Mapping of cells and proteins improved with help of gamers and AI

The advances were reported by a collaboration between KTH Royal Institute of Technology, CCP Games and Massively Multiplayer Online Science. In a study published in the September issue of Nature Biotechnology, the researchers found that gamers, or "citizen scientists," helped boost the AI system used for predicting protein localization on a subcellular level. The combination of crowdsourcing and AI led to improved classification of subcellular protein patterns and the first-time identification of 10 new members of the family of cellular structures known as "Rods & Rings," says Emma Lundberg, a researcher from KTH who leads the Cell Atlas, part of the Human Protein Atlas, at the Science for Life joint research center. Lundberg says the data is being actively integrated into the publicly-available Human Protein Atlas database and will be a resource for researchers worldwide who are working towards a greater understanding of human cells, proteins and disease development. The researchers partnered with Massively Multiplayer Online Science and CCP Games to integrate analysis of protein localization from the Human Protein Atlas Cell Atlas images directly into EVE Online, a popular massively multiplayer online game.