Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Citation - WoS: 30Machine Learning Methods for Microrna Gene Prediction(Humana Press, 2014) Saçar, Müşerref Duygu; Allmer, JensMicroRNAs (miRNAs) are single-stranded, small, noncoding RNAs of about 22 nucleotides in length, which control gene expression at the posttranscriptional level through translational inhibition, degradation, adenylation, or destabilization of their target mRNAs. Although hundreds of miRNAs have been identified in various species, many more may still remain unknown. Therefore, discovery of new miRNA genes is an important step for understanding miRNA-mediated posttranscriptional regulation mechanisms. It seems that biological approaches to identify miRNA genes might be limited in their ability to detect rare miRNAs and are further limited to the tissues examined and the developmental stage of the organism under examination. These limitations have led to the development of sophisticated computational approaches attempting to identify possible miRNAs in silico. In this chapter, we discuss computational problems in miRNA prediction studies and review some of the many machine learning methods that have been tried to address the issues.Article Citation - WoS: 3Citation - Scopus: 3Extended Void Merging Tree Algorithm for Self-Similar Models(Oxford University Press, 2014) Russell, EsraIn hierarchical evolution, voids exhibit two different behaviours related with their surroundings and environments, they can merge or collapse. These two different types of void processes can be described by the two-barrier excursion set formalism based on Brownian random walks. In this study, the analytical approximate description of the growing void merging algorithm is extended by taking into account the contributions of voids that are embedded into overdense region(s) which are destined to vanish due to gravitational collapse. Following this, to construct a realistic void merging model that consists of both collapse and merging processes, the twobarrier excursion set formalism of the void population is used. Assuming spherical voids in the Einstein-de Sitter Universe, the void merging algorithm which allows us to consider the two main processes of void hierarchy in one formalism is constructed. In addition to this, the merger rates, void survival probabilities, void size distributions in terms of the collapse barrier and finally, the void merging tree algorithm in the self-similar models are defined and derived.Article Citation - WoS: 21Citation - Scopus: 61Studies of Jet Mass in Dijet and W/Z + Jet Events(Springer Verlag, 2013) CMS Collaboration; Karapınar, GülerInvariant mass spectra for jets reconstructed using the anti-k T and CambridgeAachen algorithms are studied for different jet "grooming" techniques in data corresponding to an integrated luminosity of 5 fb-1, recorded with the CMS detector in proton-proton collisions at the LHC at a center-of-mass energy of 7 TeV. Leading-order QCD predictions for inclusive dijet and W/Z+jet production combined with parton-shower Monte Carlo models are found to agree overall with the data, and the agreement improves with the implementation of jet grooming methods used to distinguish merged jets of large transverse momentum from softer QCD gluon radiation. © 2013 CERN for the benefit of the CMS collaboration.Article Citation - WoS: 15Citation - Scopus: 19Campways: Constrained Alignment Framework for the Comparative Analysis of a Pair of Metabolic Pathways(Oxford University Press, 2013) Abaka, Gamze; Bıyıkoğlu, Türker; Erten, CesimMotivation: Given a pair of metabolic pathways, an alignment of the pathways corresponds to a mapping between similar substructures of the pair. Successful alignments may provide useful applications in phylogenetic tree reconstruction, drug design and overall may enhance our understanding of cellular metabolism.Results: We consider the problem of providing one-to-many alignments of reactions in a pair of metabolic pathways. We first provide a constrained alignment framework applicable to the problem. We show that the constrained alignment problem even in a primitive setting is computationally intractable, which justifies efforts for designing efficient heuristics. We present our Constrained Alignment of Metabolic Pathways (CAMPways) algorithm designed for this purpose. Through extensive experiments involving a large pathway database, we demonstrate that when compared with a state-of-the-art alternative, the CAMPways algorithm provides better alignment results on metabolic networks as far as measures based on same-pathway inclusion and biochemical significance are concerned. The execution speed of our algorithm constitutes yet another important improvement over alternative algorithms. © The Author 2013.Conference Object Citation - Scopus: 5Performance Comparison of Combined Collaborative Filtering Algorithms for Recommender Systems(Institute of Electrical and Electronics Engineers Inc., 2012) Tapucu, Dilek; Kasap, Seda; Tekbacak, FatihRecommender systems have a goal to make personalized recommendations by using filtering algorithms. Collaborative filtering (CF) is one of the most popular techniques for recommender systems. As usual, huge number of the datasets on the Internet increase the amount of time to work on data. This challenge enforces people to improve better algorithms for processing data with user preferences and recommending the most appropriate item to the users. In this paper, we analyze CF algorithms and present results for combined user-based/item-based CF algorithms for different size of datasets. Our goal is to show combined solution results using Loglikelihood, Spearman, Tanimoto and Pearson algorithms. The contribution is to describe which user based CF algorithms and user/item based combined CF algorithms perform better according to dataset, sparsity, execution time and k-neighborhood values. © 2012 IEEE.Conference Object Citation - Scopus: 2Hiding Sensitive