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Search Results: 1 - 10 of 96844 matches for " Jonathan W. Arthur "
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Computational Methods for Protein Identification from Mass Spectrometry Data
Leo McHugh,Jonathan W Arthur
PLOS Computational Biology , 2008, DOI: 10.1371/journal.pcbi.0040012
Abstract: Protein identification using mass spectrometry is an indispensable computational tool in the life sciences. A dramatic increase in the use of proteomic strategies to understand the biology of living systems generates an ongoing need for more effective, efficient, and accurate computational methods for protein identification. A wide range of computational methods, each with various implementations, are available to complement different proteomic approaches. A solid knowledge of the range of algorithms available and, more critically, the accuracy and effectiveness of these techniques is essential to ensure as many of the proteins as possible, within any particular experiment, are correctly identified. Here, we undertake a systematic review of the currently available methods and algorithms for interpreting, managing, and analyzing biological data associated with protein identification. We summarize the advances in computational solutions as they have responded to corresponding advances in mass spectrometry hardware. The evolution of scoring algorithms and metrics for automated protein identification are also discussed with a focus on the relative performance of different techniques. We also consider the relative advantages and limitations of different techniques in particular biological contexts. Finally, we present our perspective on future developments in the area of computational protein identification by considering the most recent literature on new and promising approaches to the problem as well as identifying areas yet to be explored and the potential application of methods from other areas of computational biology.
Predicting Peptide Binding Affinities to MHC Molecules Using a Modified Semi-Empirical Scoring Function
Webber W. P. Liao, Jonathan W. Arthur
PLOS ONE , 2011, DOI: 10.1371/journal.pone.0025055
Abstract: The Major Histocompatibility Complex (MHC) plays an important role in the human immune system. The MHC is involved in the antigen presentation system assisting T cells to identify foreign or pathogenic proteins. However, an MHC molecule binding a self-peptide may incorrectly trigger an immune response and cause an autoimmune disease, such as multiple sclerosis. Understanding the molecular mechanism of this process will greatly assist in determining the aetiology of various diseases and in the design of effective drugs. In the present study, we have used the Fresno semi-empirical scoring function and modify the approach to the prediction of peptide-MHC binding by using open-source and public domain software. We apply the method to HLA class II alleles DR15, DR1, and DR4, and the HLA class I allele HLA A2. Our analysis shows that using a large set of binding data and multiple crystal structures improves the predictive capability of the method. The performance of the method is also shown to be correlated to the structural similarity of the crystal structures used. We have exposed some of the obstacles faced by structure-based prediction methods and proposed possible solutions to those obstacles. It is envisaged that these obstacles need to be addressed before the performance of structure-based methods can be on par with the sequence-based methods.
Modeling Single Nucleotide Polymorphisms in the Human AKR1C1 and AKR1C2 Genes: Implications for Functional and Genotyping Analyses
Jonathan W. Arthur,Juergen K. V. Reichardt
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0015604
Abstract: Enzymes encoded by the AKR1C1 and AKR1C2 genes are responsible for the metabolism of progesterone and 5α-dihydrotestosterone (DHT), respectively. The effect of amino acid substitutions, resulting from single nucleotide polymorphisms (SNPs) in the AKR1C2 gene, on the enzyme kinetics of the AKR1C2 gene product were determined experimentally by Takashi et al. In this paper, we used homology modeling to predict and analyze the structure of AKR1C1 and AKR1C2 genetic variants. The experimental reduction in enzyme activity in the AKR1C2 variants F46Y and L172Q, as determined by Takahashi et al., is predicted to be due to increased instability in cofactor binding, caused by disruptions to the hydrogen bonds between NADP and AKR1C2, resulting from the insertion of polar residues into largely non-polar environments near the site of cofactor binding. Other AKR1C2 variants were shown to involve either conservative substitutions or changes taking place on the surface of the molecule and distant from the active site, confirming the experimental finding of Takahashi et al. that these variants do not result in any statistically significant reduction in enzyme activity. The AKR1C1 R258C variant is predicted to have no effect on enzyme activity for similar reasons. Thus, we provide further insight into the molecular mechanism of the enzyme kinetics of these proteins. Our data also highlight previously reported difficulties with online databases.
