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Deposit, archive and share your final research data in DR-NTU (Data)

DR-NTU (Data) is for research data deposit. For research paper deposits, please use DR-NTU.

Mission: DR-NTU (Data) curates, stores, preserves, makes available and enables the download of digital data generated by the NTU research community. The repository develops and provides guidance for managing, sharing, and reusing research data to promote responsible data sharing in support of open science and research integrity.

Who can deposit? NTU faculty, research staff and students.

What can be deposited? Final, non-sensitive research data from projects carried out at NTU. The uploaded content must not infringe upon the copyrights or other intellectual property rights, and must be void of all identifiable information.

How to deposit?

Useful links: FAQs | Collection Guidelines | NTU Research Data Management | General terms of use and Privacy policy

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71,941 to 71,950 of 73,632 Results
Adobe PDF - 147.7 KB - MD5: 1424b8ab1a7767cb584a8a749089216a
Koh, Kovic & Styles 2019. Preregistration for crossmodal influences between size and pitch in book reading for children in Singapore. CC-BY
Peter Preiser(Nanyang Technological University)
Peter Preiser logo
May 13, 2019School of Biological Sciences (SBS)
Research topics: His research interests focus on the molecular mechanisms by which the malaria parasite is able to avoid host immunity and adapt to changes in the host cell environment. One of the main problems in developing an efficient malaria vaccine is the ability of the para...
Francesc Xavier Roca Castella (Nanyang Technological University)
Francesc Xavier Roca Castella  logo
May 9, 2019School of Biological Sciences (SBS)
Research topics: • focus on the study of the mechanisms of pre-messenger RNA splicing in human cells • identify new therapeutic targets, and/or to develop RNA-based therapies for human diseases
May 3, 2019 - Oliver Martin MUELLER-CAJAR
Mueller-Cajar, Oliver Martin, 2019, "Data relating to Wunder et al., Nature Communications (2018)", https://doi.org/10.21979/N9/RM7TRL, DR-NTU (Data), V1
This dataset provides raw gel images analyzed to support the findings reported in Wunder et al. 2018.
Adobe PDF - 822.9 KB - MD5: a99cb507d4e00d9037afcdc8f9df223e
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