Introduction

Motivation

primary sources   +

books and reviews

isolated, with ambiguities and inconsistencies

Introduction

Motivation

how do we connect the minds of life scientists?

how do we avoid ambiguity ? 

is there a way to make knowledge machine actionable?

how do we leverage computers to reason upon the body of knowledge? 

Introduction

Introduction

Wikidata  in 2019 was already a tool for the biomedical sciences

Introduction

At the same time, the Human Cell Atlas Project was gaining traction to characterize all existing human cell types

Introduction

What if we leveraged Wikidata to support the Human Cell Atlas?

Introduction

What if we leveraged Wikidata to support the Human Cell Atlas?

Q1.  How can Wikidata support bioinformatics research?

Q2.  How to use Wikidata to represent knowledge about cell types?

By providing a home for 5-star Linked Open Bio Data

Q1.  How can Wikidata support bioinformatics research?

https://5stardata.info/en/

https://5stardata.info/en/

By providing a home for 5-star Linked Open Bio Data

Q1.  How can Wikidata support bioinformatics research?

We connected 15.000 cell-gene markers associations from PanglaoDB to Wikidata, making it 5-star Linked Open Data

The network structure of Wikidata enables live navigation in a connected knowledge graph, connecting to other pieces of knowledge

Besides PanglaoDB, we partnered up with the Complex Portal database to make knowledge about complexes 5-star LOD

Leveraging  SPARQL queries and Wikipedia links for enrichment analysis

What can we do with 5-star Linked Open Bio Data?

Leveraging  SPARQL queries and Wikipedia links for enrichment analysis

What can we do with 5-star Linked Open Data?

Leveraging  SPARQL queries and Wikipedia links for enrichment analysis

What can we do with 5-star Linked Open Data?

Q2.  How to use Wikidata to represent knowledge about cell types?

Where does Wikidata stand in the bio knowledge ecosystem

Q2.  How to use Wikidata to represent knowledge about cell types?

There is a fairly complete list of cell types ... right?

Q2.  How to use Wikidata to represent knowledge about cell types?

cell types --> cell classes

any idea grouping cells  that is used to communicate knowledge about the real world, provided that:

1. it has a (published) name

2. it is useful for theories

3. it is found in multiple individuals, across time

classes

 Wikidata for biocuration

• Open edits
• 5-star LOD
• GUI + APIs
• flexible data model
• stable funding

Q2.  How to use Wikidata to represent knowledge about cell classes?

A spreadsheet-based workflow to extract and map information

• read papers related to the Human Cell Atlas
• select cell classes
• curate in a spreadsheet
• parse into Wikidata with a Python script, mapping to unique identifiers

Q2.  How to use Wikidata to represent knowledge about cell classes?

Q2.  How to use Wikidata to represent knowledge about cell classes?

batch import from Wikipedia

batch import

from FMA

dedicated manual curation

batch import from Cell Ontology

Q2.  How to use Wikidata to represent knowledge about cell classes?

Q2.  How to use Wikidata to represent knowledge about cell classes?

5837  have at least one supporting reference (w.wiki/AYnP)

Wikidata as a versatile platform for cell information

• 84  semantic relations
• 150  resources for external identifiers
• links to Wikipedia in 196 languages

Q2.  How to use Wikidata to represent knowledge about cell classes?

Quickstarting internationalized ontologies

Resurfacing the knowledge about cell classes from Wikidata

https://pt.wikipedia.org/wiki/Predefinição:Info/Célula/Wikidata

Feeding  Wikipedia infoboxes

Resurfacing the knowledge about cell types from Wikidata

https://cellcatalog.toolforge.org

Powering knowledge portals about cell types

Q2.  How to use Wikidata to represent knowledge about cell types?

Acknowledgements

 The knowledge graph of Wikidata in the context of the Human Cell Atlas

Student: Tiago Lubiana

Advisor: Helder Nakaya

PhD Thesis Defense - 09/09/2024

Publications during the PhD

• Lubiana, T. and Nakaya, H.I., 2024. A reasonable request for true data sharing. The Lancet Regional Health–Americas, 35.