Harvest: an open-source tool for the validation and improvement of peptide identification metrics and fragmentation exploration
Leo C McHugh, Jonathan W Arthur
BMC Bioinformatics , 2010, DOI: 10.1186/1471-2105-11-448
Abstract: We present Harvest: an open source software tool for analysing fragmentation patterns and assessing the power of a new piece of information about the MS/MS fragmentation process to more clearly differentiate between correct and random peptide assignments. We demonstrate this functionality using data metrics derived from the properties of individual datasets in a peptide identification context. Using Harvest, we demonstrate how the development of such metrics may improve correct peptide assignment confidence in the context of a high-throughput proteomics experiment and characterise properties of peptide fragmentation.Harvest provides a simple framework in C++ for analysing and prototyping metrics for peptide matching, the core of the protein identification problem. It is not a protein identification package and answers a different research question to packages such as Sequest, Mascot, X!Tandem, and other protein identification packages. It does not aim to maximise the number of assigned peptides from a set of unknown spectra, but instead provides a method by which researchers can explore fragmentation properties and assess the power of novel metrics for peptide matching in the context of a given experiment. Metrics developed using Harvest may then become candidates for later integration into protein identification packages.Protein identification using mass spectrometry is one of the fundamental tools of proteomics. Liquid Chromatography coupled to Electro-Spray Injection Tandem Mass Spectrometry (LC/MS/MS) [1] is the method of choice for the fully automated, high throughput experiments that increasingly typify proteomics research [2-4]. These methods have pre-processing steps that may include extracting the proteins, digesting the proteins with a cleavage enzyme such as trypsin, and separating the resultant peptides using reverse phase LC columns. The samples are then introduced into the mass spectrometer by means of elution through a nano-spray injector. The output
Wavelength Accuracy of the Keck HIRES Spectrograph and Measuring Changes in the Fine Structure Constant
Kim Griest,Jonathan B. Whitmore,Arthur M. Wolfe,J. Xavier Prochaska,J. Christopher Howk,Geoffrey W. Marcy
Physics , 2009, DOI: 10.1088/0004-637X/708/1/158
Abstract: We report on an attempt to accurately wavelength calibrate four nights of data taken with the Keck HIRES spectrograph on QSO PHL957, for the purpose of determining whether the fine structure constant was different in the past. Using new software and techniques, we measured the redshifts of various Ni II, Fe II, Si II, etc. lines in a damped Ly-alpha system at z=2.309. Roughly half the data was taken through the Keck iodine cell which contains thousands of well calibrated iodine lines. Using these iodine exposures to calibrate the normal Th-Ar Keck data pipeline output we found absolute wavelength offsets of 500 m/s to 1000 m/s with drifts of more than 500 m/s over a single night, and drifts of nearly 2000 m/s over several nights. These offsets correspond to an absolute redshift of uncertainty of about Delta z=10^{-5} (Delta lambda= 0.02 Ang), with daily drifts of around Delta z=5x10^{-6} (Delta lambda =0.01 Ang), and multiday drifts of nearly Delta z=2x10^{-5} (0.04 Ang). The causes of the wavelength offsets are not known, but since claimed shifts in the fine structure constant would result in velocity shifts of less than 100 m/s, this level of systematic uncertainty makes may make it difficult to use Keck HIRES data to constrain the change in the fine structure constant. Using our calibrated data, we applied both our own fitting software and standard fitting software to measure (Delta alpha)/alpha, but discovered that we could obtain results ranging from significant detection of either sign, to strong null limits, depending upon which sets of lines and which fitting method was used. We thus speculate that the discrepant results on (Delta alpha)/alpha reported in the literature may be due to random fluctuations coming from under-estimated systematic errors in wavelength calibration and fitting procedure.
Novel Approaches to Detect Serum Biomarkers for Clinical Response to Interferon-β Treatment in Multiple Sclerosis
Kaushal S. Gandhi,Fiona C. McKay,Eve Diefenbach,Ben Crossett,Stephen D. Schibeci,Robert N. Heard,Graeme J. Stewart,David R. Booth,Jonathan W. Arthur
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0010484
Abstract: Interferon beta (IFNβ) is the most common immunomodulatory treatment for relapsing-remitting multiple sclerosis (RRMS). However, some patients fail to respond to treatment. In this study, we identified putative clinical response markers in the serum and plasma of people with multiple sclerosis (MS) treated with IFNβ. In a discovery-driven approach, we use 2D-difference gel electrophoresis (DIGE) to identify putative clinical response markers and apply power calculations to identify the sample size required to further validate those markers. In the process we have optimized a DIGE protocol for plasma to obtain cost effective and high resolution gels for effective spot comparison. APOA1, A2M, and FIBB were identified as putative clinical response markers. Power calculations showed that the current DIGE experiment requires a minimum of 10 samples from each group to be confident of 1.5 fold difference at the p<0.05 significance level. In a complementary targeted approach, Cytometric Beadarray (CBA) analysis showed no significant difference in the serum concentration of IL-6, IL-8, MIG, Eotaxin, IP-10, MCP-1, and MIP-1α, between clinical responders and non-responders, despite the association of these proteins with IFNβ treatment in MS.
