SimuMap: a computational system for spatial modelling

The paper presents a computational system based upon formal principles to run spatial models for environmental processes. The simulator is named SimuMap because it is typically used to simulate spatial processes over a mapped representation of terrain. A model is formally represented in SimuMap as a set of coupled sub-models. The paper considers the situation where spatial processes operate at different time levels, but are still integrated. An example of such a situation commonly occurs in watershed hydrology where overland flow and stream channel flow have very different flow rates but are highly related as they are subject to the same terrain runoff processes. SimuMap is able to run a network of sub-models that express different time-space derivatives for water flow processes. Sub-models may be coded generically with a map algebra programming language that uses a surface data model. To address the problem of differing time levels in simulation, the paper: (i) reviews general approaches for numerical solvers, (ii) considers the constraints that need to be enforced to use more adaptive time steps in discrete time specified simulations, and (iii) scaling transfer rates in equations that use different time bases for time-space derivatives. A multistep scheme is proposed for SimuMap. This is presented along with a description of its visual programming interface, its modelling formalisms and future plans. (C) 2003 Elsevier Ltd. All rights reserved.

Computational properties of min/max autocorrelation factors

Minimum/maximum autocorrelation factor (MAF) is a suitable algorithm for orthogonalization of a vector random field. Orthogonalization avoids the use of multivariate geostatistics during joint stochastic modeling of geological attributes. This manuscript demonstrates in a practical way that computation of MAF is the same as discriminant analysis of the nested structures. Mathematica software is used to illustrate MAF calculations from a linear model of coregionalization (LMC) model. The limitation of two nested structures in the LMC for MAF is also discussed and linked to the effects of anisotropy and support. The analysis elucidates the matrix properties behind the approach and clarifies relationships that may be useful for model-based approaches. (C) 2003 Elsevier Science Ltd. All rights reserved.

Assessing computational tools for the discovery of transcription factor binding sites

The prediction of regulatory elements is a problem where computational methods offer great hope. Over the past few years, numerous tools have become available for this task. The purpose of the current assessment is twofold: to provide some guidance to users regarding the accuracy of currently available tools in various settings, and to provide a benchmark of data sets for assessing future tools.

Substrate specifity of protein kinases and computational prediction of substrates

To ensure signalling fidelity, kinases must act only on a defined subset of cellular targets. Appreciating the basis for this substrate specificity is essential for understanding the role of an individual protein kinase in a particular cellular process. The specificity in the cell is determined by a combination of peptide specificity of the kinase (the molecular recognition of the sequence surrounding the phosphorylation site), substrate recruitment and phosphatase activity. Peptide specificity plays a crucial role and depends on the complementarity between the kinase and the substrate and therefore on their three-dimensional structures. Methods for experimental identification of kinase substrates and characterization of specificity are expensive and laborious, therefore, computational approaches are being developed to reduce the amount of experimental work required in substrate identification. We discuss the structural basis of substrate specificity of protein kinases and review the experimental and computational methods used to obtain specificity information. (c) 2005 Elsevier B.V. All rights reserved.

MULTIPRED: A computational system for prediction of promiscuous HLA binding peptides

MULTIPRED is a web-based computational system for the prediction of peptide binding to multiple molecules ( proteins) belonging to human leukocyte antigens (HLA) class I A2, A3 and class II DR supertypes. It uses hidden Markov models and artificial neural network methods as predictive engines. A novel data representation method enables MULTIPRED to predict peptides that promiscuously bind multiple HLA alleles within one HLA supertype. Extensive testing was performed for validation of the prediction models. Testing results show that MULTIPRED is both sensitive and specific and it has good predictive ability ( area under the receiver operating characteristic curve A(ROC) > 0.80). MULTIPRED can be used for the mapping of promiscuous T-cell epitopes as well as the regions of high concentration of these targets termed T-cell epitope hotspots. MULTIPRED is available at http:// antigen.i2r.a-star.edu.sg/ multipred/.

Mechanistic modelling of pilling. Part II: Individual-fibre computational model

A one-dimensional computational model of pilling of a fibre assembly has been created. The model follows a set of individual fibres, as free ends and loops appear as fuzz and arc progressively withdrawn from the body of the assembly, and entangle to form pills, which eventually break off or are pulled out. The time dependence of the computation is given by ticks, which correspond to cycles of a wear and laundering process. The movement of the fibres is treated as a reptation process. A set of standard values is used as inputs to the computation. Predictions arc given of the change with a number Of cycles of mass of fuzz, mass of pills, and mass removed from the assembly. Changes in the standard values allow sensitivity studies to be carried out.

Study of flow behaviour in a three-product cyclone using computational fluid dynamics

Simplicity in design and minimal floor space requirements render the hydrocyclone the preferred classifier in mineral processing plants. Empirical models have been developed for design and process optimisation but due to the complexity of the flow behaviour in the hydrocyclone these do not provide information on the internal separation mechanisms. To study the interaction of design variables, the flow behaviour needs to be considered, especially when modelling the new three-product cyclone. Computational fluid dynamics (CFD) was used to model the three-product cyclone, in particular the influence of the dual vortex finder arrangement on flow behaviour. From experimental work performed on the UG2 platinum ore, significant differences in the classification performance of the three-product cyclone were noticed with variations in the inner vortex finder length. Because of this simulations were performed for a range of inner vortex finder lengths. Simulations were also conducted on a conventional hydrocyclone of the same size to enable a direct comparison of the flow behaviour between the two cyclone designs. Significantly, high velocities were observed for the three-product cyclone with an inner vortex finder extended deep into the conical section of the cyclone. CFD studies revealed that in the three-product cyclone, a cylindrical shaped air-core is observed similar to conventional hydrocyclones. A constant diameter air-core was observed throughout the inner vortex finder length, while no air-core was present in the annulus. (c) 2006 Elsevier Ltd. All rights reserved.

