Artificial neural networks (ANN) to predict terminator sequences, based on a feed-forward architecture and trained using the error back propagation technique, have been developed. The network uses two different methods for coding nucleotide sequences. In one the nucleotide bases are coded in binary while the other uses the electron-ion interaction potential values (EIIP) of the nucleotide bases. The latter strategy is new, property based and substantially reduces the network size. The prediction capacity of the artificial neural network using both coding strategies is more than 95%
The current deluge of newly identified RNA transcripts presents a singular opportunity for improved ...
A neural network-based method has been developed for the prediction of β-turns in proteins by using ...
Eural Networks are a computational algorithm that uses layers of neurons with weighted edges connect...
AbstractArtificial neural networks (ANN) to predict terminator sequences, based on a feed-forward ar...
A neural network (NN) was trained on amino and nucleic acid sequences to test the NN’s ability to pr...
A neural network (NN) was trained on amino and nucleic acid sequences to test the NN’s ability to pr...
Many biological experiments require a protein sequence to be translated to the nucleic acid sequence...
Abstract:- The conversion of symbolic sequences into complex genomic signals allows using signal pro...
Protein sequences are composed of 20 amino acids . The twenty amino acid letters are: A, C, D, E, F,...
Promoters are DNA sequences located upstream of the gene region and play a central role in gene expr...
Several studies have explored how neural networks can be used to find genes within regions of previo...
One of the most difficult problems in the analysis of eucaryotic genes is the detection of RNA polym...
A multilayered feed-forward ANN architecture trained using the error-back-propagation (EBP) algorith...
Gene prediction is the process of finding the location of genes and other meaningful subsequences in...
The four nitrogenous bases of DNA spell out the recipes from which proteins are made. A gene typical...
The current deluge of newly identified RNA transcripts presents a singular opportunity for improved ...
A neural network-based method has been developed for the prediction of β-turns in proteins by using ...
Eural Networks are a computational algorithm that uses layers of neurons with weighted edges connect...
AbstractArtificial neural networks (ANN) to predict terminator sequences, based on a feed-forward ar...
A neural network (NN) was trained on amino and nucleic acid sequences to test the NN’s ability to pr...
A neural network (NN) was trained on amino and nucleic acid sequences to test the NN’s ability to pr...
Many biological experiments require a protein sequence to be translated to the nucleic acid sequence...
Abstract:- The conversion of symbolic sequences into complex genomic signals allows using signal pro...
Protein sequences are composed of 20 amino acids . The twenty amino acid letters are: A, C, D, E, F,...
Promoters are DNA sequences located upstream of the gene region and play a central role in gene expr...
Several studies have explored how neural networks can be used to find genes within regions of previo...
One of the most difficult problems in the analysis of eucaryotic genes is the detection of RNA polym...
A multilayered feed-forward ANN architecture trained using the error-back-propagation (EBP) algorith...
Gene prediction is the process of finding the location of genes and other meaningful subsequences in...
The four nitrogenous bases of DNA spell out the recipes from which proteins are made. A gene typical...
The current deluge of newly identified RNA transcripts presents a singular opportunity for improved ...
A neural network-based method has been developed for the prediction of β-turns in proteins by using ...
Eural Networks are a computational algorithm that uses layers of neurons with weighted edges connect...