Texture information could be used in proteomics to improve the quality of the image analysis of proteins separated on a gel. In order to evaluate the best technique to identify relevant textures, we use several different kernel-based machine learning...
Predicting binary events such as newborns with large birthweight is important for obstetricians in their attempt to reduce both maternal and fetal morbidity and mortality. Such predictions have been a challenge in obstetric practice, where longitudin...
BACKGROUND: The conjugation of ubiquitin to a substrate protein (protein ubiquitylation), which involves a sequential process--E1 activation, E2 conjugation and E3 ligation, is crucial to the regulation of protein function and activity in eukaryotes....
BACKGROUND: Understanding the mechanisms by which transcription factors (TF) are recruited to their physiological target sites is crucial for understanding gene regulation. DNA sequence intrinsic features such as predicted binding affinity are often ...
BACKGROUND: Non-small cell lung cancer (NSCLC) is one of the leading causes of death globally, and research into NSCLC has been accumulating steadily over several years. Drug repositioning is the current trend in the pharmaceutical industry for ident...
Computational and mathematical methods in medicine
Jan 10, 2016
This study presents the design of the recognition system that will discriminate between healthy people and people with Parkinson's disease. A diagnosing of Parkinson's diseases is performed using fusion of the fuzzy system and neural networks. The st...
Machine learning or MVPA (Multi Voxel Pattern Analysis) studies have shown that the neural representation of quantities of objects can be decoded from fMRI patterns, in cases where the quantities were visually displayed. Here we apply these technique...
IEEE transactions on neural networks and learning systems
Jan 8, 2016
In this brief, the problem of composite anti-disturbance tracking control for a class of strict-feedback systems with unmatched unknown nonlinear functions and external disturbances is investigated. A disturbance-observer-based control (DOBC) in comb...
Computer methods and programs in biomedicine
Jan 7, 2016
BACKGROUND AND OBJECTIVE: The automatic classification of breast imaging lesions is currently an unsolved problem. This paper describes an innovative representation learning framework for breast cancer diagnosis in mammography that integrates deep le...
Neural networks : the official journal of the International Neural Network Society
Jan 6, 2016
In this paper, we present a fast and accurate kernel-based supervised algorithm referred to as the Reduced Kernel Extreme Learning Machine (RKELM). In contrast to the work on Support Vector Machine (SVM) or Least Square SVM (LS-SVM), which identifies...
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