FindingPheno is a four-year-long collaborative research project with a consortium of eight organizations from five countries...
The FindingPheno project was presented at the Holofood Co-LAB industry event organised by Chr. Hansen on 27 April 2021. This virtual meeting brought together academic researchers...
FindingPheno is a Research and Innovation Action (RIA) combining eight different academic and industrial partners from five countries. RIAs are a specific type of international research collaboration focused on...
From ecological questions to industrial applications, harnessing the power of microbiomes is becoming increasingly recognized for its potential to solve the world’s most challenging problems. In keeping with this year's theme of sustainability.....
Big data is getting bigger.
What do we mean by 'data tsunami'? Why is it happening? Why should we care?...
FindingPheno has taken on the challenging task of analyzing omics data from the holobiont, i.e. plant or animal hosts and their associated microbiome....
FindingPheno activities are divided into Work Packages. This is primarily a tool to help us understand what we should do and achieve during the project...
We are pleased to announce the reaching of a key early milestone in our project, the completion of our Data Management Plan (DMP)...
Preparations are in full swing for our first external meeting, our first opportunity as a consortium to start connecting with other EU projects, academics or companies working at the intersection of big data and microbiome research...
FindingPheno commenced with an online Kick-Off Meeting (KOM) where partners 'met' each other and started relationship building despite the global pandemic isolation...
Our need for food is growing, with global demand expected to increase by 70% by 2050 with population growth and demographic change. Using our current farming methods to meet this extra demand would require new farmland...
Machine Learning and Statistical Modeling for Multi-Omics Training
The University of Turku coordinated the training, which targeted consortium members and close collaborators. The training gave an overview of analytical tools used for multi-omics studies in R, especially multi-omics tools and techniques required to ...
When discussing farm-grown meat, most first thoughts are chicken, beef or pork. But fish can also be grown on farms via aquaculture. Aquaculture farms can take many forms...
Machine learning is a breakthrough technology that can revolutionize the way we analyze and make decisions based on data...
Did you know about Genome
Wide Association Studies, or
GWAS? It aims to identify
genetic causes of specific
diseases...
We released a short video with an update on the Annual Meeting held in Budapest in May 2022. The meeting was hosted by the Centre for Ecological Research and was a great success. The video below includes pictures from the event.
Did you know that cancer cells have distinct features that set them apart from normal cells? They have different shapes, sizes, organization, and even express different proteins. It is amazing how these differences can aid in the diagnosis...
Farm animals like pigs, cows and sheep exhibit different unique personalities and behaviors, like us humans. They handle various types of stress...
In my experience, temporary assignments or secondments can be really cool for secondees and host institutions. You get to expand your knowledge, develop new skills, and gain valuable experience working with professionals in a new environment. Likewise, host institutions get fresh perspectives that can develop new and improved work practices. It is a win-win situation for everyone.
In this blog post, I will share my experience participating in a three-month virtual secondment with a Data Science team at the University of Turku (UTU) in Finland. I will discuss the process of planning and executing my online secondment, and the research conducted.
Meet Klara! 🎉 Hailing from the Swedish northern city of Umeå, where she completed her studies and PhD. She is a math whiz with a passion for digging into complex data.