title: The landscape for epigenetic/epigenomic biomedical resources.
abstract: Recent advances in molecular biology and computational power have seen the biomedical sector enter a new era, with corresponding development of Bioinformatics as a major discipline. Generation of enormous amounts of data has driven the need for more advanced storage solutions and shared access through a range of public repositories. The number of such biomedical resources is increasing constantly and mining these large and diverse data sets continues to present real challenges. This paper attempts a general overview of currently available resources, together with remarks on their data mining and analysis capabilities. Of interest here is the recent shift in focus from genetic to epigenetic/epigenomic research and the emergence and extension of resource provision to support this both at local and global scale. Biomedical text and numerical data mining are both considered, the first dealing with automated methods for analyzing research content and information extraction, and the second (broadly) with pattern recognition and prediction. Any summary and selection of resources is inherently limited, given the spectrum available, but the aim is to provide a guideline for the assessment and comparison of currently available provision, particularly as this relates to epigenetics/epigenomics.
authors.affiliation: Centre for Scientific Computing & Complex Systems Modelling (SCI-SYM), School of Computing, Dublin City University, Dublin, Ireland. kabita.shakya@gmail.com
authors.forename: Kabita
authors.initials: K
authors.lastname: Shakya
authors.forename: Mary J
authors.initials: MJ
authors.lastname: O'Connell
authors.forename: Heather J
authors.initials: HJ
authors.lastname: Ruskin
mesh_terms: D019295:Computational Biology; D057225:Data Mining; D030541:Databases, Genetic; D057890:Epigenomics