New Approach to Detect Coiled Coil and Leucine Zipper Motifs in Protein Sequences.

This article presents a new approach to detect coiled coil and leucine zipper (L-Zip) motifs in protein sequences. The approach is based on protein scale calculation and sequence analysis. For this purpose, the wavelet-based local extrema extraction is employed, and window-based variations of local extrema afterward. This, in turn, provided a way to distinguish coiled coil subsequences and potential L-Zip motifs. The approach is validated on carefully chosen protein sequences that return inconclusive results within known frameworks for L-Zip detection, for example, 2ZIP. The results show that this new approach represents an improvement over previously presented approaches.

Neuro-fuzzy classification of asthma and chronic obstructive pulmonary disease.

BACKGROUND: This paper presents a system for classification of asthma and chronic obstructive pulmonary disease (COPD) based on fuzzy rules and the trained neural network. METHODS: Fuzzy rules and neural network parameters are defined according to Global Initiative for Asthma (GINA) and Global Initiative for chronic Obstructive Lung Disease (GOLD) guidelines. For neural network training more than one thousand medical reports obtained from database of the company CareFusion were used. Afterwards the system was validated on 455 patients by physicians from the Clinical Centre University of Sarajevo. RESULTS: Out of 170 patients with asthma, 99.41% of patients were correctly classified. In addition, 99.19% of the 248 COPD patients were correctly classified. The system was 100% successful on 37 patients with normal lung function. Sensitivity of 99.28% and specificity of 100% in asthma and COPD classification were obtained. CONCLUSION: Our neuro-fuzzy system for classification of asthma and COPD uses a combination of spirometry and Impulse Oscillometry System (IOS) test results, which in the very beginning enables more accurate classification. Additionally, using bronchodilatation and bronhoprovocation tests we get a complete patient's dynamic assessment, as opposed to the solution that provides a static assessment of the patient.