Browsing by Author "Eser, Elif"

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Open Access
Diverse sequence search and alignment
(2013) Eser, Elif
Sequence similarity tools, such as BLAST, seek sequences from a database most similar to a query. They return results signi cantly similar to the query sequence that are typically also highly similar to each other. Most sequence analysis tasks in bioinformatics require an exploratory approach where the initial results guide the user to new searches. However, diversity has not been considered as an integral component of sequence search tools yet. Repetitions in the result can be avoided by introducing non-redundancy during database construction; however, it is not feasible to dynamically set a level of non-redundancy tailored to a query sequence. We introduce the problem of diverse search and browsing in sequence databases that produces non-redundant results optimized for any given query. We de ne diversity measures for sequences, and propose methods to obtain diverse results extracted from current sequence similarity search tools. We propose a new measure to evaluate the diversity of a set of sequences that is returned as a result of a similarity query. We evaluate the e ectiveness of the proposed methods in post-processing PSI-BLAST results. We also assess the functional diversity of the returned results based on available Gene Ontology annotations. Our experiments show that the proposed methods are able to achieve more diverse yet similar result sets compared to static non-redundancy approaches. In both sequence based and functional diversity evaluation, the proposed diversi cation methods outperform original BLAST results signi cantly. We built an online diverse sequence search tool Div-BLAST that supports queries using BLAST web services. It re-ranks the results diversely according to given parameters.
Open Access
Generating time-varying road network data using sparse trajectories
(IEEE, 2016-12) Eser, Elif; Kocayusufoğlu, F.; Eravci, Bahaedd; Ferhatosmanoglu, Hakan; Larriba-Pey, J. L.
While research on time-varying graphs has attracted recent attention, the research community has limited or no access to real datasets to develop effective algorithms and systems. Using noisy and sparse GPS traces from vehicles, we develop a time-varying road network data set where edge weights differ over time. We present our methodology and share this dataset, along with a graph manipulation tool. We estimate the traffic conditions using the sparse GPS data available by characterizing the sparsity issues and assessing the properties of travel sequence data frequency domain. We develop interpolation methods to complete the sparse data into a complete graph dataset with realistic time-varying edge values. We evaluate the performance of time-varying and static shortest path solutions over the generated dynamic road network. The shortest paths using the dynamic graph produce very different results than the static version. We provide an independent Java API and a graph database to analyze and manipulate the generated time-varying graph data easily, not requiring any knowledge about the inners of the graph database system. We expect our solution to support researchers to pursue problems of time-varying graphs in terms of theoretical, algorithmic, and systems aspects. The data and Java API are available at: http://elif.eser.bilkent.edu.tr/roadnetwork. © 2016 IEEE.
Open Access
On the Tracking of Dynamical Optimal Meeting Points
(Elsevier B.V., 2018) Eser, Elif; Monteil, J.; Simonetto, A.
Finding optimal meeting points on road networks is becoming more and more relevant with the growth of ride-sharing services. Optimal meeting points serve as locations where multiple vehicles can drop their passengers, which will then be pooled in one single (high capacity) vehicle to reach their common final destination. Finding good meeting points is then key in ensuring low travel times to the chosen location and therefore high quality of service. Optimal meeting points are hardy stationary, since variations on traffic conditions, road events, or drivers predispositions to go slower/faster than predicted could shift optimality from one location to another one continuously in time. In this paper, we propose online algorithms to find and track optimal meeting points in such dynamic scenarios, as well as a system architecture to enable extensive simulations for any selected network of interest. Our algorithms are an extension of existing static algorithms. First we integrate realistic considerations such as the finite number of drop-off locations and the proximity radius constant to avoid constant rerouting of vehicles. Second we adapt those algorithms to the dynamic case, which requires to address the trade-off between computational time and optimality. With the aid of extensive numerical simulations, we illustrate and discuss the effectiveness of each algorithm under different scenarios: static networks, dynamic congested networks and dynamic congested network subject to dynamic events.
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Türkiye’ye iadesi sağlanamayan arkeolojik eserler
(Bilkent University, 2015) Konor, Begüm; Eser, Elif; Nur Tozoğlu, Sena; Özerdem, Mert; Cığız, Emre