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Categoria WoS
  • Pharmacology & Pharmacy - Q1 - T1 - 63/256
Area
Titulo: Exploring patterns of epigenetic information with data mining techniques
Tipo: revista internacional
Fecha: 2,2013
Revista: Current Pharmaceutical Design. Special Issue: Epigenetic and metabolic drug target for anticancer therapy
JCR Journal; Impact Factor: 3.288
SCIMago SJR:
Citas ISI: 1 Citas Scopus: 2 Citas Google Scholar: 4
Paginas: 779-789
ISSN: 1381-6128
Editorial: Bentham Science Publishers
doi: 10.2174/138161213804581936
Pubmed ID: 23016855

Abstract:

Data mining, a part of the Knowledge Discovery in Databases process (KDD), is the process of extracting patterns from large data sets by combining methods from statistics and artificial intelligence with database management. Analyses of epigenetic data have evolved towards genome-wide and high-throughput approaches, thus generating great amounts of data for which data mining is essential. Part of these data may contain patterns of epigenetic information which are faithfully propagated over multiple cell divisions, making epigenetic regulation a key mechanism for cellular differentiation and cell fate decisions. In addition, incomplete erasure of epigenetic information can lead to complex patterns of non-Mendelian inheritance. Therefore, the previous patterns could be extracted with data mining techniques. This work reviews some of the most important applications of data mining to epigenetics.

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