Principal Investigator: Professor Yaniv Erlich
MyHeritage Ltd., IsraelTags: 34008, complex-trait, Machine Learning, statistics
A central question is medical research is understanding the reason and risk factors of different traits and diseases, such as cancer, heart diseases etc. By mapping these risk factors, it is possible to identify people and populations that are at higher risk and offer early intervention in order to mitigate the risk.
For example, we can look at a genetic marker across the genome and see whether it is found with people that have higher likelihood for breast cancer.
If so, such a pattern can indicate that people that carry this marker have higher risk for breast cancer.
If successful, our research agenda will illumine key elements in the genetics of common illnesses and traits. With this information in hand, medical experts will be able to identify people at risk and offer early intervention. This mission perfectly aligns with the UK Biobank stated purpose of ??improve the prevention, diagnosis and treatment of illness and the promotion of health throughout society?.
We are a group of biologists, bioinformatics scientists and data scientists. We will take a combined approach in order to identify the risk factors and improve the signal to noise ratio. We plan to use cutting edge methods including statistical tools, artificial intelligence, and other types of machines learning techniques.
Experience has highlighted that larger datasets increase the likelihood of extracting signal from the data. Therefore, we would aspire to the greatest sample size possible, ideally the entire cohort.