Home About us Contact
|
Home About us Contact | ||
|
|
||
Computational Methods (computational + methods)
Selected AbstractsComputational Methods for the Development of Polymeric BiomaterialsADVANCED ENGINEERING MATERIALS, Issue 1-2 2010Aurora D. Costache This review focuses on polymeric biomaterials and provides a selective overview of the computational modeling approaches used to predict their properties and biological responses. Also, a short overview of existing databases and software packages for the biomaterials field is presented. The review summarizes the research in this area since the year 2000. [source] Ibero-Latin American Conference on Computational Methods in Engineering CILAMCE 2005INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING, Issue 6 2007Andrea M. P. Valli No abstract is available for this article. [source] Integrated Computational Methods for Prediction of the Lowest Observable Adverse Effect Level of Food-Borne MoleculesMOLECULAR INFORMATICS, Issue 1 2007Leila Tilaoui Abstract In this work we present an integrated system partly based on the commercially available software TOPKAT, which predicts chronic toxicity through provision of a computational estimation of Lowest Observed Adverse Effect Level (LOAEL) values. We found evidence that the LOAEL correlated with a specific class of molecular descriptors, known as 2D autocorrelation descriptors. The system developed is found to be helpful in supporting , with reasonable confidence , the prioritisation of issues in chemical food research, by establishing levels of safety concern in the absence of sufficient experimental toxicological data. [source] Computational Methods in Biomedical Research edited by KHATTREE, R. and NAIK, D. N.BIOMETRICS, Issue 1 2009Article first published online: 17 MAR 200 No abstract is available for this article. [source] N -Methylation Effects on the Coordination Chemistry of Cyclic Triamines with Divalent Transition Metals and Their CoII Dioxygen CarriersEUROPEAN JOURNAL OF INORGANIC CHEMISTRY, Issue 2 2006Silvia Del Piero Abstract The thermodynamics of complex formation of CoII and CdII ions with the triaza macrocyclic ligand 1,4,7-triazacyclononane (tacn) and its N -methylated derivative 1,4,7-trimethyl-1,4,7-triazacyclononane (Me3tacn) has been studied in dimethyl sulfoxide (DMSO) at 298.1 K and in an ionic medium (0.1 M Et4NClO4) by means of potentiometric, UV/Vis, calorimetric and FT-IR techniques. The results are discussed by taking into account electronic and steric effects as well as solvation of the species concerned. Computational methods based on density functional theory (DFT) have been used to obtain structural information about the ligands and their complexes in order to provide further, independent insights into the effect of N -methylation on the coordination affinity of the ligands towards the metal ions. The computational suggestions are of great help to correlate steric effects and thermodynamic results. The kinetics of dioxygen uptake for the formation of the Co(tacn)2O2 superoxo adduct has also been studied by means of UV/Vis measurements. (© Wiley-VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2006) [source] Bioaccumulation Assessment Using Predictive Approaches,INTEGRATED ENVIRONMENTAL ASSESSMENT AND MANAGEMENT, Issue 4 2009John W Nichols Abstract Mandated efforts to assess chemicals for their potential to bioaccumulate within the environment are increasingly moving into the realm of data inadequacy. Consequently, there is an increasing reliance on predictive tools to complete regulatory requirements in a timely and cost-effective manner. The kinetic processes of absorption, distribution, metabolism, and elimination (ADME) determine the extent to which chemicals accumulate in fish and other biota. Current mathematical models of bioaccumulation implicitly or explicitly consider these ADME processes, but there is a lack of data needed to specify critical model input parameters. This is particularly true for compounds that are metabolized, exhibit restricted diffusion across biological membranes, or do not partition simply to tissue lipid. Here we discuss the potential of in vitro test systems to provide needed data for bioaccumulation modeling efforts. Recent studies demonstrate the utility of these systems and provide a "proof of concept" for the prediction models. Computational methods that predict ADME processes from an evaluation of chemical structure are also described. Most regulatory agencies perform bioaccumulation assessments using a weight-of-evidence approach. A strategy is presented for incorporating predictive methods into this approach. To implement this strategy it is important to understand