The von Heijne [ 20] signal sequence prediction was used to predict the start of the mature laccase.
Gapped Ancestral Sequence Prediction program (GASP) [ 25] was used to predict ancestral sequences from phylogenetic trees and the corresponding multiple sequence alignments.
Ghandi, M., Lee, D., Mohammad-Noori, M. & Beer, M. A. Enhanced regulatory sequence prediction using gapped k-mer features.
Splice variants were removed from the datasets, keeping only the representative/longest protein sequence prediction, and datasets were filtered for internal stop codons and incompatible reading frames.
My machine learning projects involve: binary neural networks, recurrent neural networks for noisy sequence prediction, artistic stylization of movies, and hierarchical neural network models that drive cars.
A study of the peptide sequence prediction based on the steered molecular dynamics (SMD) method is presented.
We first show that this architecture can achieve excellent performance in visual sequence prediction tasks, including state-of-the-art performance in a standard 'bouncing balls' dataset (Sutskever et al., 2009).
The optimal input levels differ for the two sequence prediction problems, but a small region of overlap exists where both tasks can usually be performed successfully.
Besides improving the reaction conditions, the stringency of primer hybridization can be distinctly improved by computer based sequence prediction algorithms based on the thermodynamic stability of DNA hybrid a described by the partition function of the hybridization reaction.
In this paper, we investigate a combined architecture of Bayesian segmentation at the first stage and neural network at the second stage which captures both local and non-local correlation, to increase the single sequence prediction accuracy.
By applying a recently developed sequence prediction algorithm and a novel ensemble averaging calculation, we generate a diverse collection of peptide sequences that are predicted to have significant affinity for the protein.
