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Geraldine Jean, Ph.D.
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Geraldine Jean, Ph.D.

  • Postdoc (Alumna)

Biography:

I hold my Ph.D. degree in Computer Science from the University of Bordeaux 1 (France) received in December 2008. My thesis on In silico methods for genome rearrangement analysis: from identification of common markers to ancestral reconstruction can be downloaded here. I am now postdoc in the Machine Learning in Genome Biology group at the Friedrich Miescher Laboratory in Tübingen.

During my Ph.D., I was mainly interested in the definition of mathematic models describing genome at gene scale and in the development of algorithmic and combinatoric methods based on the study of genome rearrangements for the comparison of genomes. I am now working on the development of algorithms for spliced alignments of short reads from NGS technologies.

Please check out my personal webpage for previous publications and teaching details.

Publications:

A list of publications can be found there.

Education:

2009-Now:

Postdoctoral position at the FML

2005-2008:
Ph.D. in Computer Science at the LaBRI, University of Bordeaux 1 - Talence, France
Thesis: "In silico methods for genome rearrangement analysis: from identification of common markers to ancestral reconstruction"
Advisers: Pr. Serge Dulucq and Dr. Macha Nikolski
2003-2005:
M.Sc. in Computer Science (Models and Algorithms) at the University of Bordeaux 1 - Talence, France
M.Sc. thesis: "Genomic rearrangements: state of the art and constrained reversal distance"
Adviser: Pr. Serge Dulucq
2000-2003:

B.S. in Computer Science at the Faculty of Sciences and Techniques of Nantes - Nantes, France

Professional experience:

2008-2009:
Assistant Professor in Computer Science
at the ENSEIRB-MATMECA, Engineer School of Computer Science - France
2005-2008:
Teaching assistant in Computer Science
at the ENSEIRB MATMECA, Engineer School of Computer Science - France

Research Interests:

Spliced Alignments for ESTs, cDNAs, and Next-Generation Sequencing Reads:
I am currently working on the development of PALMapper, a spliced alignment tool for short reads. The first goal was to improve the running time by combining QPALMA with GenomeMapper and by refining the dynamic programming algorithm for spliced alignments in order to efficiently deal with the large amount of data provided by NGS technologies.