the "domain of applicability" of both in vitro and structure-based approaches, and the context in which they are applied. [source] Computational methods for optical molecular imagingINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING, Issue 12 2009Duan Chen Abstract A new computational technique, the matched interface and boundary (MIB) method, is presented to model the photon propagation in biological tissue for the optical molecular imaging. Optical properties have significant differences in different organs of small animals, resulting in discontinuous coefficients in the diffusion equation model. Complex organ shape of small animal induces singularities of the geometric model as well. The MIB method is designed as a dimension splitting approach to decompose a multidimensional interface problem into one-dimensional ones. The methodology simplifies the topological relation near an interface and is able to handle discontinuous coefficients and complex interfaces with geometric singularities. In the present MIB method, both the interface jump condition and the photon flux jump conditions are rigorously enforced at the interface location by using only the lowest-order jump conditions. This solution near the interface is smoothly extended across the interface so that central finite difference schemes can be employed without the loss of accuracy. A wide range of numerical experiments are carried out to validate the proposed MIB method. The second-order convergence is maintained in all benchmark problems. The fourth-order convergence is also demonstrated for some three-dimensional problems. The robustness of the proposed method over the variable strength of the linear term of the diffusion equation is also examined. The performance of the present approach is compared with that of the standard finite element method. The numerical study indicates that the proposed method is a potentially efficient and robust approach for the optical molecular imaging. Copyright © 2008 John Wiley & Sons, Ltd. [source] Identification of small molecule aggregators from large compound libraries by support vector machinesJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 4 2010Hanbing Rao Abstract Small molecule aggregators non-specifically inhibit multiple unrelated proteins, rendering them therapeutically useless. They frequently appear as false hits and thus need to be eliminated in high-throughput screening campaigns. Computational methods have been explored for identifying aggregators, which have not been tested in screening large compound libraries. We used 1319 aggregators and 128,325 non-aggregators to develop a support vector machines (SVM) aggregator identification model, which was tested by four methods. The first is five fold cross-validation, which showed comparable aggregator and significantly improved non-aggregator identification rates against earlier studies. The second is the independent test of 17 aggregators discovered independently from the training aggregators, 71% of which were correctly identified. The third is retrospective screening of 13M PUBCHEM and 168K MDDR compounds, which predicted 97.9% and 98.7% of the PUBCHEM and MDDR compounds as non-aggregators. The fourth is retrospective screening of 5527 MDDR compounds similar to the known aggregators, 1.14% of which were predicted as aggregators. SVM showed slightly better overall performance against two other machine learning methods based on five fold cross-validation studies of the same settings. Molecular features of aggregation, extracted by a feature selection method, are consistent with published profiles. SVM showed substantial capability in identifying aggregators from large libraries at low false-hit rates. © 2009 Wiley Periodicals, Inc.J Comput Chem, 2010 [source] Protein,protein docking dealing with the unknownJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 2 2010Irina S. Moreira Abstract Protein,protein binding is one of the critical events in biology, and knowledge of proteic complexes three-dimensional structures is of fundamental importance for the biochemical study of pharmacologic compounds. In the past two decades there was an emergence of a large variety of algorithms designed to predict the structures of protein,protein complexes,a procedure named docking. Computational methods, if accurate and reliable, could play an important role, both to infer functional properties and to guide new experiments. Despite the outstanding progress of the methodologies developed in this area, a few problems still prevent protein,protein docking to be a widespread practice in the structural study of proteins. In this review we focus our attention on the principles that govern docking, namely the algorithms used for searching and scoring, which are usually referred as the docking problem. We also focus our attention on the use of a flexible description of the proteins under study and the use of biological information as the localization of the hot spots, the important residues for protein,protein binding. The most common docking softwares are described too. