Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/11
Browse
4 results
Search Results
Now showing 1 - 4 of 4
Article Citation - WoS: 3Citation - Scopus: 4Quasi-Supervised Strategies for Compound-Protein Interaction Prediction [article](Wiley-VCH Verlag, 2021) Çakı, Onur; Karaçalı, BilgeIn-silico compound-protein interaction prediction addresses prioritization of drug candidates for experimental biochemical validation because the wet-lab experiments are time-consuming, laborious and costly. Most machine learning methods proposed to that end approach this problem with supervised learning strategies in which known interactions are labeled as positive and the rest are labeled as negative. However, treating all unknown interactions as negative instances may lead to inaccuracies in real practice since some of the unknown interactions are bound to be positive interactions waiting to be identified as such. In this study, we propose to address this problem using the Quasi-Supervised Learning (QSL) algorithm. In this framework, potential interactions are predicted by estimating the overlap between a true positive dataset of compound-protein pairs with known interactions and an unknown dataset of all the remaining compound-protein pairs. The potential interactions are then identified as those in the unknown dataset that overlap with the interacting pairs in the true positive dataset in terms of the associated similarity structure. We also address the class-imbalance problem by modifying the conventional cost function of the QSL algorithm. Experimental results on GPCR and Nuclear Receptor datasets show that the proposed method can identify actual interactions from all possible combinations.Article Citation - WoS: 3Citation - Scopus: 4Hierarchical Motif Vectors for Prediction of Functional Sites in Amino Acid Sequences Using Quasi-Supervised Learning(Institute of Electrical and Electronics Engineers Inc., 2012) Karaçalı, BilgeWe propose hierarchical motif vectors to represent local amino acid sequence configurations for predicting the functional attributes of amino acid sites on a global scale in a quasi-supervised learning framework. The motif vectors are constructed via wavelet decomposition on the variations of physico-chemical amino acid properties along the sequences. We then formulate a prediction scheme for the functional attributes of amino acid sites in terms of the respective motif vectors using the quasi-supervised learning algorithm that carries out predictions for all sites in consideration using only the experimentally verified sites. We have carried out comparative performance evaluation of the proposed method on the prediction of N-glycosylation of 55,184 sites possessing the consensus N-glycosylation sequon identified over 15,104 human proteins, out of which only 1,939 were experimentally verified N-glycosylation sites. In the experiments, the proposed method achieved better predictive performance than the alternative strategies from the literature. In addition, the predicted N-glycosylation sites showed good agreement with existing potential annotations, while the novel predictions belonged to proteins known to be modified by glycosylation.Article Citation - Scopus: 1An Efficient Algorithm for Large-Scale Quasi-Supervised Learning(Springer Verlag, 2016) Karaçalı, BilgeWe present a novel formulation for quasi-supervised learning that extends the learning paradigm to large datasets. Quasi-supervised learning computes the posterior probabilities of overlapping datasets at each sample and labels those that are highly specific to their respective datasets. The proposed formulation partitions the data into sample groups to compute the dataset posterior probabilities in a smaller computational complexity. In experiments on synthetic as well as real datasets, the proposed algorithm attained significant reduction in the computation time for similar recognition performances compared to the original algorithm, effectively generalizing the quasi-supervised learning paradigm to applications characterized by very large datasets.Article Citation - Scopus: 13The Prognostic Value of Tumor-Stroma Proportion in Laryngeal Squamous Cell Carcinoma(Federation of Turkish Pathology Societies, 2013) Ünlü, Mehtat; Çetinayak, Hasan Oğuz; Önder, Devrim; Ecevit, Cenk; Akman, Fadime; İkiz, Ahmet ömer; Ada, Emel; Karaçalı, Bilge; Sarıoğlu, SülenObjective: Tumor-stroma proportion of tumor has been presented as a prognostic factor in some types of adenocarcinomas, but there is no information about squamous cell carcinomas and laryngeal carcinomas. Material and Method: Five digital images of the tumor sections were obtained from 85 laryngeal carcinomas. Proportion of epithelial tumor component and stroma were measured by a software tool, allowing the pathologists to mark 205.6 μm2 blocks on areas as carcinomatous/stromal, by clicking at the image. Totally, 3.451 mm2 tumor areas have been marked to 16.785 small square blocks for each case. Results: Median follow up was 48 months (range 3-194). The mean tumor-stroma proportion was 48.63+18.18. There was no difference for tumor-stroma proportion when tumor location, grade, stage and perinodal invasion were considered. Although the following results were statistically insignificant, the mean tumor-stroma proportion was the lowest (37.46±12.49) for subglottic carcinomas, and it was 52.41±37.47, 50.86+19.84 and 44.56±16.91 for supraglottic, transglottic and glottic cases. The tumor-stroma proportion was lowest in cases with perinodal invasion and the highest in cases without lymph node metastasis (44.72±20.23, 47.77±17.37, 50.05±17.34). Tumor-stroma proportion was higher in the basaloid subtype compared with the classical squamous cell carcinoma (53.76±14.70 and 48.63±18.38 respectively). The overall and disease-free survival analysis did not reveal significance for tumor-stroma proportion (p=0.08, p=0.38). Only pathological stage was an independent factor for overall survival (p=0.008). Conclusion: This is the first series investigating tumor-stroma proportion as a prognostic marker in laryngeal carcinomas proposing a new method, but the findings do not support tumor-stroma proportion as a prognostic marker.