Data within biology has been growing exponentially ever since we first decoded the human genome. So has the computational power.
We now have the potential to measure thousands of biological signals in no time and understand the molecular processes that cause how we appear - the so called phenotype.
The problem is that we do not have a good enough framework and computational tools to do this.
Biology is like a messy spider's web, lots of processes that influence each other that together change how an organism lives and grows. Until now, we have been limited in analyzing just one or two strands of the web at a time. But to understand these complex interactions we need new tools that look at the web as a whole, allowing us to untangle the connections within.
This is what FindingPheno does!
We develop and apply computational methods that utilize the avalanche of multi-omics data currently being generated, to unlock the untapped potential within it.
We use publicly available data and collaborate with projects around. We have assembled a team of experts taking a new approach, combining machine learning with statistical modelling and evolutionary biology in unexpected ways.
Our aim is to go beyond association to find true causation, learning about the interactions between crops or farm animals and their microbiomes and how they respond to feed, fertilizer and the environment.
Then, once we untangle the spider web of biological data and link it to changes in phenotype, we can use this data to solve big problems like improving farming methods, protecting the environment, and even combating human disease.