Bilgisayar Mühendisliği Bölümü Koleksiyonu

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Browsing Bilgisayar Mühendisliği Bölümü Koleksiyonu by Author "Aladağ, Ahmet Emre"

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    An integrated model for visualizing biclusters from gene expression data and PPI networks
    (2010) Erten, Cesim; Erten, Cesim; Sözdinler, Melih
    We provide a model to integrate the visualization of biclusters extracted from gene expresion data and the underlying PPI networks. Such an integration conveys the biologically relevant interconnection between these two structures inferred from biological experiments. We model the reliabilities of the structures using directed graphs with vertex and edge weights. The resulting graphs are drawn using appropriate weighted modifications of the algorithms necessary for the layered drawings of directed graphs. We provide applications of the proposed visualization model on the S. cerevisiae dataset. Copyright 2010 ACM.
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    Article
    Citation Count: 1
    Reliability-Oriented bioinformatic networks visualization
    (Oxford University Press, 2011) Erten, Cesim; Erten, Cesim; Sözdinler, Melih
    We present our protein-protein interaction (PPI) network visualization system RobinViz (reliability-oriented bioinformatic networks visualization). Clustering the PPI network based on gene ontology (GO) annotations or biclustered gene expression data providing a clustered visualization model based on a central/peripheral duality computing layouts with algorithms specialized for interaction reliabilities represented as weights completely automated data acquisition processing are notable features of the system.
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    Article
    Citation Count: 93
    SPINAL: scalable protein interaction network alignment
    (Oxford University Press, 2013) Erten, Cesim; Erten, Cesim
    Motivation: Given protein-protein interaction (PPI) networks of a pair of species a pairwise global alignment corresponds to a one-to-one mapping between their proteins. Based on the presupposition that such a mapping provides pairs of functionally orthologous proteins accurately the results of the alignment may then be used in comparative systems biology problems such as function prediction/verification or construction of evolutionary relationships. Results: We show that the problem is NP-hard even for the case where the pair of networks are simply paths. We next provide a polynomial time heuristic algorithm SPINAL which consists of two main phases. In the first coarse-grained alignment phase we construct all pairwise initial similarity scores based on pairwise local neighborhood matchings. Using the produced similarity scores the fine-grained alignment phase produces the final one-to-one mapping by iteratively growing a locally improved solution subset. Both phases make use of the construction of neighborhood bipartite graphs and the contributors as a common primitive. We assess the performance of our algorithm on the PPI networks of yeast fly human and worm. We show that based on the accuracy measures used in relevant work our method outperforms the state-of-the-art algorithms. Furthermore our algorithm does not suffer from scalability issues as such accurate results are achieved in reasonable running times as compared with the benchmark algorithms.