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010 [source] Design of granule structure: Computational methods and experimental realizationAICHE JOURNAL, Issue 11 2006Mansoor A. Ansari Abstract The spatial distribution of solid components and porosity within a composite granule,its microstructure,is an important attribute as it carries information about the processing history of the granule and determines its end-use application properties, particularly the dissolution rate. In this work, the problem of rational design of granule structure is formulated, and two methods for its solution are proposed,stochastic design, which is based on random permutation of points within the structure using the simulated annealing algorithm, and variational design, which is based on direct simulation of granule formation from its constituent primary particles, followed by direct simulation of granule dissolution. The variational design method is demonstrated in a case study of the effect of primary particle size, radial distribution of components, and composition of a two-component granule (active, excipient) on the dissolution profile. Selected granule structures designed computationally were also physically made by fluid-bed granulation, their structure analyzed by X-ray micro-tomography, and dissolution curves measured. It was confirmed that the designed structures are feasible to manufacture and that they meet the required dissolution profiles. © 2006 American Institute of Chemical Engineers AIChE J, 2006 [source] Machine learning approaches for predicting compounds that interact with therapeutic and ADMET related proteinsJOURNAL OF PHARMACEUTICAL SCIENCES, Issue 11 2007H. Li Abstract Computational methods for predicting compounds of specific pharmacodynamic and ADMET (absorption, distribution, metabolism, excretion and toxicity) property are useful for facilitating drug discovery and evaluation. Recently, machine learning methods such as neural networks and support vector machines have been explored for predicting inhibitors, antagonists, blockers, agonists, activators and substrates of proteins related to specific therapeutic and ADMET property. These methods are particularly useful for compounds of diverse structures to complement QSAR methods, and for cases of unavailable receptor 3D structure to complement structure-based methods. A number of studies have demonstrated the potential of these methods for predicting such compounds as substrates of P-glycoprotein and cytochrome P450 CYP isoenzymes, inhibitors of protein kinases and CYP isoenzymes, and agonists of serotonin receptor and estrogen receptor. This article is intended to review the strategies, current progresses and underlying difficulties in using machine learning methods for predicting these protein binders and as potential virtual screening tools. Algorithms for proper representation of the structural and physicochemical properties of compounds are also evaluated. © 2007 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 96: 2838,2860, 2007 [source] Computational methods in authorship attributionJOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY, Issue 1 2009Moshe Koppel Statistical authorship attribution has a long history, culminating in the use of modern machine learning classification methods. Nevertheless, most of this work suffers from the limitation of assuming a small closed set of candidate authors and essentially unlimited training text for each. Real-life authorship attribution problems, however, typically fall short of this ideal. Thus, following detailed discussion of previous work, three scenarios are considered here for which solutions to the basic attribution problem are inadequate. In the first variant, the profiling problem, there is no candidate set at all; in this case, the challenge is to provide as much demographic or psychological information as possible about the author. In the second variant, the needle-in-a-haystack problem, there are many thousands of candidates for each of whom we might have a very limited writing sample. In the third variant, the verification problem, there is no closed candidate set but there is one suspect; in this case, the challenge is to determine if the suspect is or is not the author. For each variant, it is shown how machine