Surface similarity parameter: A new machine learning loss metric for oscillatory spatio-temporal data.

Supervised machine learning approaches require the formulation of a loss functional to be minimized in the training phase. Sequential data are ubiquitous across many fields of research, and are often treated with Euclidean distance-based loss functions that were designed for tabular data. For smooth oscillatory data, those conventional approaches lack the ability to penalize amplitude, frequency and phase prediction errors at the same time, and tend to be biased towards amplitude errors.

RIP2 regulates growth and differentiation of normal myoblasts and of rhabdomyosarcoma cells.

RIP2 is an important regulator of myoblast proliferation and differentiation. We have previously demonstrated that in the myoblast cell line C2C12 and in primary myoblasts, downregulation of rip2 gene expression is a prerequisite for differentiation. To further study the role of rip genes in myogenesis, we compared expression patterns of rip1-4 in two myoblast cell lines, C2C12 and C2F3, after the induction of differentiation.