Hugues Richard
36 years old, French, married
Lab. Computational & Quantitative Biology, UPMC
15 rue de l’Ecole de Médecine 75006 Paris
[email protected]
Work : +33-(0)-1-4427-7347
http://www.lcqb.upmc.fr/hrichard
Working Experience
Since 2009
2006-2009
2001-2006
Assistant Professor in Statistics and Computational Biology,
Analytical Genomics team, Lab. of Computational and Quantitative Biology, UMR7238
University Pierre & Marie Curie - Sorbonne Universités, Paris.
Post-doctoral Fellowship, Computational Molecular Biology Dept
Max Planck Institute for Molecular Genetic, Berlin.
Tutor (01-04) and Lecturer (04-06) in Statistics and Bioinformatics
Statistic & Genomes Laboratory, University Evry Val d’Essonne.
Education
2001-2005
2000-2001
Ph. D., Computational Biology - Prediction of the Subcellular Localization of Proteins
by their Biological Sequences
Supervisors B. Prum and F. Képès - University Evry Val d’Essonne - France.
Master’s Degree in Mathematics: Analysis and Stochastic Processes
Marne-la-Vallée University - France, with recognition.
Awards
2010-2012
2012
Fall 2011
2006-2009
Leave of teaching (délégation CNRS)
Laboratory Génomique des microorganismes (UMR 7238)
Japan Society for the Promotion of Science (6 months)
Computational Biology Research Center, Tokyo, Japan. Hosted by M. Frith.
IPAM long research program (3 months)
Mathematical and Computational Approaches in High-Throughput Genomics,
Institute for Pure and Applied Mathematics, UCLA, USA.
Max Planck post-doctoral fellowship.
Next Generation Sequencing data analysis
Genomics
Fiona, automatic read error correction for genome sequencing experiments
D. Weese, M. Holtgrewe, ABI, Berlin and M. Schulz, MPI for Informatics, Saarbrucken
Split alignement for the analysis of Structural Variants in Cancer cells
Anish MS Shrestha, Tokyo University, and M. Frith, CBRC, Tokyo
Exome sequencing for the genetic mapping of mental retardation
Human Molecular Genetics Dept., MPI for Molecular Genetics, Berlin
RNA-Seq
Analysis of small RNAs in the diatom Phaeodactylum Tricornutum
A. Falciatore, LGM, Paris and A. Rogato, Stazione Dohm, Naples
Parseq, A tool for the reconstruction of the transcriptional landscape
P. Nicolas, INRA, Jouy-en-Josas.
FANTOM5 Bioinformaticist Collaborator,
Riken OSC, Yokohama, Japan
Alternative Splicing Events in the Zebrafinch forebrain’s transcriptome
C. Scharff and I. Adam, Behavioral Biology Department, Free University, Berlin
Native tongue,
Hugues Richard
Fluent,
Advanced,
Intermediate
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Research Areas:
• Statistical methods for high-throughput sequencing data:
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RNA-Seq and transcriptome analysis [4, 6, 5, 7, 8, 9, 11], ,
Non Coding RNA and gene model annotation [2, 8]
sequence alignment, detection of gene fusion or genomic variation [1, 10].
Automatic correction of sequencing errors [3].
• Word statistics and Markov chains, Hidden Markov Models [12, 13, 14, 15]
• Classification, Protein annotation [22,23]
Software development:
• 5 software tools [3, 1, 4, 6, 8] and 2 web services [13, 14]
• 1 processing pipeline [10], 2 librairies (R and C++) [9, 12].
References
[1] Gillet-Markowska, A., Richard, H., Fischer, G., and Lafontaine, I. Ulysse: Accurate detection of structural
variations from large insert mate-pair next generation sequencing. In revision.
[2] Rogato*, A., Richard*, H., Voss, B., Sarazin, A., Navarro, S. C., Navarro, L., Carbone, A., Hess, W. R.,
and Falciatore, A. (In press) The diversity of small non coding rna populations in the diatom phaeodactylum
tricornotum. BMC Genomics.
[3] Schulz*, M. H., Weese*, D., Holtgrewe*, M., Dimitrova, V., Niu, S., Reinert, K., and Richard, H. (In
press) Fiona: a parallel and automatic strategy for read error correction. Bioinformatics.
