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Biomaterials. 2017 Dec;149:88-97. doi: 10.1016/j.biomaterials.2017.10.008. Epub 2017 Oct 3.

cBiT: A transcriptomics database for innovative biomaterial engineering.

Author information

1
MERLN Institute for Technology-inspired Regenerative Medicine, Maastricht University, Universiteitssingel 40, 6229 ER, Maastricht, The Netherlands. Electronic address: d.hebels@maastrichtuniversity.nl.
2
MERLN Institute for Technology-inspired Regenerative Medicine, Maastricht University, Universiteitssingel 40, 6229 ER, Maastricht, The Netherlands.
3
DataHub, Maastricht University & Maastricht UMC+, P. Debyelaan 15, 6229 HX, Maastricht, The Netherlands.

Abstract

Creating biomaterials that are suited for clinical application is still hampered by a lack of understanding of the interaction between a cell and the biomaterial surface it grows on. This surface communication can strongly impact cellular behavior, which in turn affects the chances of a successful interaction between a material and the host tissue. Transcriptomics data have previously been linked to measurements of biomaterial properties in order to explain the biological mechanisms underlying these cell-biomaterial interactions. However, such multi-assay data are highly complex and therefore require careful and unambiguous characterization and storage. Failure to do so may result in loss of valuable data or erroneous data analysis. In order to start a new initiative that tackles these issues and offers a platform for innovative biomaterial development, we have created a publically accessible repository called The Compendium for Biomaterial Transcriptomics (cBiT, https://cbit.maastrichtuniversity.nl). cBiT is a data warehouse that gives users the opportunity to search through biomaterial-based transcriptomics data sets using a web interface. Data of interest can be selected and downloaded, together with associated measurements of material properties. Researchers are also invited to add their data to cBiT in order to further enhance its scientific value. We aim to make cBiT the hub for biomaterial-associated data, thereby enabling major contributions to a more efficient development of new materials with improved body integration. Here, we describe the structure of cBiT and provide a use case with clinically applied materials to demonstrate how cBiT can be used to correlate data across transcriptomics studies.

KEYWORDS:

Biomaterials; Compendium; Data analysis; Database; Repository; Reverse engineering; Transcriptomics

[Indexed for MEDLINE]

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