TU Darmstadt / ULB / TUprints

Learning directed acyclic graphs from large-scale genomics data

Nikolay, Fabio ; Pesavento, Marius ; Kritikos, George ; Typas, Nassos (2017):
Learning directed acyclic graphs from large-scale genomics data.
In: EURASIP Journal on Bioinformatics and Systems Biology, 2017 (10), Springer Open, ISSN 1687-4153,

Copyright Information: CC BY 4.0 International - Creative Commons, Attribution.

Download (1MB) | Preview
Item Type: Article
Origin: Secondary publication via sponsored Golden Open Access
Title: Learning directed acyclic graphs from large-scale genomics data
Language: English

In this paper, we consider the problem of learning the genetic interaction map, i.e., the topology of a directed acyclic graph (DAG) of genetic interactions from noisy double-knockout (DK) data. Based on a set of well-established biological interaction models, we detect and classify the interactions between genes. We propose a novel linear integer optimization program called the Genetic-Interactions-Detector (GENIE) to identify the complex biological dependencies among genes and to compute the DAG topology that matches the DK measurements best. Furthermore, we extend the GENIE program by incorporating genetic interaction profile (GI-profile) data to further enhance the detection performance. In addition, we propose a sequential scalability technique for large sets of genes under study, in order to provide statistically significant results for real measurement data. Finally, we show via numeric simulations that the GENIE program and the GI-profile data extended GENIE (GI-GENIE) program clearly outperform the conventional techniques and present real data results for our proposed sequential scalability technique.

Journal or Publication Title: EURASIP Journal on Bioinformatics and Systems Biology
Volume of the journal: 2017
Issue Number: 10
Place of Publication: Darmstadt
Publisher: Springer Open
Classification DDC: 600 Technik, Medizin, angewandte Wissenschaften > 600 Technik
Divisions: 18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications > Communication Systems
Date Deposited: 26 Sep 2017 13:20
Last Modified: 13 Dec 2022 11:05
Corresponding Links:
URN: urn:nbn:de:tuda-tuprints-68294
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/6829
Actions (login required)
View Item View Item