Aging Brain from a Network Science Perspective: Something to Be Positive About?
Michelle W. Voss, Chelsea N. Wong, Pauline L. Baniqued, Jonathan H. Burdette, Kirk I. Erickson, Ruchika Shaurya Prakash, Edward McAuley, Paul J. Laurienti, Arthur F. Kramer
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0078345
Abstract: To better understand age differences in brain function and behavior, the current study applied network science to model functional interactions between brain regions. We observed a shift in network topology whereby for older adults subcortical and cerebellar structures overlapping with the Salience network had more connectivity to the rest of the brain, coupled with fragmentation of large-scale cortical networks such as the Default and Fronto-Parietal networks. Additionally, greater integration of the dorsal medial thalamus and red nucleus in the Salience network was associated with greater satisfaction with life for older adults, which is consistent with theoretical predictions of age-related increases in emotion regulation that are thought to help maintain well-being and life satisfaction in late adulthood. In regard to cognitive abilities, greater ventral medial prefrontal cortex coherence with its topological neighbors in the Default Network was associated with faster processing speed. Results suggest that large-scale organizing properties of the brain differ with normal aging, and this perspective may offer novel insight into understanding age-related differences in cognitive function and well-being.
El conductismo social: un fundamento de la modificación del comportamiento
Arthur W. Staats
Revista Latinoamericana de Psicología , 1979,
Abstract: Begínning in the earIy 1950′s the approach now called social behaviorism began making contributions to the development of behaviorism and behavior modification. Included in these contributions of social behaviorism were the first behavior analysis and the statement of behavior principIes and procedures, the development of the token reinforcer system, the concept of behavioral analysís as a general method and the presentation of a large number of behavior analyses later used in behavior modification studíes, the concept of behavíoral assessment, and the first behavioral abnormal psychology. These past contributíons are described as an introduction to the hypothesis that contemporary social behaviorism in its elaborated form provides a basis for future developments of behaviorism and behavior modification. In particular the prínciples, concepts, methods, and analyses involved in the following four areas are outlined, (1) the behavioral .interactíon conception; (2) the tripartite personality repertoire conceptíon (with the analyses and research on the emotíonal-motívational, the language-cognítíve, and instrumental personality systems); (3) the social behavioristíc theory of abnormal behavior; and (4) me social behavioristic conception of behavioral assessment. Each area is seen as a future focus of development of the behavioral movement-ín fact elaboratíons of these elements have already begun-and some of the reseach and theory projectíons involved are outlined, Finally, social behaviorism is seen to províde a basis for rapprochement with central aspects of traditional psychology
Narrative Research from Inside and Outside
Arthur W. Frank
The Canadian Journal of Sociology , 2008,
Abstract:
Patterns of Compact Cardinals
Arthur W. Apter
Mathematics , 1999,
Abstract: We show relative to strong hypotheses that patterns of compact cardinals in the universe, where a compact cardinal is one which is either strongly compact or supercompact, can be virtually arbitrary. Specifically, we prove if V is a model of ``ZFC + Omega is the least inaccessible limit of measurable limits of supercompact cardinals + f :Omega-->2 is a function'', then there is a partial ordering P in V so that for Vbar = V^P, Vbar_Omega models ``ZFC + There is a proper class of compact cardinals + If f(alpha) = 0, then the alpha-th compact cardinal isn't supercompact + If f(alpha) = 1, then the alpha-th compact cardinal is supercompact''. We then prove a generalized version of this theorem assuming kappa is a supercompact limit of supercompact cardinals and f:kappa-->2 is a function, and we derive as corollaries of the generalized version of the theorem the consistency of the least measurable limit of supercompact cardinals being the same as the least measurable limit of non-supercompact strongly compact cardinals and the consistency of the least supercompact cardinal being a limit of strongly compact cardinals.
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