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Pedro Gonnet

Publications and source records attributed to Pedro Gonnet.

3 recordsLinked to original sources

A simple algorithm to accelerate the computation of non-bonded interactions in cell-based molecular dynamics simulations.

Cell lists are ubiquitous in molecular dynamics simulations--be it for the direct computation of short-range inter-atomic potentials, the short-range direct part of a long-range interaction or for the periodic construction of Verlet lists. The conventional approach to computing pairwise interactions using cell lists leads to a large number of unnecessary interparticle distance calculations. In this paper, an algorithm is presented which reduces the number of spurious distance calculations by first sorting the particles along the cell pair axis and then only interacting two particles if their distance along the axis is smaller than the cutoff distance of the interaction. This approach is shown to be more efficient than the conventional approach and similar approaches using smaller cells.

Journal Article↗

Fine-tuning the prediction of sequences cleaved by signal peptidase II: a curated set of proven and predicted lipoproteins of Escherichia coli K-12.

A curated set of 81 proven and 44 predicted lipoproteins of Escherichia coli K-12 was defined with the combined use of a literature survey, a variety of predictive tools and human expertise. The well-documented Gram-negative proteome of E. coli K-12 was chosen to assess how the different approaches complement each other and to ensure a stable definition of a consistent set of lipoproteins. The results of detailed analysis of such proteins at the level of a single proteome are presented, corroborated and rationalized.

Amino Acid Motifs↗

Probabilistic alignment of motifs with sequences.

MOTIVATION: Motif detection is an important component of the classification and annotation of protein sequences. A method for aligning motifs with an amino acid sequence is introduced. The motifs can be described by the secondary (i.e. functional, biophysical, etc.) characteristics of a signal or pattern to be detected. The results produced are based on the statistical relevance of the alignment. The method was targeted to avoid the problems (i.e. over-fitting, biological interpretation and mathematical soundness) encountered in other methods currently available. RESULTS: The method was tested on lipoprotein signals in B. subtilis yielding stable results. The results of signal prediction were consistent with other methods where literature was available. AVAILABILITY: An implementation of the motif alignment, refining and bootstrapping is available for public use online at http://www.expasy.org/tools/patoseq/

Amino Acid Motifs↗