Applied Research Systems Ars Holding N.v.

Merck Serono S. a.

Laboratoires Serono S.a.

Geneva Bioinformatics (Genebio), S.a.

Jacques Colinge

Christine Power

Christine Plater-Zyberk

Georg Feger

Rob Hooft Van Huijsduijnen

Alexandre Masselot

The invention relates to the use of SARP-1 for the preparation of a medicament for the treatment and/or prevention of scleroderma, in particular of systemic sclerosis.

Method for treating liver cirrhosis or interstitial pulmonary fibrosis

The present invention relates to a system and method for scoring peptide matches. Embodiments of the present invention improves identification of peptides and proteins by introducing an appropriate signal detection based scoring system and what is believed to be the new concept of an extended match. To score a match between a first peptide and a second peptide, a stochastic model may be generated based on one or more match characteristics associated with the first peptide, the second peptide and their fragments. A first probability that the first peptide matches the second peptide, and second probability that the first peptide does not match the second peptide, may be calculated based on the stochastic model. And a match between the first peptide and the second peptide may be scored based at least in part on a ratio between the first probability and the second probability.

System and method for scoring peptide matches

Use of SARP-1 for the treatment and/or prevention of scleroderma

A method for identification of gene transcripts comprises the steps of: generating a set of raw sequences by sequencing of biological material; isolating ditags from the set of raw sequences; isolating tags from the ditags; determining abundance of the tags; and identifying the tags, the method providing a step of reducing the amount of sequencing errors by using a statistical model for sequencing errors.

Method for the identification of gene transcripts with improved efficiency in the treatment of errors

The invention relate to an automated method for identifying related biomolecular sequences having defined features of interest from databases, the databases comprising at least a first and a second set of sequences, each set being derived from a different type of organism, comprising the steps of: a) establishing from the first set of sequences a non-redundant list of query sequences having the defined features of interest (first family members), using a database search program; b) performing sequence alignments with the first family members in a second set of sequences derived from a second type of organism, using a database search program and a preset similarity threshold, giving a list of second family members: c) establishing a two dimensional matrix displaying the first and second family members and their respective similarity values resulting from step (b), optionally displaying only those second family members having similarity values exceeding a preset threshold value; d) selecting from the matrix those pairs of first and second family members for which the similarity values are the best among all of the alignments that involve one of the two pair's members (orthologs).

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Neydens, France

Jacques Colinge