2023
Fowler, A., FitzPatrick, M., Shanmugarasa, A., Ibrahim, A. S. F., Kockelbergh, H., Yang, H. -C., . . . Soilleux, E. J. (n.d.). An Interpretable Classification Model Using Gluten-Specific TCR Sequences Shows Diagnostic Potential in Coeliac Disease. Biomolecules, 13(12), 1707. doi:10.3390/biom13121707DOI: 10.3390/biom13121707
Quinn, L. M., Haldenby, S., Antzcak, P., Fowler, A., Bullock, K., Kenny, J., . . . Goldring, C. (n.d.). Genomic profiling of idiopathic peri-hilar cholangiocarcinoma reveals new targets and mutational pathways. Scientific Reports, 13(1). doi:10.1038/s41598-023-33096-0DOI: 10.1038/s41598-023-33096-0
2022
Kockelbergh, H., Evans, S., Deng, T., Clyne, E., Kyriakidou, A., Economou, A., . . . Soilleux, E. J. (2022). Utility of Bulk T-Cell Receptor Repertoire Sequencing Analysis in Understanding Immune Responses to COVID-19. DIAGNOSTICS, 12(5). doi:10.3390/diagnostics12051222DOI: 10.3390/diagnostics12051222
Benchmarking the performance of six variant callers on synthetic and real ctDNA datasets (Conference Paper)
Maruzani, R., Fowler, A., & Brierley, L. (2022). Benchmarking the performance of six variant callers on synthetic and real ctDNA datasets. In HUMAN HEREDITY Vol. VOL. (pp. 16). Retrieved from https://www.webofscience.com/
DECoN: A Detection and Visualization Tool for Exonic Copy Number Variants. (Journal article)
Fowler, A. (2022). DECoN: A Detection and Visualization Tool for Exonic Copy Number Variants.. Methods in molecular biology (Clifton, N.J.), 2493, 77-88. doi:10.1007/978-1-0716-2293-3_6DOI: 10.1007/978-1-0716-2293-3_6
Selecting subsets of immune repertoire features improves prediction of coeliac disease status using machine learning (Conference Paper)
Kockelbergh, H., Shoukat, M. S., Evans, S. C., Brierley, L., Jorgensen, A. L., Green, P. L., . . . Fowler, A. (2022). Selecting subsets of immune repertoire features improves prediction of coeliac disease status using machine learning. In HUMAN HEREDITY Vol. VOL. (pp. 14-15). Retrieved from https://www.webofscience.com/
2021
Brierley, L., & Fowler, A. (2021). Predicting the animal hosts of coronaviruses from compositional biases of spike protein and whole genome sequences through machine learning. PLoS Pathogens, 17(4). doi:10.1371/journal.ppat.1009149DOI: 10.1371/journal.ppat.1009149
Foers, A. D., Shoukat, M. S., Welsh, O. E., Donovan, K., Petry, R., Evans, S. C., . . . Soilleux, E. J. (n.d.). Classification of intestinal T cell receptor repertoires using machine learning methods can identify patients with coeliac disease regardless of dietary gluten status. The Journal of Pathology. doi:10.1002/path.5592DOI: 10.1002/path.5592
Shoukat, M. S., Foers, A. D., Woodmansey, S., Evans, S. C., Fowler, A., & Soilleux, E. J. (2021). Use of machine learning to identify a T cell response to SARS-CoV-2. CELL REPORTS MEDICINE, 2(2). doi:10.1016/j.xcrm.2021.100192DOI: 10.1016/j.xcrm.2021.100192
2020
Brierley, L., & Fowler, A. (2020). Predicting the animal hosts of coronaviruses from compositional biases of spike protein and whole genome sequences through machine learning. doi:10.1101/2020.11.02.350439DOI: 10.1101/2020.11.02.350439
