Browsing by Author "Alkan, Ferhat"

Now showing 1 - 4 of 4

Citation Count: 54
BEAMS: backbone extraction and merge strategy for the global many-to-many alignment of multiple PPI networks
(Oxford University Press, 2014) Erten, Cesim; Erten, Cesim
Motivation: Global many-to-many alignment of biological networks has been a central problem in comparative biological network studies. Given a set of biological interaction networks the informal goal is to group together related nodes. For the case of protein-protein interaction networks such groups are expected to form clusters of functionally orthologous proteins. Construction of such clusters for networks from different species may prove useful in determining evolutionary relationships in predicting the functions of proteins with unknown functions and in verifying those with estimated functions. Results: A central informal objective in constructing clusters of orthologous proteins is to guarantee that each cluster is composed of members with high homological similarity usually determined via sequence similarities and that the interactions of the proteins involved in the same cluster are conserved across the input networks. We provide a formal definition of the global many-to-many alignment of multiple protein-protein interaction networks that captures this informal objective. We show the computational intractability of the suggested definition. We provide a heuristic method based on backbone extraction and merge strategy (BEAMS) for the problem. We finally show through experiments based on biological significance tests that the proposed BEAMS algorithm performs better than the state-of-the-art approaches. Furthermore the computational burden of the BEAMS algorithm in terms of execution speed and memory requirements is more reasonable than the competing algorithms.
Global many- to - many aligment of multiple protein-protein interaction networks
(Kadir Has Üniversitesi, 2013) Alkan, Ferhat; Aşıcı, Tınaz Ekim
Proteins are essential parts of organisms and almost every biological process within a living cell is mediated by proteins and their interactions. Due to such importance, proteins are at the core of many researches in systems biology and evolutionary biology. In particular, defining the function of a protein and identfying functionally orthologous proteins are crucially important in many research areas and precise function of a protein can only be defined by biochemical and structural studies. However, many computational methods are also developed for such purposes and they use the sequence and interaction data of proteins since it provides a presumption about the chemical structure of a protein. For example, network alignment studies aims to find clusters of functionally related proteins across given protein interaction networks usually by implementing the given networks as graphs and employing some graph theoretical approaches. In this thesis, we focused on the problem of global many-to-many alignment of multiple protein-protein interaction networks. We define the problem as an optimization problem and this is the first combinatorial definition that is given for the problem in the literature. Then, we prove the computational intractability of this problem and we propose a new heurictic algorithm for the solution. We test the proposed algorithm BEAMS on both actual and synthetic PPI networks and it outperforms the existing algorithms, that serve at similar purpose, in terms of many evaluation aspects.
Citation Count: 7
RedNemo: topology-based PPI network reconstruction via repeated diffusion with neighborhood modifications
(Oxford University Press, 2017) Erten, Cesim; Erten, Cesim
Motivation: Analysis of protein-protein interaction (PPI) networks provides invaluable insight into several systems biology problems. High-throughput experimental techniques together with computational methods provide large-scale PPI networks. However a major issue with these networks is their erroneous nature
Citation Count: 9
SiPAN: simultaneous prediction and alignment of protein-protein interaction networks
(Oxford University Press, 2015) Erten, Cesim; Erten, Cesim
Motivation: Network prediction as applied to protein-protein interaction (PPI) networks has received considerable attention within the last decade. Because of the limitations of experimental techniques for interaction detection and network construction several computational methods for PPI network reconstruction and growth have been suggested. Such methods usually limit the scope of study to a single network employing data based on genomic context structure domain sequence information or existing network topology. Incorporating multiple species network data for network reconstruction and growth entails the design of novel models encompassing both network reconstruction and network alignment since the goal of network alignment is to provide functionally orthologous proteins from multiple networks and such orthology information can be used in guiding interolog transfers. However such an approach raises the classical chicken or egg problem