ARNI: Abductive inference of complex regulatory network structures
dc.contributor.author | Maimari, N. | en |
dc.contributor.author | Turliuc, C. -R | en |
dc.contributor.author | Broda, K. | en |
dc.contributor.author | Kakas, Antonis C. | en |
dc.contributor.author | Krams, R. | en |
dc.contributor.author | Russo, A. | en |
dc.creator | Maimari, N. | en |
dc.creator | Turliuc, C. -R | en |
dc.creator | Broda, K. | en |
dc.creator | Kakas, Antonis C. | en |
dc.creator | Krams, R. | en |
dc.creator | Russo, A. | en |
dc.date.accessioned | 2019-11-13T10:41:09Z | |
dc.date.available | 2019-11-13T10:41:09Z | |
dc.date.issued | 2013 | |
dc.identifier.issn | 0302-9743 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/54475 | |
dc.description.abstract | Physical network inference methods use a template of molecular interaction to infer biological networks from high throughput datasets. Current inference methods have limited applicability, relying on cause-effect pairs or systematically perturbed datasets and fail to capture complex network structures. Here we present a novel framework, ARNI, based on abductive inference, that addresses these limitations. © Springer-Verlag 2013. | en |
dc.source | 11th International Conference on Computational Methods in Systems Biology, CMSB 2013 | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84885966995&partnerID=40&md5=8a170f09150d12728f736ce41bd04a1c | |
dc.subject | Computational methods | en |
dc.subject | Artificial intelligence | en |
dc.subject | Computer science | en |
dc.subject | Network structures | en |
dc.subject | Gene networks | en |
dc.subject | Abductive inference | en |
dc.subject | Biological networks | en |
dc.subject | Complex regulatory network | en |
dc.subject | Inference methods | en |
dc.subject | Logic-based modeling | en |
dc.subject | Physical network | en |
dc.title | ARNI: Abductive inference of complex regulatory network structures | en |
dc.type | info:eu-repo/semantics/article | |
dc.description.volume | 8130 LNBI | en |
dc.description.startingpage | 235 | |
dc.description.endingpage | 237 | |
dc.author.faculty | 002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences | |
dc.author.department | Τμήμα Πληροφορικής / Department of Computer Science | |
dc.type.uhtype | Article | en |
dc.description.notes | <p>Conference code: 100084</p> | en |
dc.source.abbreviation | Lect. Notes Comput. Sci. | en |
dc.contributor.orcid | Kakas, Antonis C. [0000-0001-6773-3944] | |
dc.gnosis.orcid | 0000-0001-6773-3944 |
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