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Dr

James Lefevre

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Overview

Availability

Dr James Lefevre is:
Available for supervision

Qualifications

  • Doctor of Philosophy, The University of Queensland

Works

Search Professor James Lefevre’s works on UQ eSpace

60 works between 2004 and 2025

1 - 20 of 60 works

2025

Book Chapter

From Block Designs to Codes to Crypto and Back Again

Donovan, Diane, Lefevre, James and Yazıcı, E. Şule (2025). From Block Designs to Codes to Crypto and Back Again. Lecture Notes in Computer Science. (pp. 25-43) Cham: Springer Nature Switzerland. doi: 10.1007/978-3-031-83490-5_2

From Block Designs to Codes to Crypto and Back Again

2024

Journal Article

Pyroptotic cell corpses are crowned with F-actin-rich filopodia that engage CLEC9A signaling in incoming dendritic cells

Holley, Caroline L., Monteleone, Mercedes, Fisch, Daniel, Libert, Alexandre E. S., Ju, Robert J., Choi, Joon H., Condon, Nicholas D., Emming, Stefan, Crawford, Joanna, Lawrence, Grace M. E. P., Coombs, Jared R., Lefevre, James G., Bajracharya, Rinie, Lahoud, Mireille H., Yap, Alpha S., Hamilton, Nicholas, Stehbens, Samantha J., Kagan, Jonathan C., Ariotti, Nicholas, Burgener, Sabrina S. and Schroder, Kate (2024). Pyroptotic cell corpses are crowned with F-actin-rich filopodia that engage CLEC9A signaling in incoming dendritic cells. Nature Immunology, 26 (1) eaas8995, 1-35. doi: 10.1038/s41590-024-02024-3

Pyroptotic cell corpses are crowned with F-actin-rich filopodia that engage CLEC9A signaling in incoming dendritic cells

2024

Journal Article

An application of node and edge nonlinear hypergraph centrality to a protein complex hypernetwork

Lawson, Sarah, Donovan, Diane and Lefevre, James (2024). An application of node and edge nonlinear hypergraph centrality to a protein complex hypernetwork. PLoS One, 19 (10) e0311433, e0311433. doi: 10.1371/journal.pone.0311433

An application of node and edge nonlinear hypergraph centrality to a protein complex hypernetwork

2024

Journal Article

Applying hypergraphs to studies in quantitative biology

Barton, Samuel, Coster, Adelle, Donovan, Diane and Lefevre, James (2024). Applying hypergraphs to studies in quantitative biology. LIFE: International Journal of Health and Life-Sciences, 9, 21-33. doi: 10.20319/lijhls.2024.9.2133

Applying hypergraphs to studies in quantitative biology

2023

Journal Article

Hypergraphs and centrality measures identifying key features in gene expression data

Barton, Samuel, Broad, Zoe, Ortiz-Barrientos, Daniel, Donovan, Diane and Lefevre, James (2023). Hypergraphs and centrality measures identifying key features in gene expression data. Mathematical Biosciences, 366 109089, 1-14. doi: 10.1016/j.mbs.2023.109089

Hypergraphs and centrality measures identifying key features in gene expression data

2021

Journal Article

Non-melanoma skin cancer segmentation for histopathology dataset

Thomas, Simon M., Lefevre, James G., Baxter, Glenn and Hamilton, Nicholas A. (2021). Non-melanoma skin cancer segmentation for histopathology dataset. Data in Brief, 39 107587, 107587. doi: 10.1016/j.dib.2021.107587

Non-melanoma skin cancer segmentation for histopathology dataset

2021

Journal Article

Characterization of tissue types in basal cell carcinoma images via generative modeling and concept vectors

Thomas, S. M., Lefevre, J. G., Baxter, G. and Hamilton, N. A. (2021). Characterization of tissue types in basal cell carcinoma images via generative modeling and concept vectors. Computerized Medical Imaging and Graphics, 94 101998, 101998. doi: 10.1016/j.compmedimag.2021.101998

Characterization of tissue types in basal cell carcinoma images via generative modeling and concept vectors

