Scalable approach for effective control of gene regulatory networks

Tan, Mehmet
Alhajj, Reda
Polat, Faruk
Objective: Interactions between genes are realized as gene regulatory networks (GRNs). The control of such networks is essential for investigating issues like different diseases. Control is the process of studying the states and behavior of a given system under different conditions. The system considered in this study is a gene regulatory network (GRN), and one of the most important aspects in the control of GRNs is scalability. Consequently, the objective of this study is to develop a scalable technique that facilitates the control of GRNs.


Effective gene expression data generation framework based on multi-model approach
Sirin, Utku; Erdogdu, Utku; Polat, Faruk; TAN, MEHMET; Alhajj, Reda (Elsevier BV, 2016-06-01)
Objective: Overcome the lack of enough samples in gene expression data sets having thousands of genes but a small number of samples challenging the computational methods using them.
Integer linear programming based solutions for construction of biological networks
Eren Özsoy, Öykü; Can, Tolga; Department of Health Informatics (2014)
Inference of gene regulatory or signaling networks from perturbation experiments and gene expression assays is one of the challenging problems in bioinformatics. Recently, the inference problem has been formulated as a reference network editing problem and it has been show that finding the minimum number of edit operations on a reference network in order to comply with perturbation experiments is an NP-complete problem. In this dissertation, we propose linear programming based solutions for reconstruction o...
Toroslu, İsmail Hakkı; HENSCHEN, L (Springer Science and Business Media LLC, 1994-05-01)
The integration of logic rules and relational databases has recently emerged as an important technique for developing knowledge management systems. An important class of logic rules utilized by these systems is the so-called transitive closure rules, the processing of which requires the computation of the transitive closure of database relations referenced by these rules. This article presents a new algorithm suitable for computing the transitive closure of very large database relations. This algorithm proc...
Inference of Gene Regulatory Networks Via Multiple Data Sources and a Recommendation Method
Ozsoy, Makbule Gulcin; Polat, Faruk; Alhajj, Reda (2015-11-12)
Gene regulatory networks (GRNs) are composed of biological components, including genes, proteins and metabolites, and their interactions. In general, computational methods are used to infer the connections among these components. However, computational methods should take into account the general features of the GRNs, which are sparseness, scale-free topology, modularity and structure of the inferred networks. In this work, observing the common aspects between recommendation systems and GRNs, we decided to ...
Functional characterization of microrna-125b expression in MCF7 breast cancer cell line
Tuna, Serkan; Erson Bensan, Ayşe Elif; Department of Biology (2010)
microRNA dependent gene expression regulation has roles in diverse processes such as differentiation, proliferation and apoptosis. Therefore, deregulated miRNA expression has functional importance for various diseases, including cancer. miR-125b is among the commonly downregulated miRNAs in breast cancer cells . Therefore we aimed to characterize the effects of miR-125b expression in MCF7 breast cancer cell line (BCCL) to better understand its roles in tumorigenesis. Here, we investigated mir-125 family mem...
Citation Formats
M. Tan, R. Alhajj, and F. Polat, “Scalable approach for effective control of gene regulatory networks,” ARTIFICIAL INTELLIGENCE IN MEDICINE, pp. 51–59, 2010, Accessed: 00, 2020. [Online]. Available: