A signal transduction score flow algorithm for cyclic cellular pathway analysis, which combines transcriptome and ChIP-seq data

Download

index.pdf

Date

2012-01-01

Author

Isik, Zerrin
Ersahin, Tulin
Atalay, Mehmet Volkan
AYKANAT, CEVDET
Atalay, Rengül

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

137
views

0
downloads

Determination of cell signalling behaviour is crucial for understanding the physiological response to a specific stimulus or drug treatment. Current approaches for large-scale data analysis do not effectively incorporate critical topological information provided by the signalling network. We herein describe a novel model- and data-driven hybrid approach, or signal transduction score flow algorithm, which allows quantitative visualization of cyclic cell signalling pathways that lead to ultimate cell responses such as survival, migration or death. This score flow algorithm translates signalling pathways as a directed graph and maps experimental data, including negative and positive feedbacks, onto gene nodes as scores, which then computationally traverse the signalling pathway until a pre-defined biological target response is attained. Initially, experimental data-driven enrichment scores of the genes were computed in a pathway, then a heuristic approach was applied using the gene score partition as a solution for protein node stoichiometry during dynamic scoring of the pathway of interest. Incorporation of a score partition during the signal flow and cyclic feedback loops in the signalling pathway significantly improves the usefulness of this model, as compared to other approaches. Evaluation of the score flow algorithm using both transcriptome and ChIP-seq data-generated signalling pathways showed good correlation with expected cellular behaviour on both KEGG and manually generated pathways. Implementation of the algorithm as a Cytoscape plug-in allows interactive visualization and analysis of KEGG pathways as well as user-generated and curated Cytoscape pathways. Moreover, the algorithm accurately predicts gene-level and global impacts of single or multiple in silica gene knockouts.

Subject Keywords

Collaboratıve constructıon, Expression data, Cancer, Microarray, Tool, Networks, Deregulation, Environment, Ontology, Receptor

URI

https://hdl.handle.net/11511/39543

Journal

MOLECULAR BIOSYSTEMS

DOI

https://doi.org/10.1039/c2mb25215e

Collections

Department of Computer Engineering, Article

Suggestions

OpenMETU
Core

A Plasmonic method for the determination of serotonin Avcı, Begüm; Volkan, Mürvet; Department of Chemistry (2019) Serotonin is an important neurotransmitter for regulating many cognitive and behavioral functions. Its abnormal levels have been related with various diseases hence the determination of the serotonin is very important. Sialic acid is mostly found in acidic glycan chains, glycolipids and glycoproteins and it is known to have a specific affinity for serotonin. In this study, determination of serotonin by using plasmonic property of gold nanoparticles was aimed. After synthesizing gold nanoparticles through si...
A biophysical network model displaying the role of basal ganglia pathways in action selection Yucelgen, Cem; Denizdurduran, Berat; Metin, Selin; Elibol, Rahmi; Şengör, Neslihan Serap (2012-10-25) Basal ganglia circuits are known to have role in a wide range of behaviour spanning from movement initiation to high order cognitive processes as reward related learning. Here, the intention is to have a biophysically realistic model of basal ganglia circuit for voluntary motor action selection. The ultimate aim is to provide a framework for models which could help comprehension of complex processes. To fulfill this aim a model capable of simulating direct, indirect and hyperdirect pathways with modified Ho...
A Lab-on-a-chip system integrating dielectrophoretic detection and impedance counting units for chemotherapy guidance in leukemia Demircan Yalçın, Yağmur; Külah, Haluk; Department of Electrical and Electronics Engineering (2018) Precision medicine is defined as therapies, directed to the requirements of individual patients on the basis of genetic, biomarker, phenotypic, or psychosocial characteristics, discriminating a given patient from others with similar clinical states. Oncology is the foremost application area of precision medicine. Although the aim of precision medicine is very clear and simple, the clinical practice of it in cancer patients has some challenges, such as tumor heterogeneity. Tumor heterogeneity can be the most...
A computational model to investigate the effect of dopamine on neural synchronization in striatum Elibol, Rahmi; Şengör, Neslihan Serap (2015-09-28) © 2015 IEEE.Synchronous behavior of neural populations has been related to cognitive processes as attention, learning and has been considered as hallmarks of neurological disorders. The computational models of neural structures, even the simple ones, could give informative results which can improve our understanding of cognitive processes, arising due to collective activity of neurons. Here, a neurocomputational model for investigating the role of dopamine level on the synchronized behavior of medium spiny ...
A Bayesian modeling and estimation framework for pharmacogenomics driven warfaring dosing Öztaner, Serdar Murat; Taşkaya Temizel, Tuğba; Erdem, Remzi; Department of Medical Informatics (2014) Recent studies have shown that the incorporation of genomics information into the drug dosing prediction formulations increases the accuracy of the drug dosing while decreasing the frequency of adverse drug effects. The current clinical approaches for drug dosing which are supported by the best pharmacogenomics algorithms explain only some percentage of the variance in dosing. The main objective of this study is to enhance the accuracy and efficacy of the warfarin dosing algorithms by using advanced methods...

Citation Formats

Z. Isik, T. Ersahin, M. V. Atalay, C. AYKANAT, and R. Atalay, “A signal transduction score flow algorithm for cyclic cellular pathway analysis, which combines transcriptome and ChIP-seq data,” MOLECULAR BIOSYSTEMS, pp. 3224–3231, 2012, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/39543.