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David S. Moss

dblp:55/5892 · DBLP profile ↗
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8ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 8 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
3 papers
Bioinformatics and computational biology · 100%
Software engineering, system software, and programming languages
1 paper
Programming languages and type systems · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › transcriptomics
RNA-seq analysis
0.512021
flexiMAP: a regression-based method for discovering differential alternative polyadenylation events in standard RNA-seq data · Bioinform. 2021
Programming languages and type systems › programming paradigms
generic programming
0.012001
The Bioinformatics Template Library-generic components for biocomputing · Bioinform. 2001

Methods — techniques the papers use, named apart from their topics

beta regression · 0.5sequence analysis · 0.1predictive modeling · 0.1c++ template library · 0.1
YearPublicationVenuePosition
2021 flexiMAP: a regression-based method for discovering differential alternative polyadenylation events in standard RNA-seq data
abstract
MOTIVATION: We present flexible Modeling of Alternative PolyAdenylation (flexiMAP), a new beta-regression-based method implemented in R, for discovering differential alternative polyadenylation events in standard RNA-seq data. RESULTS: We show, using both simulated and real data, that flexiMAP exhibits a good balance between specificity and sensitivity and compares favourably to existing methods, especially at low fold changes. In addition, the tests on simulated data reveal some hitherto unrecognized caveats of existing methods. Importantly, flexiMAP allows modeling of multiple known covariates that often confound the results of RNA-seq data analysis. AVAILABILITY AND IMPLEMENTATION: The flexiMAP R package is available at: https://github.com/kszkop/flexiMAP. Scripts and data to reproduce the analysis in this paper are available at: https://doi.org/10.5281/zenodo.3689788. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Krzysztof J. Szkop, David S. Moss, Irene Nobeli
Bioinform.2
2020 Flexibility and intrinsic disorder are conserved features of hepatitis C virus E2 glycoprotein
abstract
The glycoproteins of hepatitis C virus, E1E2, are unlike any other viral fusion machinery yet described, and are the current focus of immunogen design in HCV vaccine development; thus, making E1E2 both scientifically and medically important.We used pre-existing, but fragmentary, structures to model a complete ectodomain of the major glycoprotein E2 from three strains of HCV.We then performed molecular dynamic simulations to explore the conformational landscape of E2, revealing a number of important features.Despite high sequence divergence, and subtle differences in the models, E2 from different strains behave similarly, possessing a stable core flanked by highly flexible regions, some of which perform essential functions such as receptor binding.Comparison with sequence data suggest that this consistent behaviour is conferred by a network of conserved residues that act as hinge and anchor points throughout E2.The variable regions (HVR-1, HVR-2 and VR-3) exhibit particularly high flexibility, and bioinformatic analysis suggests that HVR-1 is a putative intrinsically disordered protein region.Dynamic cross-correlation analyses demonstrate intramolecular communication and suggest that specific regions, such as HVR-1, can exert influence throughout E2.To support our computational approach we performed small-angle X-ray scattering with purified E2 ectodomain; this data was consistent with our MD experiments, suggesting a compact globular core with peripheral flexible regions.This work captures the dynamic behaviour of E2 and has direct relevance to the interaction of HCV with cell-surface receptors and neutralising antibodies. Author summaryHepatitis C virus (HCV) is a globally important pathogen for which no vaccine is available.E2 is a protein found on the surface of HCV particles; it mediates interaction of HCV with cells and is a target for the human immune response.Current evidence suggests that antibodies targeting E2 are able to clear HCV infection, therefore, E2 is being pursued as a candidate vaccine.In this study we have built structural models of E2 from different strains of HCV and performed computational simulation to investigate how the E2 molecule moves.We have discovered that E2 possesses highly mobile regions; we propose that
Lenka Stejskal, William D. Lees, David S. Moss, Machaela Palor, Richard J. Bingham, Adrian J. Shepherd, Joe Grove
PLoS Comput. Biol.3
2012 Visualisation of variable binding pockets on protein surfaces by probabilistic analysis of related structure sets
abstract
BACKGROUND: Protein structures provide a valuable resource for rational drug design. For a protein with no known ligand, computational tools can predict surface pockets that are of suitable size and shape to accommodate a complementary small-molecule drug. However, pocket prediction against single static structures may miss features of pockets that arise from proteins' dynamic behaviour. In particular, ligand-binding conformations can be observed as transiently populated states of the apo protein, so it is possible to gain insight into ligand-bound forms by considering conformational variation in apo proteins. This variation can be explored by considering sets of related structures: computationally generated conformers, solution NMR ensembles, multiple crystal structures, homologues or homology models. It is non-trivial to compare pockets, either from different programs or across sets of structures. For a single structure, difficulties arise in defining particular pocket's boundaries. For a set of conformationally distinct structures the challenge is how to make reasonable comparisons between them given that a perfect structural alignment is not possible. RESULTS: We have developed a computational method, Provar, that provides a consistent representation of predicted binding pockets across sets of related protein structures. The outputs are probabilities that each atom or residue of the protein borders a predicted pocket. These probabilities can be readily visualised on a protein using existing molecular graphics software. We show how Provar simplifies comparison of the outputs of different pocket prediction algorithms, of pockets across multiple simulated conformations and between homologous structures. We demonstrate the benefits of use of multiple structures for protein-ligand and protein-protein interface analysis on a set of complexes and consider three case studies in detail: i) analysis of a kinase superfamily highlights the conserved occurrence of surface pockets at the active and regulatory sites; ii) a simulated ensemble of unliganded Bcl2 structures reveals extensions of a known ligand-binding pocket not apparent in the apo crystal structure; iii) visualisations of interleukin-2 and its homologues highlight conserved pockets at the known receptor interfaces and regions whose conformation is known to change on inhibitor binding. CONCLUSIONS: Through post-processing of the output of a variety of pocket prediction software, Provar provides a flexible approach to the analysis and visualization of the persistence or variability of pockets in sets of related protein structures.
