Tagged: machine learning







Plant-mSubP: a machine learning tool to predict single- and multi-target protein subcellular localisation

Plant cells are three-dimensional spaces composed of several compartments, each with its own physicochemical environment and function. The subcellular localisation of proteins, the cell’s functional machinery, is very important for characterizing their functions in a cell. Improper localisation can result in disease and cell death. Thus, predicting the subcellular localisation of proteins is a hot topic in proteomics, yet doing so through biochemical experiments can be laborious, expensive, and time-consuming. Computational prediction can be an effective alternative allowing us to decipher protein function and speed up genome annotation. In a new article published in AoBP, Sahu et al. present their...

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