{"id":6491,"date":"2020-08-12T14:31:58","date_gmt":"2020-08-12T13:31:58","guid":{"rendered":"https:\/\/www.innovationnewsnetwork.com\/?p=6491"},"modified":"2020-08-12T14:31:58","modified_gmt":"2020-08-12T13:31:58","slug":"new-ai-tool-can-further-our-understanding-of-tumour-formation","status":"publish","type":"post","link":"https:\/\/www.innovationnewsnetwork.com\/new-ai-tool-can-further-our-understanding-of-tumour-formation\/6491\/","title":{"rendered":"New AI tool can further our understanding of tumour formation"},"content":{"rendered":"
Scientists at the Institute of Computational Biology at Technische Universit\u00e4t M\u00fcnchen<\/a> (TUM) developed the new Artificial Intelligence (AI) technology to help researchers estimate reaction rates of RNA transcription, splicing and degradation without the need of any experimental data. This technology might help medical professionals better understand tumour formation and unravel cell signalling in response to cancer treatment<\/a>.<\/p>\n This new method, named single-cell velocity (scVelo), has improved upon traditional single cell sequencing methods. Prior to these findings, researchers studied static images of single cells to reveal more about their functions and properties. This method limits a researcher\u2019s access to information about the dynamics of cell development and gene activity. To improve upon this, the scientists behind scVelo aim to allow researchers to \u00a0reconstruct the developmental trajectory of a cell on a computational basis.<\/p>\nImproving upon cancer cell identification<\/h3>\n