| URL: | http://dataome.mensxmachina.org/ |
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| Description: | BioDataome is a database of uniformly preprocessed and disease-annotated omics data with the aim to promote and accelerate the reuse of public data.Currently, BioDataome includes ∼5600 datasets, ∼260 000 samples spanning ∼500 diseases and can be easily used in large-scale massive experiments and meta-analysis. |
| Year founded: | 2018 |
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| Accessibility: |
Accessible
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| Country/Region: | Greece |
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| University/Institution: | University of Crete |
| Address: | University of Crete, Voutes Campus, 70013 Heraklion, Crete, Greece |
| City: | Heraklion |
| Province/State: | Crete |
| Country/Region: | Greece |
| Contact name (PI/Team): | Kleanthi Lakiotaki |
| Contact email (PI/Helpdesk): | kliolak@gmail.com |
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BioDataome: a collection of uniformly preprocessed and automatically annotated datasets for data-driven biology. [PMID: 29688366]
Biotechnology revolution generates a plethora of omics data with an exponential growth pace. Therefore, biological data mining demands automatic, 'high quality' curation efforts to organize biomedical knowledge into online databases. BioDataome is a database of uniformly preprocessed and disease-annotated omics data with the aim to promote and accelerate the reuse of public data. We followed the same preprocessing pipeline for each biological mart (microarray gene expression, RNA-Seq gene expression and DNA methylation) to produce ready for downstream analysis datasets and automatically annotated them with disease-ontology terms. We also designate datasets that share common samples and automatically discover control samples in case-control studies. Currently, BioDataome includes ∼5600 datasets, ∼260 000 samples spanning ∼500 diseases and can be easily used in large-scale massive experiments and meta-analysis. All datasets are publicly available for querying and downloading via BioDataome web application. We demonstrate BioDataome's utility by presenting exploratory data analysis examples. We have also developed BioDataome R package found in: https://github.com/mensxmachina/BioDataome/.Database URL: http://dataome.mensxmachina.org/. |