Scientific MOOCs follower. Author of Airpocalypse, a techno-medical thriller (Out Summer 2017)

Welcome to the digital era of biology (and to this modest blog I started in early 2005).

To cure many diseases, like cancer or cystic fibrosis, we will need to target genes (mutations, for ex.), not organs! I am convinced that the future of replacement medicine (organ transplant) is genomics (the science of the human genome). In 10 years we will be replacing (modifying) genes; not organs!

Anticipating the $100 genome era and the P4™ medicine revolution. P4 Medicine (Predictive, Personalized, Preventive, & Participatory): Catalyzing a Revolution from Reactive to Proactive Medicine.

I am an early adopter of scientific MOOCs. I've earned myself four MIT digital diplomas: 7.00x, 7.28x1, 7.28.x2 and 7QBWx. Instructor of 7.00x: Eric Lander PhD.

Upcoming books: Airpocalypse, a medical thriller (action taking place in Beijing) 2017; Jesus CRISPR Superstar, a sci-fi -- French title: La Passion du CRISPR (2018).

I love Genomics. Would you rather donate your data, or... your vital organs? Imagine all the people sharing their data...

Audio files on this blog are Windows files ; if you have a Mac, you might want to use VLC ( to read them.

Concernant les fichiers son ou audio (audio files) sur ce blog : ce sont des fichiers Windows ; pour les lire sur Mac, il faut les ouvrir avec VLC (

Where should genomic information be stored? In electronic health record or in... our own DNA?

Genomic information probably should not be stored in electronic health records. Shoud it be stored in... our own DNA? In artificial (engineered) DNA? The future will tell...

Meanwhile, we have to cope with... this (good luck!): "Genomic data characteristics and life cycle One gene has ~3,000 base pairs, the exome has ~50 million base pairs,21 and the genome has ~3.2 billion base pairs.22 Apart from potentially being very large, an additional attribute of next-generation sequencing genomic data is that it has uneven depth of coverage, and thus, ideally it would be important to store information pertaining to the quality of the base-pair calls and which regions may have been missed entirely because coverage was too low.23 Storing such attributes further complicates the storage of raw genomic data. A way to reduce the complexity of genomic data is to process it to a set of variants or even further to a list of known pathologic variants and thus only store variants or selected variants. This substantially reduces the amount of data that must be stored. If one stores all variants for an individual’s complete genome, there are still an estimated 3–4 million variants per patient to store.24 In addition, there are times when accessing the normal (reference) variant is still important, for example, for copy-number variants (e.g., three or more copies of a normal gene) and some heterozygous conditions. Therefore, even normal variants should be stored in some cases. Additional storage would also be required if one stores the variants found in abnormal tissue, such as cancers."

Storing and interpreting genomic information in widely deployed electronic health record systems

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