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Nicolas Wicker

Publications and source records attributed to Nicolas Wicker.

2 recordsLinked to original sources

PipeAlign: A new toolkit for protein family analysis.

PipeAlign is a protein family analysis tool integrating a five step process ranging from the search for sequence homologues in protein and 3D structure databases to the definition of the hierarchical relationships within and between subfamilies. The complete, automatic pipeline takes a single sequence or a set of sequences as input and constructs a high-quality, validated MACS (multiple alignment of complete sequences) in which sequences are clustered into potential functional subgroups. For the more experienced user, the PipeAlign server also provides numerous options to run only a part of the analysis, with the possibility to modify the default parameters of each software module. For example, the user can choose to enter an existing multiple sequence alignment for refinement, validation and subsequent clustering of the sequences. The aim is to provide an interactive workbench for the validation, integration and presentation of a protein family, not only at the sequence level, but also at the structural and functional levels. PipeAlign is available at http://igbmc.u-strasbg.fr/PipeAlign/.

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Density of points clustering, application to transcriptomic data analysis.

With the increasing amount of data produced by high-throughput technologies in many fields of science, clustering has become an integral step in exploratory data analysis in order to group similar elements into classes. However, many clustering algorithms can only work properly if aided by human expertise. For example, one parameter which is crucial and often manually set is the number of clusters present in the analyzed set. We present a novel stopping rule to find the optimal number of clusters based on the comparison of the density of points inside the clusters and between them. The method is evaluated on synthetic as well as on real transcriptomic data and compared with two current methods. Finally, we illustrate its usefulness in the analysis of the expression profiles of promyelocytic cells before and after treatment with all-trans retinoic acid. Simultaneous clustering for gene regulation and absolute initial expression levels allowed the identification of numerous genes associated with signal transduction revealing the complexity of retinoic acid signaling.

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