learning methods can be adapted to handle the special challenges of that variant. [source] Special Topic Issue of JASIST: Computational methods for style analysis and synthesisJOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY, Issue 7 2003Shlomo Argamon [source] Computational methods for studies of multiexciton complexes,PHYSICA STATUS SOLIDI (B) BASIC SOLID STATE PHYSICS, Issue 15 2006T. Vänskä Abstract Powerful computational methods are presented for studies of energy levels, photon-recombination rates, and phonon-relaxation rates of neutral and charged multiexciton complexes at correlated levels of theory. The electron,hole system is described by a two-band effective-mass Hamiltonian. The one-particle functions are expanded in a basis set consisting of anisotropic Gaussian functions. The many-body Hamiltonian constructed in the space of the antisymmetric products of one-particle functions is diagonalized using general coupled-cluster and configuration-interaction methods. The expansion coefficients of the coupled-cluster and configuration-interaction wave functions are obtained by solving the corresponding equations using direct iterative algorithms. We demonstrate the potential of the computational approaches by calculating total energies of multiexciton complexes at coupled-cluster and configuration-interaction levels. Computational methods for studies of radiative recombination and phonon-relaxation rates have also been developed and results are reported for radiative recombination rates and recombination energies of the exciton, biexciton, and of the positive and the negative trions confined in a InGaAs/GaAs quantum-dot sample. Phonon-relaxation rates have been calculated for a few low-lying ,g states of the exciton complex of the same quantum-dot sample. (© 2006 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source] Do common in silico tools predict the clinical consequences of amino-acid substitutions in the CFTR gene?CLINICAL GENETICS, Issue 5 2010R Dorfman Dorfman R, Nalpathamkalam T, Taylor C, Gonska T, Keenan K, Yuan XW, Corey M, Tsui L-C, Zielenski J, Durie P. Do common in silico tools predict the clinical consequences of amino-acid substitutions in the CFTR gene? Computational methods are used to predict the molecular consequences of amino-acid substitutions on the basis of evolutionary conservation or protein structure, but their utility in clinical diagnosis or prediction of disease outcome has not been well validated. We evaluated three popular computer programs, namely, PANTHER, SIFT and PolyPhen, by comparing the predicted clinical outcomes for a group of known CFTR missense mutations against the diagnosis of cystic fibrosis (CF) and clinical manifestations in cohorts of subjects with CF-disease and CFTR-related disorders carrying these mutations. Owing to poor specificity, none of tools reliably distinguished between individual mutations that confer CF disease from mutations found in subjects with a CFTR-related disorder or no disease. Prediction scores for CFTR mutations derived from PANTHER showed a significant overall statistical correlation with the spectrum of disease severity associated with mutations in the CFTR gene. In contrast, PolyPhen - and SIFT-derived scores only showed significant differences between CF-causing and non-CF variants. Current computational methods are not recommended for establishing or excluding a CF diagnosis, notably as a newborn screening strategy or in patients with equivocal test results. [source] Advanced Analysis of Steel Frames Using Parallel Processing and VectorizationCOMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 5 2001C. M. Foley Advanced methods of analysis have shown promise in providing economical building structures through accurate evaluation of inelastic structural response. One method of advanced analysis is the plastic zone (distributed plasticity) method. Plastic zone analysis often has been deemed impractical due to computational expense. The purpose of this article is to illustrate applications of plastic zone analysis on large steel frames using advanced computational methods. To this end, a plastic zone analysis algorithm capable of using parallel processing and vector computation is discussed. Applicable measures for evaluating program speedup and efficiency on a Cray Y-MP C90 multiprocessor supercomputer are described. Program performance (speedup and efficiency) for parallel and vector processing is evaluated. Nonlinear response including postcritical branches of three large-scale fully restrained and partially restrained steel frameworks is computed using the proposed method. The results of the study indicate that advanced analysis