Peter Brown

Bio: Peter Brown is an academic researcher from University of Oxford. The author has contributed to research in topics: Subthalamic nucleus & Deep brain stimulation. The author has an hindex of 129, co-authored 908 publications receiving 68853 citations. Previous affiliations of Peter Brown include Queen's University & Western General Hospital.

SUNDIALS: Suite of nonlinear and differential/algebraic equation solvers

Abstract: SUNDIALS is a suite of advanced computational codes for solving large-scale problems that can be modeled as a system of nonlinear algebraic equations, or as initial-value problems in ordinary differential or differential-algebraic equations. The basic versions of these codes are called KINSOL, CVODE, and IDA, respectively. The codes are written in ANSI standard C and are suitable for either serial or parallel machine environments. Common and notable features of these codes include inexact Newton-Krylov methods for solving large-scale nonlinear systems; linear multistep methods for time-dependent problems; a highly modular structure to allow incorporation of different preconditioning and/or linear solver methods; and clear interfaces allowing for users to provide their own data structures underneath the solvers. We describe the current capabilities of the codes, along with some of the algorithms and heuristics used to achieve efficiency and robustness. We also describe how the codes stem from previous and widely used Fortran 77 solvers, and how the codes have been augmented with forward and adjoint methods for carrying out first-order sensitivity analysis with respect to model parameters or initial conditions.

Fatty acids and eicosanoids regulate gene expression through direct interactions with peroxisome proliferator-activated receptors α and γ

Abstract: Peroxisome proliferator-activated receptors (PPARs) alpha and gamma are key regulators of lipid homeostasis and are activated by a structurally diverse group of compounds including fatty acids, eicosanoids, and hypolipidemic drugs such as fibrates and thiazolidinediones. While thiazolidinediones and 15-deoxy-Delta12, 14-prostaglandin J2 have been shown to bind to PPARgamma, it has remained unclear whether other activators mediate their effects through direct interactions with the PPARs or via indirect mechanisms. Here, we describe a novel fibrate, designated GW2331, that is a high-affinity ligand for both PPARalpha and PPARgamma. Using GW2331 as a radioligand in competition binding assays, we show that certain mono- and polyunsaturated fatty acids bind directly to PPARalpha and PPARgamma at physiological concentrations, and that the eicosanoids 8(S)-hydroxyeicosatetraenoic acid and 15-deoxy-Delta12,14-prostaglandin J2 can function as subtype-selective ligands for PPARalpha and PPARgamma, respectively. These data provide evidence that PPARs serve as physiological sensors of lipid levels and suggest a molecular mechanism whereby dietary fatty acids can modulate lipid homeostasis.

VODE: a variable-coefficient ODE solver

Abstract: VODE is a new initial value ODE solver for stiff and nonstiff systems. It uses variable-coefficient Adams-Moulton and Backward Differentiation Formula (BDF) methods in Nordsieck form, as taken from the older solvers EPISODE and EPISODEB, treating the Jacobian as full or banded. Unlike the older codes, VODE has a highly flexible user interface that is nearly identical to that of the ODEPACK solver LSODE.In the process, several algorithmic improvements have been made in VODE, aside from the new user interface. First, a change in stepsize and/or order that is decided upon at the end of one successful step is not implemented until the start of the next step, so that interpolations performed between steps use the more correct data. Second, a new algorithm for setting the initial stepsize has been included, which iterates briefly to estimate the required second derivative vector. Efficiency is often greatly enhanced by an added algorithm for saving and reusing the Jacobian matrix J, as it occurs in the Newton m...

Iterative Methods for Sparse Linear Systems

Abstract: Preface 1. Background in linear algebra 2. Discretization of partial differential equations 3. Sparse matrices 4. Basic iterative methods 5. Projection methods 6. Krylov subspace methods Part I 7. Krylov subspace methods Part II 8. Methods related to the normal equations 9. Preconditioned iterations 10. Preconditioning techniques 11. Parallel implementations 12. Parallel preconditioners 13. Multigrid methods 14. Domain decomposition methods Bibliography Index.

Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy.

Abstract: Unlike other methods for docking ligands to the rigid 3D structure of a known protein receptor, Glide approximates a complete systematic search of the conformational, orientational, and positional space of the docked ligand In this search, an initial rough positioning and scoring phase that dramatically narrows the search space is followed by torsionally flexible energy optimization on an OPLS-AA nonbonded potential grid for a few hundred surviving candidate poses The very best candidates are further refined via a Monte Carlo sampling of pose conformation; in some cases, this is crucial to obtaining an accurate docked pose Selection of the best docked pose uses a model energy function that combines empirical and force-field-based terms Docking accuracy is assessed by redocking ligands from 282 cocrystallized PDB complexes starting from conformationally optimized ligand geometries that bear no memory of the correctly docked pose Errors in geometry for the top-ranked pose are less than 1 A in nearly ha

Metascape provides a biologist-oriented resource for the analysis of systems-level datasets.

Abstract: A critical component in the interpretation of systems-level studies is the inference of enriched biological pathways and protein complexes contained within OMICs datasets Successful analysis requires the integration of a broad set of current biological databases and the application of a robust analytical pipeline to produce readily interpretable results Metascape is a web-based portal designed to provide a comprehensive gene list annotation and analysis resource for experimental biologists In terms of design features, Metascape combines functional enrichment, interactome analysis, gene annotation, and membership search to leverage over 40 independent knowledgebases within one integrated portal Additionally, it facilitates comparative analyses of datasets across multiple independent and orthogonal experiments Metascape provides a significantly simplified user experience through a one-click Express Analysis interface to generate interpretable outputs Taken together, Metascape is an effective and efficient tool for experimental biologists to comprehensively analyze and interpret OMICs-based studies in the big data era

New functions for the matrix metalloproteinases in cancer progression

Abstract: Matrix metalloproteinases (MMPs) have long been associated with cancer-cell invasion and metastasis. This provided the rationale for clinical trials of MMP inhibitors, unfortunately with disappointing results. We now know, however, that the MMPs have functions other than promotion of invasion, have substrates other than components of the extracellular matrix, and that they function before invasion in the development of cancer. With this knowledge in hand, can we rethink the use of MMP inhibitors in the clinic?

Glide: a new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening.

Abstract: Glide's ability to identify active compounds in a database screen is characterized by applying Glide to a diverse set of nine protein receptors. In many cases, two, or even three, protein sites are employed to probe the sensitivity of the results to the site geometry. To make the database screens as realistic as possible, the screens use sets of “druglike” decoy ligands that have been selected to be representative of what we believe is likely to be found in the compound collection of a pharmaceutical or biotechnology company. Results are presented for releases 1.8, 2.0, and 2.5 of Glide. The comparisons show that average measures for both “early” and “global” enrichment for Glide 2.5 are 3 times higher than for Glide 1.8 and more than 2 times higher than for Glide 2.0 because of better results for the least well-handled screens. This improvement in enrichment stems largely from the better balance of the more widely parametrized GlideScore 2.5 function and the inclusion of terms that penalize ligand−protei...