Health and Healthcare Systems

Your health just got personal thanks to an algorithm

A DNA double helix is seen in an undated artist's illustration released by the National Human Genome Research Institute to Reuters on May 15, 2012.     REUTERS/National Human Genome Research Institute/Handout (CANADA - Tags: SCIENCE TECHNOLOGY) FOR EDITORIAL USE ONLY. NOT FOR SALE FOR MARKETING OR ADVERTISING CAMPAIGNS. THIS IMAGE HAS BEEN SUPPLIED BY A THIRD PARTY. IT IS DISTRIBUTED, EXACTLY AS RECEIVED BY REUTERS, AS A SERVICE TO CLIENTS - RTR32460

Analyzing genome databases could allow personalized healthcare in the future. Image: REUTERS/National Human Genome Research Institute

Jelor Gallego
Writer, Futurism
Our Impact
What's the World Economic Forum doing to accelerate action on Health and Healthcare Systems?
The Big Picture
Explore and monitor how Global Health is affecting economies, industries and global issues
A hand holding a looking glass by a lake
Crowdsource Innovation
Get involved with our crowdsourced digital platform to deliver impact at scale
Stay up to date:

Global Health


Ever since the first complete mapping of the human genome in 2003, biologists and other scientists have been hard at work making the process easier and faster. They’ve gotten so good at it, in fact, that they’ve now sequenced the genomes of more than a million people and believe that number could rise to nearly 2 billion by 2025.

However, our ability to make sense of all this data remains lackluster. Machine learning could change that, though, as a new algorithm has been developed that can read large genome data sets for the goal of personalizing healthcare.

Currently being used for this purpose is the STRUCTURE algorithm, which was first described in 2000. It looks at all the variants in each genome in a data set before updating its model to characterizing ancestral populations and how they affect an individual’s own genome. Then it moves on to the next genome.

The new algorithm, TeraStructure, looks at one variant in all of the genomes in a data set before it updates its model to produce a working estimate of population structure. That allows it to create ancestry models more accurately and quickly — two to three times faster, in fact, on a simulated data set of 10,000 genomes. It can even analyze sets as large as 100,000 or 1 million genomes.

Illness and machine learning
Image: Futurism


Each mapped genome is several billion characters long, and given that we could have as many as two billion mapped within the next decade, we need to find a efficient way to make use of this data. Therefore, machine learning could be an invaluable tool in the field of genomics as it could be used for genetic diagnostics, refining drug targets, pharmaceutical development, and personalized medicine, according to Brandon Frey, founder of company Deep Genomics.

Knowing the ancestry of an individual enables doctors to see which variants in an individual genome are due to normal genetic variation in a population and which are due to disease-causing variants passed down from ancestors. This allows for personalized healthcare — if your doctor knows which diseases you are more susceptible to due to mutations in your DNA, they can better treat or prevent those diseases. Ultimately, machine learning may provide a way for us to tailor medicine to provide better and faster relief for individuals.

Don't miss any update on this topic

Create a free account and access your personalized content collection with our latest publications and analyses.

Sign up for free

License and Republishing

World Economic Forum articles may be republished in accordance with the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License, and in accordance with our Terms of Use.

The views expressed in this article are those of the author alone and not the World Economic Forum.

Related topics:
Health and Healthcare SystemsEmerging Technologies
World Economic Forum logo
Global Agenda

The Agenda Weekly

A weekly update of the most important issues driving the global agenda

Subscribe today

You can unsubscribe at any time using the link in our emails. For more details, review our privacy policy.

Scientists make pancreatic cancer discovery, and other top health stories to read

Shyam Bishen

July 17, 2024

About Us



Partners & Members

  • Sign in
  • Join Us

Language Editions

Privacy Policy & Terms of Service

© 2024 World Economic Forum