[4] Mirauta, B., Nicolas*, P., and Richard*, H. (2014) Parseq: reconstruction of microbial transcription
landscape from rna-seq read counts using state-space models. Bioinformatics, 30, 1409–1416.
[5] Steijger, T., Abril, J., Engstr, Kokocinski, F., The RGASP Consortium: 58 authors including Richard H.,
Hubbard, T., Guigo, Harrow, J., and Bertone, P. (2013) Assessment of transcript reconstruction methods
for RNA-seq. Nat. Methods, 10, 1177–1184.
[6] Mirauta, B., Nicolas*, P., and Richard*, H. (2013) Pardiff: Inference of differential expression at basepair level from rna-seq experiments. Petrosino, A., Maddalena, L., and Pala, P. (eds.), ICIAP International
Workshops, Naples, Italy, September 9-13, 2013. Proceedings, vol. 8158 of Lecture Notes in Computer
Science, pp. 418–427, Springer.
[7] Mäder, U., Nicolas, P., Richard, H., Bessières, P., and Aymerich, S. (2011) Comprehensive identification
and quantification of microbial transcriptomes by genome-wide unbiased methods. Current Opinion in
Biotechnology, 22, 32 – 41, 16 citations (ISI base of knowledge).
[8] Warren*, W. C., Clayton*, D. F., Ellegren*, H., Arnold*, A. P., ... (65 authors), Richard, H., ... (12
authors), and Wilson, R. K. (2010) The genome of a songbird. Nature, 464, 757–762.
[9] Richard*, H., et al. (2010) Prediction of alternative isoforms from exon expression levels in rna-seq experiments. Nucleic Acids Research, 55 citations (ISI base of knowledge).
[10] Hu, H., et al. (2010) Mutation screening in 86 known X-linked mental retardation genes by droplet-based
multiplex PCR and massive parallel sequencing. The HUGO Journal.
[11] Sultan*, M., Schulz*, M. H., Richard*, H., Magen, A., Klingenhoff, A., ... (7 authors), Haas, S., Vingron,
M., Lehrach, H., and Yaspo, M.-L. (2008) A global view of gene activity and alternative splicing by deep
sequencing of the human transcriptome. Science, 321, 956–960, 525 citations (ISI base of knowledge).
[12] Miele, V., Bourguignon, P.-Y., Robelin, D., Nuel, G., and Richard, H. (2005) seq++: analyzing biological
sequences with a range of markov-related models. Bioinformatics, 21, 2783–2784.
[13] Richard, H. and Nuel, G. (2003) SPA: simple web tool to assess statistical significance of dna patterns.
Nucleic Acids Research, 31, 3679–3681.
[14] Robelin, D., Richard, H., and Prum, B. (2003) SIC: a tool to detect short inverted segments in a biological
sequence. Nucleic Acids Research, 31, 3669–3671.
[15] Robin, S., Daudin, J. J., Richard, H., Sagot, M.-F., and Schbath, S. (2002) Occurrence probability of
structured motifs in random sequences. J. of Comp. Biol., 9, 761–773, 26 citations (ISI base of knowledge).
Hugues Richard
2
Invited Presentations
[16] Invited lecture, Analysis of Tumoral genome school, Seine-Port, 12-15 mai 2014 – Methods for the analysis
of Transcriptome Sequencing Data.
[17] Invited speaker, RNA-Seq Europe, 2013, Basel, 3-5 December 2013, http://rnaseq-europe.com/speakers
– Beyond gene expression: estimate expression levels and detect transcript boundaries from RNA-seq read counts.
[18] Invited speaker, 21st International Symposium on Mathematical Programming (ISMP2012), Berlin, 19-24
August 2012 – Fiona: Automatic correction of sequencing errors in genome sequencing experiments.
[19] Keynote speaker, Next Generation Sequencing Workshop, organized by IBBE-CNR and Bari University,
Bari, 6-8 October 2010, http://mi.caspur.it/workshop_NGS10/ – Methods for the analysis of RNA-seq data.
