Nicolas Bertin Email & Phone Number

Singapore

By explicitly recognizing the importance of individual and population-level genetic variations and other molecular factors in determining or predicting clinical outcomes, Precision Medicine (PM) promises to transform how we assess disease risk, deliver more accurate diagnoses, and tailor appropriate therapies while minimizing treatment-related side effects. To address the challenge of big data analytics and integrative omics for PM, four institutions have come together to form the Centre for Big Data and Integrative Genomics (c-BIG). As the Programme Manager for c-BIG, Dr. Bertin coordinates efforts and tracks progress across the centre's four partner institutions (GIS, BII, IHPC, I2R), oversees the deployment of the multi-institutional centre’s data acquisition, storage, and analytic capacities for large-scale clinical and research omics, and drives industry collaborations related to c-BIG infrastructure.

Singapore

My role in HLI pertained to the development of components of HLI’s Knowledgebase (HLI-KB) and clinical reporting products. Notably, a genome browser enabling the visualisation of NGS data at scales spanning several orders of magnitude (single base to whole-chromosome & single individuals to cohorts of 1,000s). I was also in charge of the continuous development of ETLs and analytics supporting the HLI-KB, including a highly-scalable cloud-based clinical and functional annotations pipeline for the interpretation of very large-scale (30,000+ individuals) whole-genome (WGS) and whole-exome (WES) inferred germline and somatic mutations in individuals and across cohorts.⇨ Key Accomplishments • Delivered key components of HLI-KB and clinical reporting (metabolome, WES and WGS) products. • Re-engineered HLI-KB’s GWAS-based genetic and disease risks modelling computation within Spark on Kubernetes infrastructure, decreasing computation time from days to hours. • Coordinated the development of Yandex/ClickHouse OLAP DSL functionalities for real time browsing of both whole-genome (600M+ variants) and cohort scales (30k+ samples) germline and somatic mutations. • Streamlined data acquisition and integrative analysis of patients’ metabolome data.

Singapore

After a PhD thesis largely influenced by the advent of network biology, a postdoc where non-coding transcription has been front seat, during which I designed computational approaches fostering the development and exploitation of novel functional genomic technologies, I quite naturally got attracted by the novel prospects offered by a better understanding of the role and the implication of the spatial organization of the chromatin, joining the Fullwood lab at the Cancer Science Institute in NUS, developing computational approaches for the integrative analysis of chromatin-chromatin interactions and epigenomic data at a genome scale.

Yokohama, Kanagawa, Japan

I joined the FANTOM international research consortium established by Dr. Hayashizaki and his colleagues in 2000 to assign functional annotations to the full-length cDNAs that were collected during the Mouse Encyclopedia Project at RIKEN. This unique international endeavour has steadily developed and expanded over time to encompass the fields of transcriptome analysis to more than 2,000 human biological samples (tissues, primary cells and cancer-model cell-lines) allowing an unprecedented characterisation of biological processes in normal development and diseases etiology from an understanding of the ‘elements’ - the transcripts - to an understanding of the ‘system’ - the transcriptional regulatory network.⇨ Key Achievements : • Development of the RIKEN ZENBU Genome Browser for real-time massive NGS-based (CAGE, RNA-seq, ChIP-seq, …) data integration, visualization and collaborative analysis. http://fantom.gsc.riken.jp/zenbu/ • Implementation of algorithms and pipelines for CAGE-based transcriptional network inference (FANTOM4 and FANTOM5 projects) and RNA-seq expression integrative analysis (FANTOM5). • Development and application of the nanoCAGE and CAGEscan technologies.⇨ Selected peer-reviewed scientific publications : • Hon CC*, Ramilowski JA*, Harshbarger J*, Bertin N*, …, Carninci P, Forrest ARR. An atlas of human long non-coding RNAs with accurate 5' ends. Nature, 2017 • Severin J, …, Hayashizaki Y, Bertin N#, Forrest ARR#. ZENBU: secured scientific collaborations, data integration and omics visualization. Nature Biotechnology, 2014 • Plessy C*, Pascarella G*, Bertin N*, …, Gustincich S, Carninci P. Promoter architecture of mouse olfactory receptor genes. Genome Research, 2012 • Plessy C*#, Bertin N*#, …, Gustincich S#, Carninci P#. Linking promoters to functional transcripts in small samples with nanoCAGE and CAGEscan. Nature Methods, 2010⎡ For a complete list of publications while in RIKEN Yokohama, see http://tinyurl.com/lzsyzyt ⎦

Greater Boston Area

From static to dynamic interactome networks⇨ Key Achievements• High-throughput data acquisition and analysis of in vivo concurrent spatial and temporal gene expression localization in C. elegans.• Development of storage and infrastructure analytics for the first proteome-scale protein-protein interaction map in a metazoan.• Continuous development of a LIMS dedicated to establishing ORFeome resources in C. elegans, and H. sapiens and B. melitensis.• Development of tools for the visualization and integrative analysis of protein-protein interaction, expression, and phenotypic data derived biological networks in S. cerevisiae and C. elegans.⇨ Selected peer-reviewed scientific publications : • Bertin N*, Simonis N*, Dupuy D*, Cusick ME, Han JD, Fraser HB, Roth FP, Vidal M. Confirmation of organized modularity in the yeast interactome. PloS Biology, 2007• Han JD, Bertin N, …, Roth FP, Vidal M. Evidence for dynamically organized modularity in the yeast protein-protein interaction network. Nature, 2004• Han JD, Dupuy D, Bertin N, Cusick ME, Vidal M. Effect of sampling on topology predictions of protein-protein interaction networks. Nature Biotechnology, 2005• Dupuy D*, Bertin N*, Hidalgo CA*, …, Barabasi AL, Vidal M. Genome-scale analysis of in vivo spatiotemporal promoter activity in Caenorhabditis elegans. Nature Biotechnology, 2007 • Li S*, Armstrong CM*, Bertin N*, Ge H*, Milstein S*, Boxem M*, Vidalain PO*, Han JD*, Chesneau A*, …, Roth FP, Hill DE, Vidal M. A map of the interactome network of the metazoan C. elegans. Science, 2004• Rual JF*, Hirozane-Kishikawa T*, Hao T*, Bertin N*, Li S*, …, Vidal M. Human ORFeome Version 1.1: A Platform for Reverse Proteomics. Genome Research, 2004⎡For a complete list of publications while in the Vidal Lab, Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute and Harvard Medical School Boston (USA), see http://tinyurl.com/mba3zyj ⎦

Doctor Of Philosophy - Phd, Biomathematics, Bioinformatics, And Computational Biology

Thesis title: “From static to dynamic interactome networks” Supervisor : Professor Marc Vidal Vidal Lab, Department of Genetics, Harvard.

Doctor Of Philosophy - Phd, Systems Biology

Thesis title: “From static to dynamic interactome networks” Supervisor : Professor Marc Vidal Vidal Lab, Department of Genetics, Harvard.

Magistère, Biology