1487987e862c44b91a0296cf3866387e-AuthorFeedback.pdf

Methods 2.3), and these absolute gradients are smoothed, thus it can handle negative2 or low-scoring bases within a motif (this is also why thesmoothing is important). How does the Fourier-based prior compare to other attribution prior formulations [R2,3,4] and traditional13 regularization[R4]? Why did the auPRC of peak overlap not improve in some cases with the Fourier-based prior? Profile44 models are able to finely track motifs along shifting peaks, so they can isolate the specific motifs underlying peaks.45 Binarymodels, however, see the same sequences repeatedly to predict abinary label, so if asequence has multiple46 motifs(i.e.