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Found 4 result(s)

Huygens ING

Huygens Instituut voor Nederlandse Geschiedenis

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By stimulating inspiring research and producing innovative tools, Huygens ING intends to open up old and inaccessible sources, and to understand them better. Huygens ING’s focus is on Digital Humanities, History, History of Science, and Textual Scholarship. Huygens ING pursues research in the fields of History, Literary Studies, the History of Science and Digital Humanities. Huygens ING aims to publish digital sources and data responsibly and with care. Innovative tools are made as widely available as possible. We strive to share the available knowledge at the institute with both academic peers and the wider public.

Dutch Trial Register

formerly: Netherlands Trial Register

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The Dutch Trial Register (LTR) is a register in which a part of the clinical studies in The Netherlands are registered. This currently includes all data from the former National Trial Register (NTR).

Rotterdam Ophthalmic Data Repository

ROD-REP

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The Rotterdam Ophthalmic Data Repository (ROD-Rep) contains data sets related to ophthalmology that the Rotterdam Ophthalmic Institute has made freely available for researchers worldwide. This portal is an initiative of the Rotterdam Ophthalmic Institute, which is the research institute of the Rotterdam Eye Hospital. It provides the datasets from ophthalmic research (includes measurements such as visual fields and various imaging modalities, grades, etc.) for sharing and re-use to accelerate multi-disciplinary research, resulting in better ophthalmic care. The portal is the successor of the ORGIDS (or Open Rotterdam Glaucoma Imaging Data Sets site); which was an initiative of Koen Vermeer, Hans Lemij and Netty Dorrestijn and initial financial support was provided by Stichting Glaucoomfonds (The Netherlands).

PSnpBind

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PSnpBind is a large database of protein–ligand complexes covering a wide range of binding pocket mutations and small molecules’ landscape. This database can be used as a source of data for different types of studies, for example, developing machine learning algorithms to predict protein–ligand affinity or mutation's effect on it which requires an extensive amount of data with a wide coverage of mutation types and small molecules. Also, studies of protein-ligand interactions and conformer orientation changes across different mutated versions of a protein can be established using data from PSnpBind.