Enhancement of drug affinity for cell membranes by conjugation with lipoamino acids II. Experimental and computational evidence using biomembrane models

Lipoamino acids (LAAs) are promoieties able to enhance the amphiphilicity of drugs, facilitating their interaction with cell membranes. Experimental and computational studies were carried out on two series of lipophilic amide conjugates between a model drug (tranylcypromine, TCP) and LAA or alkanoic acids containing a short, medium or long alkyl side chain (C-4 to C-16). The effects of these compounds were evaluated by monolayer surface tension analysis and differential scanning calorimetry using dimyristoylphosphatidylcholine nnonolayers and liposomes as biomembrane models. The experimental results were related to independent calculations to determine partition coefficient and blood-brain partitioning. The comparison of TCP-LAA conjugates with the related series of TCP alkanoyl amides confirmed that the ability to interact with the biomembrane models is not due to the mere increase of lipophilicity, but mainly to the amphipatic nature and the kind of LAA residue. (C) 2005 Elsevier B.V. All rights reserved.

Mechanistic aspects of proton chain transfer: A computational study for the green fluorescent protein chromophore

We explore several models for the ground-state proton chain transfer pathway between the green fluorescent protein chromophore and its surrounding protein matrix, with a view to elucidating mechanistic aspects of this process. We have computed quantum chemically the minimum energy pathways (MEPs) in the ground electronic state for one-, two-, and three-proton models of the chain transfer. There are no stable intermediates for our models, indicating that the proton chain transfer is likely to be a single, concerted kinetic step. However, despite the concerted nature of the overall energy profile, a more detailed analysis of the MEPs reveals clear evidence of sequential movement of protons in the chain. The ground-state proton chain transfer does not appear to be driven by the movement of the phenolic proton off the chromophore onto the neutral water bridge. Rather, this proton is the last of the three protons in the chain to move. We find that the first proton movement is from the bridging Ser205 moiety to the accepting Glu222 group. This is followed by the second proton moving from the bridging water to the Ser205for our model this is where the barrier occurs. The phenolic proton on the chromophore is hence the last in the chain to move, transferring to a bridging “water” that already has substantial negative charge.

Using computational fluid dynamics in combating erosion-corrosion

Computational fluid dynamics was used to search for the links between the observed pattern of attack seen in a bauxite refinery's heat exchanger headers and the hydrodynamics inside the header. Validation of the computational fluid dynamics results was done by comparing then with flow parameters measured in a 1:5 scale model of the first pass header in the laboratory. Computational fluid dynamics simulations were used to establish hydrodynamic similarity between the 1:5 scale and full scale models of the first pass header. It was found that the erosion-corrosion damage seen at the tubesheet of the first pass header was a consequence of increased levels of turbulence at the tubesheet caused by a rapidly turning flow. A prismatic flow corrections device introduced in the past helped in rectifying the problem at the tubesheet but exaggerated the erosion-corrosion problem at the first pass header shell. A number of alternative flow correction devices were tested using computational fluid dynamics. Axial ribbing in the first pass header and an inlet flow diffuser have shown the best performance and were recommended for implementation. Computational fluid dynamics simulations have revealed a smooth orderly low turbulence flow pattern in the second, third and fourth pass as well as the exit headers where no erosion-corrosion was seen in practice. This study has confirmed that near-wall turbulence intensity, which can be successfully predicted by using computational fluid dynamics, is a good hydrodynamic predictor of erosion-corrosion damage in complex geometries. (c) 2006 Published by Elsevier Ltd.

Computational analysis of base composition pattern and promoter elements in the putative promoter regions in relation to expression profiles of 682 human genes on chromosome 22

The base composition pattern (BCP) in the putative promoter region (PPRs) up to 5 Kb lengths of 682 human genes on Chromosome 22 (Chr22) was examined. Two-dimensional (2D) and three-dimensional (3D) functions were designed to delineate the DNA base composition, with four major patterns identified. It is found that 17.6% genes include TATA box, 28.0% GC box, 18.9% CAAT box and 38.4% CpG islands, and approximately 10% genes have one of four putative initiator (Inr) motifs. The occurrence of the promoter elements is tightly associated with the base composition features in the promoter regions, and the associations of the base composition features with occurrence of the promoter elements in the promoter regions mediate tissue-wide expression of the genes in human. The occurrence of two or more promoter elements in the promoter regions is required for the medium- and wide-range expression profiles of the human genes on Chr22. Thus, the reported data shed light on the characteristics of the PPRs of the human genes on Chr22, which may improve our understanding of regulatory roles of the PPRs with occurrence of the promoter elements in gene expression.

Computational methods for the detection of facial palsy

We are developing a telemedicine application which offers automated diagnosis of facial (Bell's) palsy through a Web service. We used a test data set of 43 images of facial palsy patients and 44 normal people to develop the automatic recognition algorithm. Three different image pre-processing methods were used. Machine learning techniques (support vector machine, SVM) were used to examine the difference between the two halves of the face. If there was a sufficient difference, then the SVM recognized facial palsy. Otherwise, if the halves were roughly symmetrical, the SVM classified the image as normal. It was found that the facial palsy images had a greater Hamming Distance than the normal images, indicating greater asymmetry. The median distance in the normal group was 331 (interquartile range 277-435) and the median distance in the facial palsy group was 509 (interquartile range 334-703). This difference was significant (P