID-19 cases in the country. Starting from March 18, 2020, the Malaysian government introduced four consecutive phases of a Movement Control Order (MCO) to stem the spread of COVID-19. The MCO was implemented through various non-pharmaceutical interventions (NPIs). The reported number of cases reached its peak by the first week of April and then started to reduce, hence proving the effectiveness of the MCO. To gain a quantitative understanding of the effect of MCO on the dynamics of COVID-19, this paper develops a class of mathematical models to capture the disease spread before and after MCO implementation in Malaysia. A heterogeneous variant of the Susceptible-Exposed-Infected-Recovered (SEIR) model is developed with additional compartments for asymptomatic transmission. Further, a change-point is incorporated to model disease dynamics before and after intervention which is inferred based on data. Related statistical analyses for inference are developed in a Bayesian framework and are able to provide quantitative assessments of (1) the impact of the Sri Petaling gathering, and (2) the extent of decreasing transmission during the MCO period. The analysis here also quantitatively demonstrates how quickly transmission rates fall under effective NPI implementation within a short time period. The models and methodology used provided important insights into the nature of local transmissions to decision makers in the Ministry of Health, Malaysia.
    Matched MeSH terms: Models, Biological*
  8. A fibril-based structural constitutive theory reveals the dominant role of network characteristics on the mechanical behavior of fibroblast-compacted collagen gels
    Feng Z, Ishiguro Y, Fujita K, Kosawada T, Nakamura T, Sato D, et al.
    Biomaterials, 2015 Oct;67:365-81.
    PMID: 26247391 DOI: 10.1016/j.biomaterials.2015.07.038
    In this paper, we present a general, fibril-based structural constitutive theory which accounts for three material aspects of crosslinked filamentous materials: the single fibrillar force response, the fibrillar network model, and the effects of alterations to the fibrillar network. In the case of the single fibrillar response, we develop a formula that covers the entropic and enthalpic deformation regions, and introduce the relaxation phase to explain the observed force decay after crosslink breakage. For the filamentous network model, we characterize the constituent element of the fibrillar network in terms its end-to-end distance vector and its contour length, then decompose the vector orientation into an isotropic random term and a specific alignment, paving the way for an expanded formalism from principal deformation to general 3D deformation; and, more important, we define a critical core quantity over which macroscale mechanical characteristics can be integrated: the ratio of the initial end-to-end distance to the contour length (and its probability function). For network alterations, we quantitatively treat changes in constituent elements and relate these changes to the alteration of network characteristics. Singular in its physical rigor and clarity, this constitutive theory can reproduce and predict a wide range of nonlinear mechanical behavior in materials composed of a crosslinked filamentous network, including: stress relaxation (with dual relaxation coefficients as typically observed in soft tissues); hysteresis with decreasing maximum stress under serial cyclic loading; strain-stiffening under uniaxial tension; the rupture point of the structure as a whole; various effects of biaxial tensile loading; strain-stiffening under simple shearing; the so-called "negative normal stress" phenomenon; and enthalpic elastic behaviors of the constituent element. Applied to compacted collagen gels, the theory demonstrates that collagen fibrils behave as enthalpic elasticas with linear elasticity within the gels, and that the macroscale nonlinearity of the gels originates from the curved fibrillar network. Meanwhile, the underlying factors that determine the mechanical properties of the gels are clarified. Finally, the implications of this study on the enhancement of the mechanical properties of compacted collagen gels and on the cellular mechanics with this model tissue are discussed.
    Matched MeSH terms: Models, Biological*
  9. A fluid mechanical explanation of the spontaneous reattachment of a previously detached Descemet membrane
    Ismail Z, Fitt AD, Please CP
    Math Med Biol, 2013 Dec;30(4):339-55.
