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- ItemExperimental validation of computerised models of clustering of platelet glycoprotein receptors that signal via tandem SH2 domain proteins(San Francisco, Calif. : Public Library of Science, 2022) Maqsood, Zahra; Clark, Joanne C.; Martin, Eleyna M.; Cheung, Yam Fung Hilaire; Morán, Luis A.; Watson, Sean E. T.; Pike, Jeremy A.; Di, Ying; Poulter, Natalie S.; Slater, Alexandre; Lange, Bodo M. H.; Nieswandt, Bernhard; Eble, Johannes A.; Tomlinson, Mike G.; Owen, Dylan M.; Stegner, David; Bridge, Lloyd J.; Wierling, Christoph; Watson, Steve P.The clustering of platelet glycoprotein receptors with cytosolic YxxL and YxxM motifs, including GPVI, CLEC-2 and PEAR1, triggers activation via phosphorylation of the conserved tyrosine residues and recruitment of the tandem SH2 (Src homology 2) domain effector proteins, Syk and PI 3-kinase. We have modelled the clustering of these receptors with monovalent, divalent and tetravalent soluble ligands and with transmembrane ligands based on the law of mass action using ordinary differential equations and agent-based modelling. The models were experimentally evaluated in platelets and transfected cell lines using monovalent and multivalent ligands, including novel nanobody-based divalent and tetravalent ligands, by fluorescence correlation spectroscopy. Ligand valency, receptor number, receptor dimerisation, receptor phosphorylation and a cytosolic tandem SH2 domain protein act in synergy to drive receptor clustering. Threshold concentrations of a CLEC-2-blocking antibody and Syk inhibitor act in synergy to block platelet aggregation. This offers a strategy for countering the effect of avidity of multivalent ligands and in limiting off-target effects.
- ItemTransforming the study of organisms: Phenomic data models and knowledge bases(San Francisco, Calif. : Public Library of Science, 2020) Thessen, Anne E.; Walls, Ramona L.; Vogt, Lars; Singer, Jessica; Warren, Robert; Buttigieg, Pier Luigi; Balhoff, James P.; Mungall, Christopher J.; McGuinness, Deborah L.; Stucky, Brian J.; Yoder, Matthew J.; Haendel, Melissa A.The rapidly decreasing cost of gene sequencing has resulted in a deluge of genomic data from across the tree of life; however, outside a few model organism databases, genomic data are limited in their scientific impact because they are not accompanied by computable phenomic data. The majority of phenomic data are contained in countless small, heterogeneous phenotypic data sets that are very difficult or impossible to integrate at scale because of variable formats, lack of digitization, and linguistic problems. One powerful solution is to represent phenotypic data using data models with precise, computable semantics, but adoption of semantic standards for representing phenotypic data has been slow, especially in biodiversity and ecology. Some phenotypic and trait data are available in a semantic language from knowledge bases, but these are often not interoperable. In this review, we will compare and contrast existing ontology and data models, focusing on nonhuman phenotypes and traits. We discuss barriers to integration of phenotypic data and make recommendations for developing an operationally useful, semantically interoperable phenotypic data ecosystem.
- ItemTen quick tips for editing Wikidata(San Francisco, Calif. : Public Library of Science, 2023) Shafee, Thomas; Mietchen, Daniel; Lubiana, Tiago; Jemielniak, Dariusz; Waagmeester, Andra[no abstract available]