Precision Medicine will need to get out of the pharma silo that is based on symptoms


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.


After low-cost airlines (Ryanair, Easyjet ...) comes "low-cost" participatory medicine. Some of my readers have recently christened this long-lasting, clumsy attempt at e-writing of mine "THE LOW-COSTE INNOVATION BLOG". I am an
early adopter of scientific MOOCs. My name's Catherine Coste. 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?

Audio files on this blog are Windows files ; if you have a Mac, you might want to use VLC (http://www.videolan.org) 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 (http://www.videolan.org).


Here's How I've started Learning Quantitative Medicine

The future of medicine will involve computer programming, big data and genomics. How will the stethoscopes and microscopes of tomorrow look like? The answer lies in your genome, as well as programming languages like Python, or cool "quantitative biology" instruments like MATLAB and R. Ever heard of that (very cool!) genome editing tool called CRISPR?
Picking a MOOC direction is easier said than done... Completing MITx 6.00.1x (python MOOC) is not my goal right now, as it has no contents "re:" genomics. I'm still trying to find the best way to review 7.QBWx MITx & 7.00x MITx course contents -- earned myself both EdX digital diplomas -- and I came up with this idea: I will use this book, as it is very helpful to learning python coding language: "Help Your kids With Computer Coding."





"Intro to systems biology" on Coursera (Mount Sinai) seems very promising, too... 7.00x and 7.QBWx (MIT&edX) were both excellent, great pedagogy & content in 7.00x, fascinating content in 7.QBWx but difficult because no tutorials in python.

Angelia Yulita, a MOOC student from Jakarta, Indonesia:

"I took an edX course from Georgetown: Genomic Medicine Gets Personal and they talked about how system biologists would play a great role for handling the big data. 

I was curious, so I surfed google and found that course from Coursera ["Intro to systems biology"]. So far the course is very interesting and I might decide to take all of the course series for specialization... But still, the quantitative part is challenging! Not as challenging as MIT's quantitative biology workshop 7.QBWx, but still...  

I took lots of courses about quantitative bio and its computational tools. I want to go to grad school and still try to find out whether quantitative bio is right for me or not... I wish I could do well... "












 

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