    PMID: 23054933 DOI: 10.1093/imammb/dqs028
    Descemet membrane detachment (DMD) is a rare but potentially serious surgical complication that arises most often during cataract surgery. A recent study (Couch, S. M. & Baratz, K. H. (2009) Cornea, 28, 1160-1163) cited the case of a patient with DMDs in both eyes, noting that though one detachment was surgically repaired, the other spontaneously reattached and needed no further treatment. A fluid mechanical model of buoyancy-driven aqueous humour flow in the anterior chamber around a DMD is developed to explain this phenomenon. The analytical model is based on the lubrication theory limit of the Navier-Stokes equations. The flow is determined for a fixed geometry and the possible motion of the DMD is then analysed. Numerical calculations are also carried out (using COMSOL© Multiphysics) to confirm the lubrication theory results. The analytical and numerical results both show that, under the correct conditions, either spontaneous reattachment or worsening of the tear may occur. We conclude that it is possible that clinical outcomes for DMDs may be controlled by adjusting the temperature difference across the eye and/or the orientation of the patient.
    Matched MeSH terms: Models, Biological*
  10. Fulltext A guide in lentiviral vector production for hard-to-transfect cells, using cardiac-derived c-kit expressing cells as a model system
    Kalidasan V, Ng WH, Ishola OA, Ravichantar N, Tan JJ, Das KT
    Sci Rep, 2021 Sep 28;11(1):19265.
    PMID: 34584147 DOI: 10.1038/s41598-021-98657-7
    Gene therapy revolves around modifying genetic makeup by inserting foreign nucleic acids into targeted cells via gene delivery methods to treat a particular disease. While the genes targeted play a key role in gene therapy, the gene delivery system used is also of utmost importance as it determines the success of gene therapy. As primary cells and stem cells are often the target cells for gene therapy in clinical trials, the delivery system would need to be robust, and viral-based entries such as lentiviral vectors work best at transporting the transgene into the cells. However, even within lentiviral vectors, several parameters can affect the functionality of the delivery system. Using cardiac-derived c-kit expressing cells (CCs) as a model system, this study aims to optimize lentiviral production by investigating various experimental factors such as the generation of the lentiviral system, concentration method, and type of selection marker. Our findings showed that the 2nd generation system with pCMV-dR8.2 dvpr as the packaging plasmid produced a 7.3-fold higher yield of lentiviral production compared to psPAX2. Concentrating the virus with ultracentrifuge produced a higher viral titer at greater than 5 × 105 infectious unit values/ml (IFU/ml). And lastly, the minimum inhibitory concentration (MIC) of puromycin selection marker was 10 μg/mL and 7 μg/mL for HEK293T and CCs, demonstrating the suitability of antibiotic selection for all cell types. This encouraging data can be extrapolated and applied to other difficult-to-transfect cells, such as different types of stem cells or primary cells.
    Matched MeSH terms: Models, Biological
  11. A hybrid of ant colony optimization and minimization of metabolic adjustment to improve the production of succinic acid in Escherichia coli
    Chong SK, Mohamad MS, Mohamed Salleh AH, Choon YW, Chong CK, Deris S
    Comput Biol Med, 2014 Jun;49:74-82.
    PMID: 24763079 DOI: 10.1016/j.compbiomed.2014.03.011
    This paper presents a study on gene knockout strategies to identify candidate genes to be knocked out for improving the production of succinic acid in Escherichia coli. Succinic acid is widely used as a precursor for many chemicals, for example production of antibiotics, therapeutic proteins and food. However, the chemical syntheses of succinic acid using the traditional methods usually result in the production that is far below their theoretical maximums. In silico gene knockout strategies are commonly implemented to delete the gene in E. coli to overcome this problem. In this paper, a hybrid of Ant Colony Optimization (ACO) and Minimization of Metabolic Adjustment (MoMA) is proposed to identify gene knockout strategies to improve the production of succinic acid in E. coli. As a result, the hybrid algorithm generated a list of knockout genes, succinic acid production rate and growth rate for E. coli after gene knockout. The results of the hybrid algorithm were compared with the previous methods, OptKnock and MOMAKnock. It was found that the hybrid algorithm performed better than OptKnock and MOMAKnock in terms of the production rate. The information from the results produced from the hybrid algorithm can be used in wet laboratory experiments to increase the production of succinic acid in E. coli.