2021

Journal Article

LLAMA: a robust and scalable machine learning pipeline for analysis of large scale 4D microscopy data: analysis of cell ruffles and filopodia

Lefevre, James G., Koh, Yvette W. H., Wall, Adam A., Condon, Nicholas D., Stow, Jennifer L. and Hamilton, Nicholas A. (2021). LLAMA: a robust and scalable machine learning pipeline for analysis of large scale 4D microscopy data: analysis of cell ruffles and filopodia. BMC Bioinformatics, 22 (1) 410, 1-26. doi: 10.1186/s12859-021-04324-z

LLAMA: a robust and scalable machine learning pipeline for analysis of large scale 4D microscopy data: analysis of cell ruffles and filopodia

2021

Journal Article

Interpretable deep learning systems for multi-class segmentation and classification of non-melanoma skin cancer

Thomas, Simon M., Lefevre, James G., Baxter, Glenn and Hamilton, Nicholas A. (2021). Interpretable deep learning systems for multi-class segmentation and classification of non-melanoma skin cancer. Medical Image Analysis, 68 101915, 101915. doi: 10.1016/j.media.2020.101915

Interpretable deep learning systems for multi-class segmentation and classification of non-melanoma skin cancer

2021

Other Outputs

Demonstration data for LLAMA open source analysis pipeline and visualiser publication

Lefevre, James and Cairncross, Oliver (2021). Demonstration data for LLAMA open source analysis pipeline and visualiser publication. The University of Queensland. (Dataset) doi: 10.14264/3084db2

Demonstration data for LLAMA open source analysis pipeline and visualiser publication

2019

Journal Article

Nephron progenitor commitment is a stochastic process influenced by cell migration

Lawlor, Kynan T, Zappia, Luke, Lefevre, James, Park, Joo-Seop, Hamilton, Nicholas A, Oshlack, Alicia, Little, Melissa H and Combes, Alexander N (2019). Nephron progenitor commitment is a stochastic process influenced by cell migration. eLife, 8 e41156. doi: 10.7554/elife.41156

Nephron progenitor commitment is a stochastic process influenced by cell migration

2019

Journal Article

Use of surrogate species to cost-effectively prioritize conservation actions

Ward, Michelle, Rhodes, Jonathan R., Watson, James E.M., Lefevre, James, Atkinson, Scott and Possingham, Hugh P. (2019). Use of surrogate species to cost-effectively prioritize conservation actions. Conservation Biology, 34 (3) cobi.13430, 600-610. doi: 10.1111/cobi.13430

Use of surrogate species to cost-effectively prioritize conservation actions

2019

Other Outputs

Machine Learning Macropinocytosis

Lefevre, James (2019). Machine Learning Macropinocytosis. The University of Queensland. (Dataset) doi: 10.48610/dc2f523

Machine Learning Macropinocytosis

2018

Journal Article

Branching morphogenesis in the developing kidney 1 is not impacted by nephron formation or integration

Short, Kieran M., Combes, Alexander N., Lisnyak, Valerie, Lefevre, James G., Jones, Lynelle K., Little, Melissa H., Hamilton, Nicholas A. and Smyth, Ian M. (2018). Branching morphogenesis in the developing kidney 1 is not impacted by nephron formation or integration. eLife, 7 e38992. doi: 10.7554/eLife.38992

Branching morphogenesis in the developing kidney 1 is not impacted by nephron formation or integration

2017

Journal Article

Branching morphogenesis in the developing kidney is governed by rules that pattern the ureteric tree

Lefevre, James, Short, Kieran M, Lamberton, Timothy O, Michos, Odyssé, Graf, Daniel, Smyth, Ian M and Hamilton, Nicholas A (2017). Branching morphogenesis in the developing kidney is governed by rules that pattern the ureteric tree. Development (Cambridge, England), 144 (23), 4377-4385. doi: 10.1242/dev.153874

Branching morphogenesis in the developing kidney is governed by rules that pattern the ureteric tree

