Understanding mRNA localization within a cell has been an area of interest for biologists since a long time. mRNA subcellular localization is known to exert a high degree of control on protein synthesis, cellular polarity and developmental processes. Up until recently, distribution of mRNA within a cell was primarily studied using wet-lab techniques like FISH, and APEX-Seq. However, with the advent of accurate machine learning algorithms and increased availability of biological data, it is now possible to computationally predict this biological phenomenon. Current tools are majorly designed as multiclass classifiers i.e., they can assign only one location to each mRNA. But this approach would fail to account for the fact that a majority of mRNAs are localized to multiple locations. So, in order to solve these issues, we have developed MRSLpred – a multilabel mRNA subcellular localization prediction tool.

Reference: Choudhury S., Bajiya N., Patiyal S. and Raghava GPS (2024) MRSLpred -A hybrid approach for predicting multi-label subcellular localization of mRNA at genome scale. Front. Bioinform. doi: 10.3389/fbinf.2024.1341479