of practical steel frames can be accomplished using plastic zone analysis methods and alternate computational strategies. [source] Bandgap characters in GaAs-based ternary alloysCRYSTAL RESEARCH AND TECHNOLOGY, Issue 1 2010N. Tit Abstract The existence and origins of the bowing character in the bandgap variation of GaAs-based ternary alloys are theoretically investigated based on two different computational methods. Within the framework of the virtual crystal approximation (VCA), both the empirical sp3s * tight-binding (TB) method with, and without, the inclusion of the spin-orbit coupling effects, and the first-principle full-potential linear augmented plane wave (FP-LAPW) technique are applied on both the common-cation GaSbxAs1-x and the common-anion Ga1-xInxAs alloys. These methods are used to calculate the bandgap energy, the partial and total densities of states and the constituent charge ionicity versus the composition x. The results show that the bowing behavior exists in the case of common-cation alloys (GaSbxAs1-x) as a manifestation of a competition between the anion atoms (As and Sb) in trapping the made-available-cationic charges. The bowing parameter is found to be proportional to the electronegativity characters of the competing anions (,anion). Consistent with this in the case of common-anion alloys (Ga1-xInxAs), as due to the lack of anion competition, the bowing is just absent and the variation of bandgap energy is found to be rather linear. The excellent agreement between our theoretical results and recent photoluminescence data has corroborated our claim. (© 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source] meta -Terphenyl Phosphaalkenes Bearing Electron-Donating and -Accepting GroupsEUROPEAN JOURNAL OF INORGANIC CHEMISTRY, Issue 6 2010Vittal B. Gudimetla Abstract A set of para -substituted meta -terphenyl phosphaalkenes of the form 4-X-2,6-Mes2C6H2P=C(H)C6H4 -4-X, (X = H, MeO or NMe2; X, = H, CN, or NO2) have been synthesized to allow systematic studies of the impact of remote X and X, substituents on the phosphaalkene unit. The new compounds were characterized by 1H and 31P NMR spectroscopy, UV/Vis absorption spectroscopy, single X-ray crystal structures (for four compounds) and by electrochemical studies. The introduction of remote groups (X,) on the less hindered phenyl ring generated more significant effects on the physical properties of the materials than did substituents (X) on the hindered meta -terphenyl rings. These effects were also explored by computational methods in order to assess the influence of substituents on structures and properties. The polarization of these molecules is less than that produced for analogous alkenes, as the phosphaalkenes bear sterically demanding groups that constrain the systems to adopt conformations that are less than ideal for maximum ,-conjugation of the central , network [source] Spectroscopic and Computational Study on New Blue Emitting ReL(CO)3Cl Complexes Containing Pyridylimidazo[1,5- a]pyridine LigandsEUROPEAN JOURNAL OF INORGANIC CHEMISTRY, Issue 23 2008Claudio Garino Abstract The structural and photophysical properties of three new ReL(CO)3Cl complexes (ReL1,ReL3) and their 1-(2-pyridyl)imidazo[1,5- a]pyridine ligands, namely 3-methyl-1-(2-pyridyl)imidazo[1,5- a]pyridine (L1), 1-(2-pyridyl)-3-[4-(trifluoromethyl)phenyl]imidazo[1,5- a]pyridine (L2), and 3-(4-nitrophenyl)-1-(2-pyridyl)imidazo[1,5- a]pyridine (L3), were studied by spectroscopy, X-ray diffraction, and computational methods. ReL1,ReL3 have high-energy singlet emissions arising from a , , ,* ligand-centered state. In oxygen-free acetonitrile solutions, the complexes display dual fluorescence due to intense ligand-centered triplet emission.(© Wiley-VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2008) [source] On the Structure of Cross-Conjugated 2,3-DiphenylbutadieneEUROPEAN JOURNAL OF ORGANIC CHEMISTRY, Issue 28 2007Cornelis A. van Walree Abstract The structure of the cross-conjugated compound 2,3-diphenylbutadiene was investigated by single-crystal X-ray diffraction and computational methods. In the crystal structure the central butadiene fragment adopts an s-gauche geometry [,55.6(2)° torsion angle , around the essential single bond], whereas the styrene moieties are close to planarity. MP2/6-311G* calculations show that the s-gauche conformation represents the global minimum along the , coordinate, but also revealed the existence of an s-trans local minimum. While the crystal structure seems to reflect dominance of styrene-like conjugation, the MP2/6-311G* calculations indicate that conjugation in both the styrene and butadiene ,-systems is important. An NBO orbital deletion study