An improved BioHashing for human authentication
Pattern Recognition
Wavelet decomposition tree selection for palm and face authentication
Pattern Recognition Letters
A reliable method for cell phenotype image classification
Artificial Intelligence in Medicine
Generalized Needleman-Wunsch algorithm for the recognition of T-cell epitopes
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Input Decimated Ensemble based on Neighborhood Preserving Embedding for spectrogram classification
Expert Systems with Applications: An International Journal
Fusion of systems for automated cell phenotype image classification
Expert Systems with Applications: An International Journal
Coding of amino acids by texture descriptors
Artificial Intelligence in Medicine
Predicting HIV protease-cleavable peptides by discrete support vector machines
EvoBIO'07 Proceedings of the 5th European conference on Evolutionary computation, machine learning and data mining in bioinformatics
A new encoding technique for peptide classification
Expert Systems with Applications: An International Journal
| Hi-index | 0.01 |
Recently, several works have approached the HIV-1 protease specificity problem by applying a number of methods from the field of machine learning. However, it is still difficult for researchers to choose the best method due to the lack of an effective comparison. For the first time we have made an extensive study on methods for feature extraction for the problem of HIV-1 protease. We show that a fusion of classifiers trained in different feature spaces permits to obtain a drastically error reduction with respect to the performance of the state-of-the-art.