Computer science

Languages: C++, C, bash scripts,Fortran, Html*/Css*
Additional languages tools: Git, GitHub/GitLab
Softwares: R, Mathematica, Labview, Octave/Matlab
Office tools: LaTeX, Beamer, Geany, Sublime Text, Scribus (PAO), OpenOffice and Microsoft office
Visualisation tools: GIMP, Inkscape, gnuplot
Systems: Linux (Ubuntu), Windows.

online certificates: OpenClassRoom*, End-to-End Machine Learning**, Courera***

Polymer physic Modelling

Kinetic Monte-Carlo simulation: Coarse-grained model to numerically tackled the out-of-equilibrium dynamics and properties of DNA polymer. Combining this numerical simulation (based on Worm Like Chain formalism) with HT-TPM experiments and theories (local bend or local flexible hinge WLC models, classical Odjik–Skolnick–Fixman theories, Manning's counterion condensation and Manning’s electrostatic stretching approaches) allow one to rigorously measure and extraction the effects of local or global effects on DNA molecule properties.

BioMolecular techniques

Tethered particle motion (TPM): allow ones to follow the Brownian motion of single DNA molecules, grafted by one end at a substrate and by the other end to a labelled nanoparticle.
BioMolecular quantification techniques: DLS, Zetasizer, UV spectroscopy, quantification PCR.

High-throughput/Big Data analyses pipeline

TPM analysis: High Throughput Tethered Particle Motion (ht-TPM) technique enables the tracking of the conformational changes and dynamics of hundreds of single DNA molecules in parallel, free to fluctuate in solution. Ht-TPM experiment is combine with a software to tracks in real time the positions of all the particles using the centroid method (Nanomultiplex). After this first step of criterion of validity are applied (access to the anchoring point, checking symmetry factor, ...), additional correction and analysis are done by using a home-built Mathematica scripts (correction of asymmetry factor, extrapolation of correlation functions, remove artifact/malformed DNA-nanoparticle complexes, correction of time averaging effect, calculation of the 3D motion componant).

RNASeq analysis: this high-throughput sequencing method allow one to examine and quantity the transcriptome of gene expression patterns encoded within the RNA of a biological sample at a given moment. Reads (small sequence data) are align with no mismatch and map against the reference genome (TopHat, Bowtie/2). Then, the transcripts abundance (all the gene readouts) is determined (cufflinks). Finally, gene that are deferentially regulate at transcriptional or post-transcriptional level are estimated (cuffdiff).

ChIPSeq analysis: this genome-wide methode allow one to identify enrichment in DNA-protein interactions, such as lamins proteins, transcriptional factors or histones marks modifications along the genome of a biological sample at a given moment. Reads from samples and input (representative distribution of the total DNA material) are align and map against the reference genome (Bowtie/2), and both are down-sampling in order to get the same read depth avoiding normalization bias. Finally, reads are used to call peak or domain (as Lamina-associated domains, LAD) of chormatin sequence bound by the protein of interest (identification of domains could be done by using Enriched Domain Detector (EDD), or MAC peaks or domains caller software).

From raw to highly processed data :

Methodology: Developing a strong computing procedure to extract the physical coherence (symmetry factor, correlation function,...) of gigaoctet of raws data. Quantifying the amplitude of motion of DNA/particles complexes (experimental and computational data) to extract mechanical and physicals properties of DNA. Analyzing large-scale genomic data from high-throughput ChipSeq and RNASeq sequencing (pipeline process , BWT algorithms, peakcaller software) to identify enrichment features (domains genomic regions, cluster of genes, ..).

Statistical analysis: Developing and adapting regular statistical tools, extracting and quantifying specific pattern of gene expression level in a circadian system (mice) or cell differentiation context. Investigating the dynamic of lamina-associated domains behavior and 3D configuration across circadian rhythm or cell differentiation.

Visualization techniques

Microscopy techniques: Scanning Tunneling Microscopy, Scanning Electron Microscopy, fluorescence and dark field microscopy.
Microscopy data analysis: ImageJ
Data visualization: PyMOL, Chimera, IGV

Surface treatment process

Chemical & physical treatments: epoxydation, thiolisation, piranha, Plasma cleaner, UV ozone
Drop off methods: Spin coating, convective self-assembly

Management and administrative skills

Leadership: Project management and leadership skills developed by planning and executing multiple projects and collaborations simultaneously. Project leader of computational genome modeling work in CollasLab. Supervision and co-supervisions of phD students and interships students. Leading and developing international collaborations through networking and conferences.
Administrative management: Establishment of feasible and original project integrated through grant and fellowship writing, including budget establishment.
Communication: Dissemination of results and reporting activity to the interdisciplinary scientific community by writing and publishing of scientific articles, oral communications or posters. Layman's terms scientific conferences.


English: proficient,TOIEC score 775 in 2014
Norsk: beginner
Deutsch: basic