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Cancer

Explore molecular interactions across cancer types with CancerNet

Cancer is a complex disease characterized by a large number of molecular interaction alterations. Knowledge of molecular interactions is quite useful for discovering the functions of molecules and the processes they are involved in. However, there is little systematic insight into the nature and scale of the potential interactions in human cancers.     To solve this gap, Dr. Ming Chen and his colleagues from the Institute of Bioinformatics in Zhejiang University constructed CancerNet, a database for decoding multilevel molecular interactions across diverse cancer types. Here, they describe the features of CancerNet. The CancerNet database   CancerNet aims to provide cancer-specific molecular interaction networks across multiple cancer types. It includes 33 human cancer types. The interactions contain protein-protein interactions (PPIs), miRNA–target …

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Link splice-isoform expression to cancer metabolism with GEMsplice

Metabolic models rely on genes and proteins expression to estimate or predict a metabolic cell phenotype. In the case of cancer, it is now admitted that metabolism dysregulations play a crucial role in cancer onset and proliferation. However, most metabolic models only rely on gene expression, and do not account for splice-isoform expression and/or alteration.   To solve this gap, Claudio Angione developed GEMsplice, a desktop application that allows to link splice-isoform gene expression data to cancer metabolism. Here, he describes the features and benefits of GEMsplice. Solving the gap in cancer metabolism models Despite being often perceived as the main contributors to cell fate and physiology, genes alone cannot predict the cellular phenotype. A genome-scale analysis of cancer metabolism captures …

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