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Translational efficiency detection software tools | Transcription data analysis

Translation has been the subject of intense modelling efforts in the last five decades, using various mathematical and computational approaches (Shah et al., 2013; Gerst and Levine, 1965; MacDonald and Gibbs, 2004; Gilchrist and Wagner, 2006; Mitarai et al., 2008; Zouridis and Hatzimanikatis, 2007; Reuveni et al., 2011; Dana and Tuller, 2012; Ciandrini et al., 2013). These models aimed at predicting protein production rates and understanding the role of mRNA features or contributions of translation stages. Source text: Lauria et al., 2015.

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A model trained on experimental imaging-derived data, able to quickly and accurately predict the steady state number of ribosomes per transcript in entire transcriptomes. RiboAbacus uses a mechanistic model of ribosome dynamics, enabling the quantification of the relative importance of different features (such as codon usage and the 5' ramp effect) in determining the accuracy of predictions. The model has been optimized in the human Hek-293 cell line to fit thousands of images of human polysomes obtained by atomic force microscopy, from which we could get a reference distribution of the number of ribosomes per mRNA with unmatched resolution. RiboAbacus is an intuitive tool that allows an immediate estimation of crucial translation properties for entire transcriptomes, based on easily obtainable transcript expression levels.
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