Browsing by Author "Atalay, R. Ç."
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Item Open Access Prediction of protein subcellular localization based on primary sequence data(Springer-Verlag Berlin, 2003) Özarar, M.; Atalay, V.; Atalay, R. Ç.This paper describes a system called prediction of protein subcellular localization (P2SL) that predicts the subcellular localization of proteins in eukaryotic organisms based on the amino acid content of primary sequences using amino acid order. Our approach for prediction is to find the most frequent motifs for each protein (class) based on clustering and then to use these most frequent motifs as features for classification. This approach allows a classification independent of the length of the sequence. Another important property of the approach is to provide a means to perform reverse analysis and analysis to extract rules. In addition to these and more importantly, we describe the use of a new encoding scheme for the amino acids that conserves biological function based on point of accepted mutations (PAM) substitution matrix. We present preliminary results of our system on a two class (dichotomy) classifier. However, it can be extended to multiple classes with some modifications. © Springer-Verlag Berlin Heidelberg 2003.Item Open Access Wavelet merged multi-resolution super-pixels and their applications on fluorescent MSC images(IEEE, 2015) Yorulmaz, Onur; Oğuz, Oğuzhan; Akhan, Ece; Tuncel, Dönüş; Atalay, R. Ç.; Çetin, A. EnisA new multi-resolution super-pixel based algorithm is proposed to track cell size, count and motion in Mesenchymal Stem Cells (MSCs) images. Multi-resolution super-pixels are obtained by placing varying density seeds on the image. The density of the seeds are determined according to the local high frequency components of the MSCs image. In this way a multi-resolution super-pixels decomposition of the image is obtained. A second contribution of the paper is novel decision rule for merging similar neighboring super-pixels. An algorithm based on well known wavelet decomposition is developed and applied to the histograms of neighboring super pixels to exploit similarity. The proposed algorithm is experimentally shown to be successful in segmenting and tracking cells in MSCs images.