VITAGRAPH: building a knowledge graph for biologically relevant learning tasks.

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Title: VITAGRAPH: building a knowledge graph for biologically relevant learning tasks.
Authors: Madeddu F; Department of Computer, Control and Management Engineering, Sapienza University of Rome, 00185, Rome, Italy.; Istituto per le Applicazioni del Calcolo, Consiglio Nazionale delle Ricerche, 00185, Rome, Italy., Testa L; Department of Computer, Control and Management Engineering, Sapienza University of Rome, 00185, Rome, Italy., De Carlo G; Department of Computer, Control and Management Engineering, Sapienza University of Rome, 00185, Rome, Italy.; University of Cambridge, Cambridge, UK., Pieroni M; Department of Biochemical Sciences, Sapienza University of Rome, 00185, Rome, Italy., Mastropietro A; Department of Life Science Informatics and Data Science, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, University of Bonn, Friedrich-Hirzebruch-Allee 6, 53115, Bonn, Germany. mastropietro@bit.uni-bonn.de.; Lamarr Institute for Machine Learning and Artificial Intelligence, University of Bonn, Friedrich-Hirzebruch-Allee 6, 53115, Bonn, Germany. mastropietro@bit.uni-bonn.de.; Data Science Center, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara, 630-0192, Japan. mastropietro@bit.uni-bonn.de., Petti M; Department of Computer, Control and Management Engineering, Sapienza University of Rome, 00185, Rome, Italy., Anagnostopoulos A; Department of Computer, Control and Management Engineering, Sapienza University of Rome, 00185, Rome, Italy., Tieri P; Istituto per le Applicazioni del Calcolo, Consiglio Nazionale delle Ricerche, 00185, Rome, Italy., Barbarossa S; Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, 00185, Rome, Italy.
Source: Scientific data [Sci Data] 2026 Jul 14; Vol. 13 (1). Date of Electronic Publication: 2026 Jul 14.
Publication Type: Journal Article; Dataset
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101640192 Publication Model: Electronic Cited Medium: Internet ISSN: 2052-4463 (Electronic) Linking ISSN: 20524463 NLM ISO Abbreviation: Sci Data Subsets: MEDLINE
Database: MEDLINE Ultimate
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Description
ISSN:2052-4463
DOI:10.1038/s41597-026-07498-4