    Matched MeSH terms: Models, Biological*
  12. A hyperelastic fibre-reinforced continuum model of healing tendons with distributed collagen fibre orientations
    Bajuri MN, Isaksson H, Eliasson P, Thompson MS
    Biomech Model Mechanobiol, 2016 12;15(6):1457-1466.
    PMID: 26951049
    The healing process of ruptured tendons is problematic due to scar tissue formation and deteriorated material properties, and in some cases, it may take nearly a year to complete. Mechanical loading has been shown to positively influence tendon healing; however, the mechanisms remain unclear. Computational mechanobiology methods employed extensively to model bone healing have achieved high fidelity. This study aimed to investigate whether an established hyperelastic fibre-reinforced continuum model introduced by Gasser, Ogden and Holzapfel (GOH) can be used to capture the mechanical behaviour of the Achilles tendon under loading during discrete timepoints of the healing process and to assess the model's sensitivity to its microstructural parameters. Curve fitting of the GOH model against experimental tensile testing data of rat Achilles tendons at four timepoints during the tendon repair was used and achieved excellent fits ([Formula: see text]). A parametric sensitivity study using a three-level central composite design, which is a fractional factorial design method, showed that the collagen-fibre-related parameters in the GOH model-[Formula: see text] and [Formula: see text]-had almost equal influence on the fitting. This study demonstrates that the GOH hyperelastic fibre-reinforced model is capable of describing the mechanical behaviour of healing tendons and that further experiments should focus on establishing the structural and material parameters of collagen fibres in the healing tissue.
    Matched MeSH terms: Models, Biological*
  13. A kinetic study of autohydrogenotrophic denitrification at the optimum pH and sodium bicarbonate dose
    Ghafari S, Hasan M, Aroua MK
    Bioresour Technol, 2010 Apr;101(7):2236-42.
    PMID: 20015639 DOI: 10.1016/j.biortech.2009.11.068
    In this study the kinetics of autohydrogenotrophic denitrification was studied under optimum solution pH and bicarbonate concentration. The optimal pH and bicarbonate concentration were firstly obtained using a design of experiment (DOE) methodology. For this purpose a total of 11 experiments were carried out. Sodium bicarbonate concentrations ranging of 20-2000 mg/L and pH values from 6.5 to 8.5 were used in the optimization runs. It was found that the pH has a more pronounced effect on the denitrification process as compared to the bicarbonate dose. The developed quadratic model predicted the optimum conditions at pH 8 and 1100 mg NaHCO(3)/L. Using these optimal conditions, the kinetics of denitrification for nitrate and nitrite degradation were investigated in separate experiments. Both processes were found to follow a zero order kinetic model. The ultimate specific degradation rates for nitrate and nitrite remediation were 29.60 mg NO(3)(-)-N/g MLVSS/L and 34.85 mg NO(3)(-)-N/g MLVSS/L respectively, when hydrogen was supplied every 0.5h.
    Matched MeSH terms: Models, Biological
  14. Fulltext A modeling study by response surface methodology and artificial neural network on culture parameters optimization for thermostable lipase production from a newly isolated thermophilic Geobacillus sp. strain ARM
    Ebrahimpour A, Abd Rahman RN, Ean Ch'ng DH, Basri M, Salleh AB
    BMC Biotechnol, 2008 Dec 23;8:96.
    PMID: 19105837 DOI: 10.1186/1472-6750-8-96
    BACKGROUND: Thermostable bacterial lipases occupy a place of prominence among biocatalysts owing to their novel, multifold applications and resistance to high temperature and other operational conditions. The capability of lipases to catalyze a variety of novel reactions in both aqueous and nonaqueous media presents a fascinating field for research, creating interest to isolate novel lipase producers and optimize lipase production. The most important stages in a biological process are modeling and optimization to improve a system and increase the efficiency of the process without increasing the cost.