• Lubiana, T., Lopes, R., Medeiros, P., Silva, J. C., Goncalves, A. N. A., Maracaja-Coutinho, V., & Nakaya, H. I., 2023. Ten quick tips for harnessing the power of ChatGPT in computational biology. PLOS Computational Biology, 19(8), e1011319.

• Carneiro, C.F.D., da Costa, G.G., Neves, K., Abreu, M.B., Tan, P.B., Rayêe, D., Boos, F.Z., Andrejew, R., Lubiana, T., Malički, M. and Amaral, O.B., 2023. Characterization of comments about bioRxiv and medRxiv preprints. JAMA Network Open, 6(8), pp.e2331410-e2331410

Publications during the PhD

• Shafee, T., Mietchen, D., Lubiana, T., Jemielniak, D. and Waagmeester, A., 2023. Ten quick tips for editing Wikidata. PLOS Computational Biology, 19(7), p.e1011235.

• Meldal, B.H., Perfetto, L., Combe, C., Lubiana, T., Ferreira Cavalcante, J.V., Bye-A-Jee, H., Waagmeester, A., Del-Toro, N., Shrivastava, A., Barrera, E. and Wong, E., 2022. Complex Portal 2022: new curation frontiers. Nucleic acids research, 50(D1), pp.D578-D586.

• Turki, H., Hadj Taieb, M.A., Shafee, T., Lubiana, T., Jemielniak, D., Aouicha, M.B., Labra Gayo, J.E., Youngstrom, E.A., Banat, M.A., Das, D. and Mietchen, D., 2022. Representing COVID-19 information in collaborative knowledge graphs: The case of Wikidata. Semantic Web, 13(2), pp.233-264.

Publications during the PhD

Kilpatrick, A.M., Rahman, F., Anjum, A.,[...], Lubiana, T., [...] Astroz, Y.C., Douglas, J.M. and Eranti, P., 2022. Characterizing domain-specific open educational resources by linking ISCB Communities of Special Interest to Wikipedia. Bioinformatics, 38(Supplement_1), pp.i19-i27.

Rando, H.M., MacLean, A.L., Lee, [...], Lubianat, T., [...] Dziak, J.J., Shinholster, L. and D’Agostino McGowan, L., 2021. Pathogenesis, symptomatology, and transmission of SARS-CoV-2 through analysis of viral genomics and structure. MSystems, 6(5), pp.10-1128.

Lüscher-Dias, T., Dalmolin, R.J.S., de Paiva Amaral, P., Alves, T.L., Schuch, V., Franco, G.R. and Nakaya, H.I., 2022. The evolution of knowledge on genes associated with human diseases. Iscience, 25(1)

Publications during the PhD

• Turki, H., Jemielniak, D., Taieb, M.A.H., Gayo, J.E.L., Aouicha, M.B., Banat, M.A., Shafee, T., Prud’hommeaux, E., Lubiana, T., Das, D. and Mietchen, D., 2022. Using logical constraints to validate statistical information about disease outbreaks in collaborative knowledge graphs: the case of COVID-19 epidemiology in Wikidata. PeerJ Computer Science, 8, p.e1085.

• Hoyt, C.T., Balk, M., Callahan, T.J., Domingo-Fernández, D., Haendel, M.A., Hegde, H.B., Himmelstein, D.S., Karis, K., Kunze, J., Lubiana, T. and Matentzoglu, N., 2022. Unifying the identification of biomedical entities with the Bioregistry. Scientific data, 9(1), p.714.

Organize knowledge in machine readable format

Biocuration is the field of life sciences dedicated to organizing biomedical data, information and knowledge into structured formats, such as spreadsheets, tables and knowledge graphs.

We all know, use, and love biocurated resources

knowledge curation

data curation

Kegg, Reactome, Flybase, Gene Cards...

These resources are, though, hosted mostly in U.S. / Europe.

Previous experience w/ network analysis in CSBL 

What could I do as a PhD student in Brazil? 

Enter knowlege graphs and Wikidata

 Wikidata

* all purpose, openly editable KG

* wealth of biomedical information

* many intersections of academia 

I'd love to work with that!