shows that the structure is primarily determined by (hyper)conjugation and that steric effects play a minor role. (© Wiley-VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2007) [source] Integrating modelling and experiments to assess dynamic musculoskeletal function in humansEXPERIMENTAL PHYSIOLOGY, Issue 2 2006J. W. Fernandez Magnetic resonance imaging, bi-plane X-ray fluoroscopy and biomechanical modelling are enabling technologies for the non-invasive evaluation of muscle, ligament and joint function during dynamic activity. This paper reviews these various technologies in the context of their application to the study of human movement. We describe how three-dimensional, subject-specific computer models of the muscles, ligaments, cartilage and bones can be developed from high-resolution magnetic resonance images; how X-ray fluoroscopy can be used to measure the relative movements of the bones at a joint in three dimensions with submillimetre accuracy; how complex 3-D dynamic simulations of movement can be performed using new computational methods based on non-linear control theory; and how musculoskeletal forces derived from such simulations can be used as inputs to elaborate finite-element models of a joint to calculate contact stress distributions on a subject-specific basis. A hierarchical modelling approach is highlighted that links rigid-body models of limb segments with detailed finite-element models of the joints. A framework is proposed that integrates subject-specific musculoskeletal computer models with highly accurate in vivo experimental data. [source] Experimental and computational investigation of three-dimensional mixed-mode fatigueFATIGUE & FRACTURE OF ENGINEERING MATERIALS AND STRUCTURES, Issue 1 2002S. C. Forth Experimental and computational methods were developed to model three-dimensional (3-D) mixed-mode crack growth under fatigue loading with the objective of evaluating proposed 3-D fracture criteria. The experiments utilized 7075-T73 aluminium forgings cut into modified ASTM E740 surface crack specimens with pre-cracks orientated at angles of 30, 45 and 60° in separate tests. The progress of the evolving fatigue crack was monitored in real time using an automated visualization system. In addition, the amplitude of the loading was increased at prescribed intervals to mark the location of the 3-D crack front for post-test inspection. In order to evaluate proposed crack growth equations, computer simulations of the experiments were conducted using a 3-D fracture model based on the surface integral method. An automatic mesher advanced the crack front by adding a ring of elements consistent with local application of fracture criteria governing rate and direction of growth. Comparisons of the computational and experimental results showed that the best correlation was obtained when KII and KIII were incorporated in the growth rate equations. [source] The ,I/,III-tubulin isoforms and their complexes with antimitotic agentsFEBS JOURNAL, Issue 14 2006Docking, molecular dynamics studies Both microtubule destabilizer and stabilizer agents are important molecules in anticancer therapy. In particular, paclitaxel has been demonstrated to be effective for the treatment of ovarian, breast, and nonsmall cell lung carcinomas. It has been shown that emergence of resistance against this agent correlates with an increase in the relative abundance of tubulin isoform ,III and that the more recently discovered IDN5390 can be effectively used once resistance has emerged. In this paper, we analyze the binding modes of these antimitotic agents to type I and III isoforms of ,-tubulin by computational methods. Our results are able to provide a molecular explanation of the experimental data. Using the same protocol, we could also show that no preference for any of the two isoforms can be detected for epothilone A, a potentially very interesting drug for which no data about the emergence of resistance is currently available. Our analysis provides structural insights about the recognition mode and the stabilization mechanism of these antimitotic agents and provides useful suggestions for the design of more potent and selective antimitotic agents. [source] Genome-scale models of bacterial metabolism: reconstruction and applicationsFEMS MICROBIOLOGY REVIEWS, Issue 1 2009Maxime Durot Abstract Genome-scale metabolic models bridge the gap between genome-derived biochemical information and metabolic phenotypes in a principled manner, providing a solid interpretative framework for experimental data related to metabolic states, and enabling simple in silico experiments with whole-cell metabolism. Models have been reconstructed for almost 20 