Year: 2019
Type: data-paper
Abstract: Alzheimer's disease and other types of dementia are the top cause for disabilities in later life and various types of experiments have been performed to understand the underlying mechanisms of the disease with the aim of coming up with potential drug targets. These experiments have been carried out by scientists working in different domains such as proteomics, molecular biology, clinical diagnostics and genomics. The results of such experiments are stored in the databases designed for collecting data of similar types. However, in order to get a systematic view of the disease from these independent but complementary data sets, it is necessary to combine them. In this study we describe a heterogeneous network-based data set for Alzheimer's disease (HENA). Additionally, we demonstrate the application of state-of-the-art graph convolutional networks, i.e. deep learning methods for the analysis of such large heterogeneous biological data sets. We expect HENA to allow scientists to explore and analyze their own results in the broader context of Alzheimer's disease research.
Source: Scientific Data
Institutions: Quretec (Estonia), University of Tartu, SIB Swiss Institute of Bioinformatics, Commonwealth Scientific and Industrial Research Organisation, Data61, Hybrigenics (France), Université Paris-Sud, École Normale Supérieure Paris-Saclay, Centre National de la Recherche Scientifique, Inserm, Université Paris-Saclay, Laboratoire Aimé Cotton, Centre for Psychiatry and Neuroscience, Institut Pasteur, Biologie du Développement et Cellules Souches, Institut de génétique et de biologie moléculaire et cellulaire, Phénotypage et ingénierie précliniques des systèmes d’organismes modèles, Institut Pasteur de Lille, European Bioinformatics Institute, Wellcome Trust, Tel Aviv University, Centre Hospitalier Universitaire Vaudois, Hôpital Orthopédique de la Suisse Romande, University of Lausanne
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $1,690
OpenAlex ID: W2961517618