Building a biological knowledge graph via Wikidata with a focus on the Human Cell Atlas

• Grant number: 19/26284-1
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: August 01, 2020
• End date: August 05, 2024
• Field of knowledge: Interdisciplinary Subjects
• Principal Investigator: Helder Takashi Imoto Nakaya
• Grantee: Tiago Lubiana Alves
• Host Institution: Faculdade de Ciências Farmacêuticas (FCF). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Associated research grant: 18/21934-5 - Network statistics: theory, methods, and applications, AP.TEM

Abstract

The Human Cell Atlas is an international effort aiming at characterizing every cell type of the human body. Employing techniques such as single-cell RNA sequencing, mass cytometry, and multiplexed in situ hybridization, it will produce data from virtually all human tissues. This wealth of data can have a significant impact on biomedical research, but only if its content is genuinely available. Wikidata is a knowledge graph database emerging as a FAIR (Findable, Accessible, Interoperable and Reusable) repository for biological knowledge. The formatting and deployment of information from the Human Cell Atlas to Wikidata can increase information availability and impact, by inserting the findings in a network containing multiple associations of concepts of all areas of knowledge (within and outside Science). Conceptually defining cell types in a general and applicable concept, formalized into a database-compatible format, is a massive theoretical challenge. This PhD project aims at studying our current understanding of cell types for development a comprehensive ontological model in Wikidata for cell types. We will review the single-cell literature, refining and formalizing concepts for cell type delimitation. Furthermore, we will use Natural Language Processing and Machine Learning tools to automate knowledge extraction from scientific articles in the scope of the Human Cell Atlas. In an advanced step, we will apply concepts of network theory to develop tools for user-friendly querying of the database, making the knowledge ready for the academic community. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

LUBIANA, TIAGO; LOPES, RAFAEL; MEDEIROS, PEDRO; SILVA, JUAN CARLO; GONCALVES, ANDRE NICOLAU AQUIME; MARACAJA-COUTINHO, VINICIUS; NAKAYA, HELDER I.. Ten quick tips for harnessing the power of ChatGPT in computational biology. PLOS COMPUTATIONAL BIOLOGY, v. 19, n. 8, p. 9-pg., 2023-08-01. (19/27139-5, 19/26284-1, 18/14933-2)

MELDAL, BIRGIT H. M.; PERFETTO, LIVIA; COMBE, COLIN; LUBIANA, TIAGO; CAVALCANTE, JOAO VITOR FERREIRA; BYE-A-JEE, HEMA; WAAGMEESTER, ANDRA; DEL-TORO, NOEMI; SHRIVASTAVA, ANJALI; BARRERA, ELISABETH; et al. omplex Portal 2022: new curation frontier. Nucleic Acids Research, v. 50, n. D1, p. D578-D586, JAN 7 2022. (19/26284-1)

SHAFEE, THOMAS; MIETCHEN, DANIEL; LUBIANA, TIAGO; JEMIELNIAK, DARIUSZ; WAAGMEESTER, ANDRA. Ten quick tips for editing Wikidata. PLOS COMPUTATIONAL BIOLOGY, v. 19, n. 7, p. 13-pg., 2023-07-01. (19/26284-1)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

ALVES, Tiago Lubiana. Building a biological knowledge graph via Wikidata with a focus on the Human Cell Atlas. 2024. Doctoral Thesis - Universidade de São Paulo (USP). Instituto de Matemática e Estatística (IME/SBI) São Paulo.