C3BI Seminar - Big data in biology : challenges and opportunities - Research - Institut Pasteur

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Soutenance de Thèse de Doctorat présentée par Arthur Charles-Orszag : «Cellular & molecular mechanisms of human endothelial cell plasma membrane remodeling by Neisseria meningitidis»

Soutenance d’Habilitation à Diriger des Recherches d’Henrik Salje

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05

Oct 2017

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14:00:00

Institut Pasteur, Paris, France

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Building: LWOFF

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2017-10-05 14:00:00 2017-10-05 15:00:00 Europe/Paris C3BI Seminar – Big data in biology : challenges and opportunities Ewan Birney is co-director of the European Bioinformatic Institute and played a vital role in annotating the genome sequences of human, mouse, chicken and several other organisms. He was one of the founders of […] Institut Pasteur, Paris, France Maxime Rotival maxime.rotival@pasteur.fr

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Ewan Birney is co-director of the European Bioinformatic Institute and played a vital role in annotating the genome sequences of human, mouse, chicken and several other organisms.

He was one of the founders of the Ensembl Genome Browser and the head of the Encode data analysis group.

Ewan is also a non-executive Director of Genomics England, and a consultant and advisor to a number of companies, including Oxford Nanopore Technologies and GSK.

Abstract:

Molecular biology is now a leading example of a data intensive science, with both pragmatic and theoretical challenges being raised by data volumes and dimensionality of the data. These changes are present in both “large scale” consortia science and small scale science, and across now a broad range of applications – from human health, through to agriculture and ecosystems. All of molecular life science is feeling this effect.

This shift in modality is creating a wealth of new opportunities and has some accompanying challenges. In particular there is a continued need for a robust information infrastructure for molecular biology. This ranges from the physical aspects of dealing with data volume through to the more statistically challenging aspects of interpreting it. A particular problem is finding causal relationships in the high level of correlative data. Drawing on recent experience I will explore both the “blue collar” challenges of data volume and the “white collar” challenges of interpretation.

I will end with exploration of linear traits in cardiac biology using large scale cohorts.

Location

Building: LWOFF
Address: Institut Pasteur, Paris, France

Published on: 26 Sep 2017 • Modified on: 28 Sep 2017

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