bacterial species, so far mainly through expert curation efforts integrating information from the literature with genome annotation. A wide variety of computational methods exploiting metabolic models have been developed and applied to bacteria, yielding valuable insights into bacterial metabolism and evolution, and providing a sound basis for computer-assisted design in metabolic engineering. Recent advances in computational systems biology and high-throughput experimental technologies pave the way for the systematic reconstruction of metabolic models from genomes of new species, and a corresponding expansion of the scope of their applications. In this review, we provide an introduction to the key ideas of metabolic modeling, survey the methods, and resources that enable model reconstruction and refinement, and chart applications to the investigation of global properties of metabolic systems, the interpretation of experimental results, and the re-engineering of their biochemical capabilities. [source] Multistage analysis strategies for genome-wide association studies: summary of group 3 contributions to Genetic Analysis Workshop 16GENETIC EPIDEMIOLOGY, Issue S1 2009Rosalind J. Neuman Abstract This contribution summarizes the work done by six independent teams of investigators to identify the genetic and non-genetic variants that work together or independently to predispose to disease. The theme addressed in these studies is multistage strategies in the context of genome-wide association studies (GWAS). The work performed comes from Group 3 of the Genetic Analysis Workshop 16 held in St. Louis, Missouri in September 2008. These six studies represent a diversity of multistage methods of which five are applied to the North American Rheumatoid Arthritis Consortium rheumatoid arthritis case-control data, and one method is applied to the low-density lipoprotein phenotype in the Framingham Heart Study simulated data. In the first stage of analyses, the majority of studies used a variety of screening techniques to reduce the noise of single-nucleotide polymorphisms purportedly not involved in the phenotype of interest. Three studies analyzed the data using penalized regression models, either LASSO or the elastic net. The main result was a reconfirmation of the involvement of variants in the HLA region on chromosome 6 with rheumatoid arthritis. The hope is that the intense computational methods highlighted in this group of papers will become useful tools in future GWAS. Genet. Epidemiol. 33 (Suppl. 1):S19,S23, 2009. © 2009 Wiley-Liss, Inc. [source] New Ruthenium Complexes Containing Oligoalkylthiophene-Substituted 1,10-Phenanthroline for Nanocrystalline Dye-Sensitized Solar Cells,ADVANCED FUNCTIONAL MATERIALS, Issue 1 2007C.-Y. Chen Abstract Two new ruthenium complexes [Ru(dcbpy)(L)(NCS)2], where dcbpy is 4,4,-dicarboxylic acid-2,2,-bipyridine and L is 3,8-bis(4-octylthiophen-2-yl)-1,10-phenanthroline (CYC-P1) or 3,8-bis(4-octyl-5-(4-octylthiophen-2-yl)thiophen-2-yl)-1,10-phenanthroline (CYC-P2), are synthesized, characterized by physicochemical and semiempirical computational methods, and used as photosensitizers in nanocrystalline dye-sensitized solar cells. It was found that the difference in light-harvesting ability between CYC-P1 and CYC-P2 is associated mainly with the location of the frontier orbitals, in particular the highest occupied molecular orbital (HOMO). Increasing the conjugation length of the ancillary ligand decreases the energy of the metal-to-ligand charge transfer (MLCT) transition, but at the same time reduces the molar absorption coefficient, owing to the HOMO located partially on the ancillary ligand of the ruthenium complex. The incident photon-to-current conversion efficiency curves of the devices are consistent with the MLCT band of the complexes. Therefore, the overall efficiencies of CYC-P1 and CYC-P2 sensitized cells are 6.01 and 3.42,%, respectively, compared to a cis- di(thiocyanato)-bis(2,2,-bipyridyl)-4,4,-dicarboxylate ruthenium(II)-sensitized device, which is 7.70,% using the same device-fabrication process and measuring parameters. [source] Interpreting missense variants: comparing computational methods in human disease genes CDKN2A, MLH1, MSH2, MECP2, and tyrosinase (TYR),,HUMAN MUTATION, Issue 7 2007Philip A. Chan Abstract The human genome contains frequent single-basepair variants that may or may not cause genetic disease. To characterize benign vs. pathogenic missense variants, numerous computational algorithms have been developed based on comparative sequence and/or protein structure analysis. We compared computational methods that use evolutionary conservation alone, amino acid (AA) change alone, and