NetBID2: computational tool for hidden driver analysis
2023
St. Jude Children’s Research Hospital, Memphis, USA
In this study, the researchers have created an updated method of analysing multi-omic data in an effort to identify hidden drivers of cancer that are not immediately obvious through traditional sequencing approaches. The computational tool, called NetBID2, was designed to find hidden drivers of disease by taking large sets of RNA sequencing data and generating a gene-gene interactome. This interactome allows researchers to track the relationships between driver candidates and their downstream effector genes, thus identifying which signalling proteins are most central to the key relationships that fuel disease. The authors demonstrate the power of NetBID2 using three hidden driver examples in normal tissues and paediatric and adult cancers.
NetBID2 provides comprehensive hidden driver analysis
Jiyang Yu
Added on: 09-14-2023
[1] https://www.nature.com/articles/s41467-023-38335-6[2] https://www.drugtargetreview.com/news/109662/computational-tool-gets-more-out-of-multi-omics-data/?utm_source=Email+marketing&utm_medium=email&utm_campaign=DTR+-+Industry+Insight+-+Quantum+-+01.09.2023&utm_term=Computational+tool+gets+more+out+of+multi-omics+data&utm_content=https%3a%2f%2femails.drugtargetreview.com%2frussellpublishinglz%2f&gator_td=mIEcIc9i81kCKVEhzhGoua2AdBgsh3MXlma4DaxbM%2bxK7rKyR%2fQcxk8ybkHB1l%2bRXEvytgBCnnivdmqswbwYTxn4iGykbFmGXXK7dz8FnJzV82Okhr4PBfh1smePTncFC5cYRgtu%2f2Az8umlaHaYwOrkQf3awJMA0VuCviYYObU2xCPqj4rl%2b6sSM5T5exVI%2fzk%2b0uf1Z1EzIpnMw8X8kEumOE8bMB8%2f1hAmVz6Yx%2fw%3d