2017

Journal Article

Self-organisation after embryonic kidney dissociation is driven via selective adhesion of ureteric epithelial cells

Lefevre, James G., Chiu, Han S., Combes, Alexander N., Vanslambrouck, Jessica M., Ju, Ali, Hamilton, Nicholas A. and Little, Melissa H. (2017). Self-organisation after embryonic kidney dissociation is driven via selective adhesion of ureteric epithelial cells. Development, 144 (6), 1087-1096. doi: 10.1242/dev.140228

Self-organisation after embryonic kidney dissociation is driven via selective adhesion of ureteric epithelial cells

2017

Conference Publication

An integrated cell, tissue and whole organ profile of kidney morphogenesis

Combes, Alexander, Lefevre, James, Short, Kieran, Ju, Adler, Georgas, Kylie, Lamberton, Timothy, Cairncross, Oliver, Rumballe, Bree, McMahon, Andrew, Little, Melissa, Hamilton, Nicholas and Smyth, Ian (2017). An integrated cell, tissue and whole organ profile of kidney morphogenesis. 18th International Congress of Developmental Biology, Singapore, 18-22 June 2017. Amsterdam, Netherlands: Elsevier. doi: 10.1016/j.mod.2017.04.432

An integrated cell, tissue and whole organ profile of kidney morphogenesis

2016

Journal Article

Analysed cap mesenchyme track data from live imaging of mouse kidney development

Lefevre, James G., Combes, Alexander N., Little, Melissa H. and Hamilton, Nicholas A. (2016). Analysed cap mesenchyme track data from live imaging of mouse kidney development. Data in Brief, 9, 149-154. doi: 10.1016/j.dib.2016.08.053

Analysed cap mesenchyme track data from live imaging of mouse kidney development

2016

Journal Article

Cap mesenchyme cell swarming during kidney development is influenced by attraction, repulsion, and adhesion to the ureteric tip

Combes, Alexander N., Lefevre, James G., Wilson, Sean, Hamilton, Nicholas A. and Little, Melissa H. (2016). Cap mesenchyme cell swarming during kidney development is influenced by attraction, repulsion, and adhesion to the ureteric tip. Developmental Biology, 418 (2), 297-306. doi: 10.1016/j.ydbio.2016.06.028

Cap mesenchyme cell swarming during kidney development is influenced by attraction, repulsion, and adhesion to the ureteric tip

2015

Journal Article

A spatially-averaged mathematical model of kidney branching morphogenesis

Zubkov, V. S., Combes, A. N., Short, K. M., Lefevre, J. G., Hamilton, N. A., Smyth, I. M., Little, M. H. and Byrne, H. M. (2015). A spatially-averaged mathematical model of kidney branching morphogenesis. Journal of Theoretical Biology, 379, 24-37. doi: 10.1016/j.jtbi.2015.04.015

A spatially-averaged mathematical model of kidney branching morphogenesis

Supervision

Availability

Dr James Lefevre is:
Available for supervision

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Supervision history

Current supervision

  • Doctor Philosophy

    A study of combinatorial problems and their applications

    Principal Advisor

  • Doctor Philosophy

    Combinatorial Configurations With A Focus on Heffter Arrays and their Applications

    Principal Advisor

  • Doctor Philosophy

    Assessment of machine learning methods to discover novel models of gene networks to improve genomic prediction for plant breeding

    Associate Advisor

    Other advisors: Dr Owen Powell, Professor Mark Cooper

  • Doctor Philosophy

    Modelling Biological Systems using Mathematical Networks

    Associate Advisor

  • Doctor Philosophy

    Pure and Applied Applications of Combinatorial Mathematics

    Associate Advisor

    Other advisors: Professor Daniel Ortiz-Barrientos

  • Doctor Philosophy

    Applications of hypergraphs and centrality measures

    Associate Advisor

    Other advisors: Professor Daniel Ortiz-Barrientos

  • Doctor Philosophy

    Applications of hypergraphs and centrality measures

    Associate Advisor

    Other advisors: Professor Daniel Ortiz-Barrientos

Completed supervision

Media

Enquiries

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