a combination of conservation and AA change in predicting the consequences of 254 missense variants in the CDKN2A (n = 92), MLH1 (n = 28), MSH2 (n = 14), MECP2 (n = 30), and tyrosinase (TYR) (n = 90) genes. Variants were validated as either neutral or deleterious by curated locus-specific mutation databases and published functional data. All methods that use evolutionary sequence analysis have comparable overall prediction accuracy (72.9,82.0%). Mutations at codons where the AA is absolutely conserved over a sufficient evolutionary distance (about one-third of variants) had a 91.6 to 96.8% likelihood of being deleterious. Three algorithms (SIFT, PolyPhen, and A-GVGD) that differentiate one variant from another at a given codon did not significantly improve predictive value over conservation score alone using the BLOSUM62 matrix. However, when all four methods were in agreement (62.7% of variants), predictive value improved to 88.1%. These results confirm a high predictive value for methods that use evolutionary sequence conservation, with or without considering protein structural change, to predict the clinical consequences of missense variants. The methods can be generalized across genes that cause different types of genetic disease. The results support the clinical use of computational methods as one tool to help interpret missense variants in genes associated with human genetic disease. Hum Mutat 28(7), 683,693, 2007. Published 2007 Wiley-Liss, Inc. [source] Adaptive computational methods for variational inequalities based on mixed formulationsINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 11 2006F. T. SuttmeierArticle first published online: 27 APR 200 Abstract This work describes concepts for a posteriori error estimation and adaptive mesh design for finite element models where the solution is subjected to inequality constraints. These methods are developed here for several model problems. Based on these examples, unified frameworks are proposed, which provide a systematic way of adaptive error control for problems stated in form of variational inequalities. Copyright © 2006 John Wiley & Sons, Ltd. [source] Flexible constraints for regularization in learning from dataINTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 6 2004Eyke Hüllermeier By its very nature, inductive inference performed by machine learning methods mainly is data driven. Still, the incorporation of background knowledge,if available,can help to make inductive inference more efficient and to improve the quality of induced models. Fuzzy set,based modeling techniques provide a convenient tool for making expert knowledge accessible to computational methods. In this article, we exploit such techniques within the context of the regularization (penalization) framework of inductive learning. The basic idea is to express knowledge about an underlying data-generating process in terms of flexible constraints and to penalize those models violating these constraints. An optimal model is one that achieves an optimal trade-off between fitting the data and satisfying the constraints. © 2004 Wiley Periodicals, Inc. [source] The search for low energy conformational families of small peptides: Searching for active conformations of small peptides in the absence of a known receptor,INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY, Issue 15 2007Katrina W. Lexa Abstract Breast cancer is the most common cancer among women. Tamoxifen is the preferred drug for estrogen receptor-positive breast cancer treatment, yet many of these cancers are intrinsically resistant to tamoxifen or acquire resistance during treatment. Therefore, scientists are searching for breast cancer drugs that have different molecular targets. Previous work revealed that 8-mer and cyclic 9-mer peptides inhibit breast cancer in mouse and rat model systems, interacting with an unknown receptor, while peptides smaller than eight amino acids did not inhibit breast cancer. We have shown that the use of replica exchange molecular dynamics predicts structure and dynamics of active peptides, leading to the discovery of smaller peptides with full biological activity. These simulations identified smaller peptide analogs with a conserved turn, a ,-turn formed in the larger peptides. These analogs inhibit estrogen-dependent cell growth in a mouse uterine growth assay, a test showing reliable correlation with human breast cancer inhibition. We outline the computational methods that were tried and used with the experimental information that led to the successful completion of this research. © 2007 Wiley Periodicals, Inc. Int J Quantum Chem, 2007 [source] | ||||||||||||||||||||||||||||||||||||||||||||||||||||