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Mining gene expression profiles and gene regulatory networks: Identification ofphenotype‐specific molecular mechanisms

Moustakis Vasilis, Alexandros Kanterakis, Dimitris Kafetzopoulos, George Potamias

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URIhttp://purl.tuc.gr/dl/dias/0641BD16-3E72-4C2C-9230-4B9DA8752C1F-
Αναγνωριστικόhttps://doi.org/10.1007/978-3-540-87881-0_10-
Γλώσσαen-
ΤίτλοςMining gene expression profiles and gene regulatory networks: Identification of phenotype‐specific molecular mechanismsen
ΔημιουργόςMoustakis Vasilisen
ΔημιουργόςΜουστακης Βασιληςel
ΔημιουργόςAlexandros Kanterakisen
ΔημιουργόςDimitris Kafetzopoulosen
ΔημιουργόςGeorge Potamiasen
ΕκδότηςSpringer Verlagen
ΠερίληψηThe complex regulatory mechanisms of genes and their transcription are the major gene regulatory steps in the cell. Gene Regulatory Networks (GRNs) and DNA Microarrays (MAs) present two of the most prominent and heavily researched concepts in contemporary molecular biology and bioinformatics. The challenge in contemporary biomedical informatics research lies in systems biology - the linking of various pillars of heterogeneous data so they can be used in synergy for life science research. Faced with this challenge we devised and present an integrated methodology that ‘amalgamates’ knowledge and data from both GRNs and MA gene expression sources. The methodology, is able to identify phenotype-specific GRN functional paths, and aims to uncover potential gene-regulatory ‘fingerprints’ and molecular mechanisms that govern the genomic profiles of diseases. Initial implementation and experimental results on a real-world breast-cancer study demonstrate the suitability and reliability of the approach.en
ΤύποςΑφίσα σε Συνέδριοel
ΤύποςConference Posteren
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2015-11-03-
Ημερομηνία Δημοσίευσης2008-
Βιβλιογραφική ΑναφοράA. Kanterakis, D. Kafetzopoulos, V. Moustakis, G. Potamias. "Mining Gene Expression Profiles and Gene Regulatory Networks: Identification of Phenotype‐Specific Molecular Mechanisms," in Theories, Models and Applications: 5th Hellenic Conference of AI Proceedings. 2008, pp. 97-109. doi: 10.1007/978-3-540-87881-0_10en

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