    RESULTS: Different production media were tested for lipase production by a newly isolated thermophilic Geobacillus sp. strain ARM (DSM 21496 = NCIMB 41583). The maximum production was obtained in the presence of peptone and yeast extract as organic nitrogen sources, olive oil as carbon source and lipase production inducer, sodium and calcium as metal ions, and gum arabic as emulsifier and lipase production inducer. The best models for optimization of culture parameters were achieved by multilayer full feedforward incremental back propagation network and modified response surface model using backward elimination, where the optimum condition was: growth temperature (52.3 degrees C), medium volume (50 ml), inoculum size (1%), agitation rate (static condition), incubation period (24 h) and initial pH (5.8). The experimental lipase activity was 0.47 Uml(-1) at optimum condition (4.7-fold increase), which compared well to the maximum predicted values by ANN (0.47 Uml(-1)) and RSM (0.476 Uml(-1)), whereas R2 and AAD were determined as 0.989 and 0.059% for ANN, and 0.95 and 0.078% for RSM respectively.

    CONCLUSION: Lipase production is the result of a synergistic combination of effective parameters interactions. These parameters are in equilibrium and the change of one parameter can be compensated by changes of other parameters to give the same results. Though both RSM and ANN models provided good quality predictions in this study, yet the ANN showed a clear superiority over RSM for both data fitting and estimation capabilities. On the other hand, ANN has the disadvantage of requiring large amounts of training data in comparison with RSM. This problem was solved by using statistical experimental design, to reduce the number of experiments.

    Matched MeSH terms: Models, Biological
  15. Fulltext A modified active appearance model based on an adaptive artificial bee colony
    Abdulameer MH, Sheikh Abdullah SN, Othman ZA
    ScientificWorldJournal, 2014;2014:879031.
    PMID: 25165748 DOI: 10.1155/2014/879031
    Active appearance model (AAM) is one of the most popular model-based approaches that have been extensively used to extract features by highly accurate modeling of human faces under various physical and environmental circumstances. However, in such active appearance model, fitting the model with original image is a challenging task. State of the art shows that optimization method is applicable to resolve this problem. However, another common problem is applying optimization. Hence, in this paper we propose an AAM based face recognition technique, which is capable of resolving the fitting problem of AAM by introducing a new adaptive ABC algorithm. The adaptation increases the efficiency of fitting as against the conventional ABC algorithm. We have used three datasets: CASIA dataset, property 2.5D face dataset, and UBIRIS v1 images dataset in our experiments. The results have revealed that the proposed face recognition technique has performed effectively, in terms of accuracy of face recognition.
    Matched MeSH terms: Models, Biological*
  16. Fulltext A new concept of the formation of hypoxic cells in tumors and its possible implications for radiotherapy and chemotherapy
    Ng CE
    Med J Malaysia, 1981 Mar;36(1):24-8.
    PMID: 7321933
    Hypoxic cells in tumors are proposed to consist of at least 2 types, depending on whether they remain hypoxic for long (chronic hypoxia) or short (acute hypoxia) periods. Experimental evidence of the possible presence ofacutely-hypoxic cells in one type of murine tumour is presented. Finally, the possible implications for radiotherapy and chemotherapy of the presence of acutely-hypoxic cells in human tumors is discussed briefly.
    Matched MeSH terms: Models, Biological
  17. A new twist on a very old binary similarity coefficient
    Alroy J
    Ecology, 2015 Feb;96(2):575-86.
    PMID: 26240877
    Pairwise similarity coefficients are downward biased when samples only record presences and sampling is partial. A simple but forgotten index proposed by Stephen Forbes in 1907 can help solve this problem. His original equation requires knowing the number of species absent in both samples that could have been present. It is proposed that this count should simply be ignored and that the coefficient should be adjusted using a simple heuristic correction. Four analyses show that the corrected equation outperforms the Dice and Simpson indices, which are highly correlated with many others. In two-sample simulations, similarity is almost always closer to the assumed value when the species pool size and sampling intensity are varied, regardless of whether the underlying abundance distribution is uniform, log-normal, or geometric. The index is also much more robust when sampling is unequal. An analysis of bat samples from peninsular Malaysia buttresses these conclusions. The corrected coefficient also indicates that local assemblages of North American mammals are random subsamples of larger species pools by returning similarity of values of around 1, and it suggests a more consistent relationship between biome-scale comparisons and local-scale comparisons. Finally, it yields a better-dispersed pattern when the biome-scale inventories are ordinated. If these results are generalizable, then the new and old equation should see wide application, potentially taking the place of the two most commonly used alternatives (the interrelated Dice and Jaccard indices) whenever sampling is incomplete.
