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We propose algorithms for learning Markov boundaries from data without having to learn a Bayesian network first. We study their correctness, scalability and data efficiency. The last two properties are important because we aim to apply the algorithms to identify the minimal set of features that is needed for probabilistic classification in databases with(More)
We analyze two different feature selection problems: finding a minimal feature set optimal for classification (MINIMAL-OPTIMAL) vs. finding all features relevant to the target variable (ALL-RELEVANT). The latter problem is motivated by recent applications within bioinformatics, particularly gene expression analysis. For both problems, we identify classes of(More)
This paper proposes and evaluates the k-greedy equivalence search algorithm (KES) for learning Bayesian networks (BNs) from complete data. The main characteristic of KES is that it allows a trade-off between greediness and randomness, thus exploring different good local optima when run repeatedly. When greediness is set at maximum, KES corresponds to the(More)
In this paper, we aim to compare empirically four initialization methods for the K-Means algorithm: random, Forgy, MacQueen and Kaufman. Although this algorithm is known for its robustness, it is widely reported in literature that its performance depends upon two key points: initial clustering and instance order. We conduct a series of experiments to draw(More)
MOTIVATION For the last few years, Bayesian networks (BNs) have received increasing attention from the computational biology community as models of gene networks, though learning them from gene-expression data is problematic. Most gene-expression databases contain measurements for thousands of genes, but the existing algorithms for learning BNs from data do(More)
OBJECTIVE To test whether oxidative stress could promote a systemic acute-phase response in elderly patients with type II diabetes. DESIGN AND METHODS In a group of 30 older diabetic patients with poor glycemic control, serum levels of lipid peroxides, measured as thiobarbituric acid-reacting substances (TBARS); C-reactive protein (CRP); interleukin(More)
Human immunodeficiency virus-I (HIV-1) infected patients show a gradual loss of natural killer (NK) cells that correlates with disease progression. However, the effect of HIV-1 infection on different NK cell subsets has not been fully characterized. In healthy individuals most NK cells are CD3-CD56+ and two different subpopulations, CD56(dim) and(More)
The present study evaluated 17beta-estradiol (17betaE(2)) (2.5 mg/kg sc) effects on bilateral OBX-induced behavioral changes and oxidative stress. OBX in male Wistar rats produced an increase in lipid peroxidation products and a decline in reduced glutathione (GSH) content and glutathione peroxidase (GSH-Px) activity, together with an increase in caspase-3(More)
We studied the effects of transcranial magnetic stimulation (TMS, 60 Hz and 0.7 mT for 4 h/day for 14 days) on oxidative and cell damage caused by olfactory bulbectomy (OBX) in Wistar rats. The levels of lipid peroxidation products and caspase-3 were enhanced by OBX, whereas it prompted a reduction in reduced glutathione (GSH) content and antioxidative(More)
We evaluated the effects of nicotine on cell and oxidative damage caused by olfactory bulbectomy (OBX). The rats were divided into seven groups as follows: i) control; ii) vehicle (6% ethanol); iii) treated with nicotine; iv) sham operated; v) olfactory bulbectomy (OBX); vi) OBX+vehicle; and vii) OBX+Nic. The OBX was performed using the trepanation of(More)