Paul Ashford, David S. Moss, Alexander Alex, Siew K. Yeap, Alice Povia, Irene Nobeli
BMC Bioinform.2
2010 A computational analysis of the antigenic properties of haemagglutinin in influenza A H3N2
abstract
MOTIVATION: Modelling antigenic shift in influenza A H3N2 can help to predict the efficiency of vaccines. The virus is known to exhibit sudden jumps in antigenic distance, and prediction of such novel strains from amino acid sequence differences remains a challenge. RESULTS: From analysis of 6624 amino acid sequences of wild-type H3, we propose updates to the frequently referenced list of 131 amino acids located at or near the five identified antibody binding regions in haemagglutinin (HA). We introduce a class of predictive models based on the analysis of amino acid changes in these binding regions, and extend the principle to changes in HA1 as a whole by dividing the molecule into regional bands. Our results show that a range of simple models based on banded changes give better predictive performance than models based on the established five canonical regions and can identify a higher proportion of vaccine escape candidates among novel strains than a current state-of-the-art model.
William D. Lees, David S. Moss, Adrian J. Shepherd
Bioinform.2
2009 ImmunoGrid, an integrative environment for large-scale simulation of the immune system for vaccine discovery, design and optimization
abstract
Vaccine research is a combinatorial science requiring computational analysis of vaccine components, formulations and optimization. We have developed a framework that combines computational tools for the study of immune function and vaccine development. This framework, named ImmunoGrid combines conceptual models of the immune system, models of antigen processing and presentation, system-level models of the immune system, Grid computing, and database technology to facilitate discovery, formulation and optimization of vaccines. ImmunoGrid modules share common conceptual models and ontologies. The ImmunoGrid portal offers access to educational simulators where previously defined cases can be displayed, and to research simulators that allow the development of new, or tuning of existing, computational models. The portal is accessible at .
Francesco Pappalardo 0001, Mark D. Halling-Brown, Nicolas Rapin, Ping Zhang 0008, Davide Alemani, Andrew P. J. Emerson, Paola Paci, Patrice Duroux, Marzio Pennisi, Arianna Palladini, Olivo Miotto, Daniel Churchill, Elda Rossi, Adrian J. Shepherd, David S. Moss, Filippo Castiglione, Massimo Bernaschi, Marie-Paule Lefranc, Søren Brunak, Santo Motta, Pierluigi Lollini, Kaye E. Basford, Vladimir Brusic
Briefings Bioinform.15
2008 Towards a lightweight generic computational grid framework for biological research
abstract
BACKGROUND: An increasing number of scientific research projects require access to large-scale computational resources. This is particularly true in the biological field, whether to facilitate the analysis of large high-throughput data sets, or to perform large numbers of complex simulations - a characteristic of the emerging field of systems biology. RESULTS: In this paper we present a lightweight generic framework for combining disparate computational resources at multiple sites (ranging from local computers and clusters to established national Grid services). A detailed guide describing how to set up the framework is available from the following URL: http://igrid-ext.cryst.bbk.ac.uk/portal_guide/. CONCLUSION: This approach is particularly (but not exclusively) appropriate for large-scale biology projects with multiple collaborators working at different national or international sites. The framework is relatively easy to set up, hides the complexity of Grid middleware from the user, and provides access to resources through a single, uniform interface. It has been developed as part of the European ImmunoGrid project.
Mark D. Halling-Brown, David S. Moss, Adrian J. Shepherd
BMC Bioinform.2
2001 The Bioinformatics Template Library-generic components for biocomputing
abstract
Abstract Motivation: The efficiency of bioinformatics programmers can be greatly increased through the provision of ready-made software components that can be rapidly combined, with additional bespoke components where necessary, to create finished programs. The new standard for C++ includes an efficient and easy to use library of generic algorithms and data-structures, designed to facilitate low-level component programming. The extension of this library to include functionality that is specifically useful in compute-intensive tasks in bioinformatics and molecular modelling could provide an effective standard for the design of reusable software components within the biocomputing community. Results: A novel application of generic programming techniques in the form of a library of C++ components called the Bioinformatics Template Library (BTL) is presented. This library will facilitate the rapid development of efficient programs by providing efficient code for many algorithms and data-structures that are commonly used in biocomputing, in a generic form that allows them to be flexibly combined with application specific object-oriented class libraries. Availability: The BTL is available free of charge from our web site http://www.cryst.bbk.ac.uk/~classlib/ and the EMBL file server http://www.embl-ebi.ac.uk/FTP/index.html Contact: [email protected]; [email protected] * To whom correspondence should be addressed. 3 Present address: Celltech Chiroscience, Granta Park, Great Abingdon, Cambridge CB1 6GS, UK. 4 Present address: Department of Biochemistry & Molecular Biology, University College London, Gower Street, London WC1E 6BT, UK.
William R. Pitt, M. Steven, B. Sweeney, Alan J. Bleasby, David S. Moss
Bioinform.6
2000 Information Resources for the Bioinformatician
abstract
The collaborative computing project in biosequence and structure analysis (CCPII) was established to foster bioinformatics in the broad community and the UK research community in particular. A World-Wide Web site called 'The Bioinformatics Resource' has been created containing a comprehensive set of information resources of use to the bioinformatician. The activities of CCPII are complementary to other providers of molecular biology information such as the BIOSCI electronic communication forum, which was established to facilitate communication between professionals in the biological sciences.
Jon C. Ison, Sinead B. O'Leary, Alan J. Bleasby, David S. Moss
Briefings Bioinform.4