Predictive Frequent Itemsets(International Association of Engineers, 2011) Yıldız, Barış; Ergenç, BelginIn this work, we propose an itemset hiding algorithm with four versions that use different heuristics in selecting the item in itemset and the transaction for distortion. The main strengths of itemset hiding algorithm can be stated as i) it works without pre-mining so privacy breech caused by revealing frequent itemsets in advance is prevented and efficiency is increased, ii) base algorithm (Matrix-Apriori) works without candidate generation so efficiency is increased, iii) sanitized database and frequent itemsets of this database are given as outputs so no post-mining is required and iv) simple heuristics like the length of the pattern and the frequency of the item in the pattern are used for selecting the item for distortion. We compare versions of our itemset hiding algorithm by their side effects, runtimes and distortion on original database.Article Citation - WoS: 15Citation - Scopus: 17Genetic Algorithm-Based Discharge Estimation at Sites Receiving Lateral Inflows(American Society of Civil Engineers (ASCE), 2009) Tayfur, Gökmen; Barbetta, Silvia; Moramarco, TommasoThe genetic algorithm (GA) technique is applied to obtain optimal parameter values of the standard rating curve model (RCM) for predicting, in real time, event-based flow discharge hydrographs at sites receiving significant lateral inflows. The standard RCM uses the information of discharge and effective cross-sectional flow area at an upstream station and effective cross-sectional flow area wave travel time later at a downstream station to predict the flow rate at this last site. The GA technique obtains the optimal parameter values of the model, here defined as the GA-RCM model, by minimizing the mean absolute error objective function. The GA-RCM model was tested to predict hydrographs at three different stations, located on the Upper Tiber River in central Italy. The wave travel times characterizing the three selected river branches are, on the average, 4, 8, and 12h. For each river reach, seven events were employed, four for the model parameters' calibration and three for model testing. The GA approach, employing 100 chromosomes in the initial gene pool, 75% crossover rate, 5% mutation rate, and 10,000 iterations, made the GA-RCM model successfully simulate the hydrographs observed at each downstream section closely capturing the trend, time to peak, and peak rates with, on the average, less than 5% error. The model performance was also tested against the standard RCM model, which uses, on the contrary to the GA-RCM model, different values for the model parameters and wave travel time for each event, thus, making the application of the standard RCM for real time discharge monitoring inhibited. The comparative results revealed that the RCM model improved its performance by using the GA technique in estimating parameters. The sensitivity analysis results revealed that at most two events would be sufficient for the GA-RCM model to obtain the optimal values of the model parameters. A lower peak hydrograph can also be employed in the calibration to predict a higher peak hydrograph. Similarly, a shorter travel time hydrograph can be used in GA to obtain optimal model parameters that can be used to simulate floods characterized by longer travel time. For its characteristics, the GA-RCM model is suitable for the monitoring of discharge in real time, at river sites where only water levels are observed.Conference Object Citation - WoS: 6Citation - Scopus: 6A Merging Clustering Algorithm for Mobile Ad Hoc Networks(Springer Verlag, 2006) Dağdeviren, Orhan; Erciyeş, Kayhan; Çokuslu, DenizClustering is a widely used approach to ease implementation of various problems such as routing and resource management in mobile ad hoc networks (MANET)s. We propose a new fully distributed algorithm for clustering in MANETs that merges clusters to form higher level clusters by increasing their levels. We show the operation of the algorithm and analyze its time and message complexities and provide results in the simulation environment of ns2. Our results conform that the algorithm proposed is scalable and has a lower time and message complexities than the other algorithmsConference Object Citation - WoS: 8Citation - Scopus: 13A Distributed Backbone Formation Algorithm for Mobile Ad Hoc Networks(Springer Verlag, 2006) Dağdeviren, Orhan; Erciyeş, KayhanConstruction of a backbone architecture is an important issue in mobile ad hoc networks(MANET)s to ease routing and resource management. We propose a new fully distributed algorithm for backbone formation in MANETs that constructs a directed ring architecture. We show the operation of the algorithm, analyze its message complexity and provide results in the simulation environment of ns2. Our results conform that the algorithm is scalable in terms of its running time and roundtrip delay against mobility, surface area, number of nodes and number of clusterheads.Conference Object Citation - WoS: 3Citation - Scopus: 5Serial and Parallel Multilevel Graph Partitioning Using Fixed Centers(Springer Verlag, 2005) Erciyeş, Kayhan; Alp, Ali; Marshall, GeoffreyWe present new serial and parallel algorithms for multilevel graph partitioning. Our algorithm has coarsening, partitioning and uncoarsening phases like other multilevel partitioning methods. However, we choose fixed nodes which are at least a specified distance away from each other and coarsen them with their neighbor nodes in the coarsening phase using various heuristics. Using this algorithm, it is possible to obtain theoretically and experimentally much more balanced partitions with substantially decreased total edge costs between the partitions than other algorithms. We also developed a parallel method for the fixed centered partitioning algorithm. It is shown that parallel fixed centered partitioning obtains significant speedups compared to the serial case.