[20] Invited speaker, Workshop on Bioinformatics and High throughput sequencing, organized the ReNaBi
network, Paris, 24 March 2010, http://www.lirmm.fr/~rivals/SHD-2010 – Methods for the analysis of RNAseq data.
Conferences with Proceedings
[21] Mirauta, B., Nicolas, P. Richard, H. A Sequential Monte Carlo method for estimating transcriptional
landscape at base pair level from RNA-Seq data, Journées Ouvertes en Biologie, Informatique et Mathématiques (JOBIM), Institut Pasteur, Paris, 28 June- 1st July 2011.
[22] Richard, H., Mucchielli M., Prum B., Képès F., Hidden Markov Models Hierarchical Classification for AbInitio Prediction of Protein Subcellular Localization, ISMB’05, Detroit, June 2005, PLoS CB poster.
[23] Richard, H., Mucchielli M., Prum B., Képès F. , Discrimination of the subcellular locations of the yeast
proteins by their biological sequence, JOBIM’04, Montréal, june 2004,n 79.
Communications
[24] Richard, H., Weese, D., Holtgrewe, M., Schultz, M. Fiona: A tool for automatic correction of sequencing
errors in genome sequencing experiments, 22nd Annual Workshop on Mathematical and Statistical Aspects of
Molecular Biology, (MASAMB), Berlin, 10-11 avril 2012.
[25] Mirauta, B., Nicolas, P., Richard, H. Sequential Monte Carlo - Particle Gibbs inference of Transcriptional
Landscape from RNA-Seq Data, Mathematical and Statistical Aspects of Molecular Biology (MASAMB), Berlin,
10-11 april 2012
Invited Seminars
Lake Arrowhead, Institute for Pure and Applied Mathematics, Los Angeles, 11.06.2014.
Institute for Cell Biology, UnikKlinik, RWTH, Aachen, 08.04.2014.
Computational Biology Research Center (CBRC), Tokyo, 02.23.2012.
Génoscope, Evry, 03.26.2009.
Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier (LIRMM), Montpellier,
01.27.2009.
• Laboratoire Biométrie et Biologie Evolutive (LBBE), Lyon, 01.22.2009.
• University College Dublin (UCD), Dublin, 11.21.2008.
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Hugues Richard
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Service
• Referee for the international scientific journals: Genome Biology, Nucleic Acids Research, Bioinformatics,
BMC genomics, BMC bioinformatics.
• Organization of of the conference: Statistical Methods for Post-Genomic Data (SMPGD), which aims
at gathering statisticians, computer scientists, and biologists to discuss new statistical methodologies for
the analysis of high throughput biological data (http://smpgd2014.sciencesconf.org/, more than 100
participants)
Students supervision
Graduate students
• (2010- expected Nov. 2014) Shared PhD supervision of Bogdan Mirauta (Ministry of research fellowship),
on the developpment of method estimating transcription rate from RNA-Seq data at the basepair level.
• (2007 to 2010) Shared PhD supervision of M. H Schulz, (International Max Planck research School) on
a method for the detection and quantification of alternative splicing event on RNA-Seq data.
Master Students
• (April-September 2014), joint with E. Laine: A. Ait-Amlat on the phylogenetic reconstruction of transcript
isoforms evolution
• (April-September 2014), M. Bessoul on the enumeration of alternative splicing events
• (February-August 2013), M. Bessoul, on the development of a method for the inference of methylation
levels from bisulfite sequencing experiments.
• (April-September 2010), B. Mirauta presently a PhD student (see above)
• (Since 2010), I also supervised 4 research projects with 1st year master students: Analysis of bisulfite
sequencing data, Correcting sequencing errors by a suffix tree approach, Annotating proteins with variable
order markov chains, Evaluating various segmentation methods for the analysis of transcriptome data.
Teaching
Bioinformatics:
Statistics:
Computer Science:
Hugues Richard
Next generation sequence data analysis
sequence analysis and word statistics.
Microarray/RNA-Seq analysis.
Phylogeny.
Multivariate data analysis and Hypothesis testing.
Classification and Pattern Matching.
Markovian models
Algorithms.
Programming (C & C++).
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Fahie, Leonard Albert (Big Youth)

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