    Matched MeSH terms: Models, Biological
  18. Fulltext A newton cooperative genetic algorithm method for in silico optimization of metabolic pathway production
    Ismail MA, Deris S, Mohamad MS, Abdullah A
    PLoS One, 2015;10(5):e0126199.
    PMID: 25961295 DOI: 10.1371/journal.pone.0126199
    This paper presents an in silico optimization method of metabolic pathway production. The metabolic pathway can be represented by a mathematical model known as the generalized mass action model, which leads to a complex nonlinear equations system. The optimization process becomes difficult when steady state and the constraints of the components in the metabolic pathway are involved. To deal with this situation, this paper presents an in silico optimization method, namely the Newton Cooperative Genetic Algorithm (NCGA). The NCGA used Newton method in dealing with the metabolic pathway, and then integrated genetic algorithm and cooperative co-evolutionary algorithm. The proposed method was experimentally applied on the benchmark metabolic pathways, and the results showed that the NCGA achieved better results compared to the existing methods.
    Matched MeSH terms: Models, Biological*
  19. A non-dominated sorting Differential Search Algorithm Flux Balance Analysis (ndsDSAFBA) for in silico multiobjective optimization in identifying reactions knockout
    Daud KM, Mohamad MS, Zakaria Z, Hassan R, Shah ZA, Deris S, et al.
    Comput Biol Med, 2019 10;113:103390.
    PMID: 31450056 DOI: 10.1016/j.compbiomed.2019.103390
    Metabolic engineering is defined as improving the cellular activities of an organism by manipulating the metabolic, signal or regulatory network. In silico reaction knockout simulation is one of the techniques applied to analyse the effects of genetic perturbations on metabolite production. Many methods consider growth coupling as the objective function, whereby it searches for mutants that maximise the growth and production rate. However, the final goal is to increase the production rate. Furthermore, they produce one single solution, though in reality, cells do not focus on one objective and they need to consider various different competing objectives. In this work, a method, termed ndsDSAFBA (non-dominated sorting Differential Search Algorithm and Flux Balance Analysis), has been developed to find the reaction knockouts involved in maximising the production rate and growth rate of the mutant, by incorporating Pareto dominance concepts. The proposed ndsDSAFBA method was validated using three genome-scale metabolic models. We obtained a set of non-dominated solutions, with each solution representing a different mutant strain. The results obtained were compared with the single objective optimisation (SOO) and multi-objective optimisation (MOO) methods. The results demonstrate that ndsDSAFBA is better than the other methods in terms of production rate and growth rate.
    Matched MeSH terms: Models, Biological*
  20. A novel mechanism measurement of predator interference in predator-prey models
    Alebraheem J, Abu-Hassan Y
    J Math Biol, 2023 Apr 27;86(5):84.
    PMID: 37103566 DOI: 10.1007/s00285-023-01914-8
    A characteristic of ecosystems is the existence of manifold of independencies which are highly complex. Various mathematical models have made considerable contributions in gaining a better understanding of the predator-prey interactions. The main components of any predator-prey models are, firstly, how the different population classes grow and secondly, how the prey and predator interacts. In this paper, the two populations' growth rates obey the logistic law and the carrying capacity of the predator depends on the available number of prey are considered. Our aim is to clarify the relationship between models and Holling types functional and numerical responses in order to gain insights into predator interferences and to answer an important question how competition is carried out. We consider a predator-prey model and a two-predator one-prey model to explain the idea. The novel approach is explained for the mechanism measurement of predator interference through depending on numerical response. Our approach gives good correspondence between an important real data and computer simulations.
    Matched MeSH terms: Models, Biological*
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