Statistics at The Zoo (Journal article)
Holmes, L., Edwards, K., Moss, A., Tollington, S., Fowler, A., Hughes, D., & Sudell, M. (2020). Statistics at The Zoo. Significance, 17(5), 26-29. doi:10.1111/1740-9713.01446DOI: 10.1111/1740-9713.01446
Inferring B cell specificity for vaccines using a Bayesian mixture model (Journal article)
Fowler, A., Galson, J. D., Truck, J., Kelly, D. F., & Lunter, G. (2020). Inferring B cell specificity for vaccines using a Bayesian mixture model. BMC GENOMICS, 21(1). doi:10.1186/s12864-020-6571-7DOI: 10.1186/s12864-020-6571-7
2019
A Novel Artificial Intelligence Based Approach to the Diagnosis of Coeliac Disease, Based on T-Cell Receptor Repertoires (Conference Paper)
Fowler, A., Shoukat, M. S., Welsh, O. E., Donovan, K., & Soilleux, E. J. (2019). A Novel Artificial Intelligence Based Approach to the Diagnosis of Coeliac Disease, Based on T-Cell Receptor Repertoires. In JOURNAL OF PATHOLOGY Vol. 249 (pp. S21). Retrieved from https://www.webofscience.com/
2018
Soilleux, E., & Auer-Fowler, A. H. M. (2018, November 5). WO 2019/086900 A1, Computer-implemented method and system for determining a disease status of a subject from immune-receptor sequencing data.
2016
Fowler, A., Mahamdallie, S., Ruark, E., Seal, S., Ramsay, E., Clarke, M., . . . Rahman, N. (2016). Accurate clinical detection of exon copy number variants in a targeted NGS panel using DECoN.. Wellcome open research, 1, 20. doi:10.12688/wellcomeopenres.10069.1DOI: 10.12688/wellcomeopenres.10069.1
Galson, J. D., Trück, J., Clutterbuck, E. A., Fowler, A., Cerundolo, V., Pollard, A. J., . . . Kelly, D. F. (2016). B-cell repertoire dynamics after sequential hepatitis B vaccination and evidence for cross-reactive B-cell activation. Genome Medicine, 8(1). doi:10.1186/s13073-016-0322-zDOI: 10.1186/s13073-016-0322-z
The Diversity and Molecular Evolution of B-Cell Receptors during Infection (Journal article)
Hoehn, K. B., Fowler, A., Lunter, G., & Pybus, O. G. (2016). The Diversity and Molecular Evolution of B-Cell Receptors during Infection. MOLECULAR BIOLOGY AND EVOLUTION, 33(5), 1147-1157. doi:10.1093/molbev/msw015DOI: 10.1093/molbev/msw015
Bayesian Classification of Vaccine-Specific B-Cells from Repertoire Sequencing Data (Conference Paper)
Fowler, A., & Lunter, G. (2016). Bayesian Classification of Vaccine-Specific B-Cells from Repertoire Sequencing Data. In HUMAN HEREDITY Vol. 81 (pp. 234). Retrieved from https://www.webofscience.com/
2015
Analysis of B Cell Repertoire Dynamics Following Hepatitis B Vaccination in Humans, and Enrichment of Vaccine-specific Antibody Sequences (Journal article)
Galson, J. D., Trueck, J., Fowler, A., Clutterbuck, E. A., Muenz, M., Cerundolo, V., . . . Kelly, D. F. (2015). Analysis of B Cell Repertoire Dynamics Following Hepatitis B Vaccination in Humans, and Enrichment of Vaccine-specific Antibody Sequences. EBioMedicine, 2(12), 2070-2079. doi:10.1016/j.ebiom.2015.11.034DOI: 10.1016/j.ebiom.2015.11.034
BCR repertoire sequencing: different patterns of B-cell activation after two Meningococcal vaccines (Journal article)
Galson, J. D., Clutterbuck, E. A., Trueck, J., Ramasamy, M. N., Muenz, M., Fowler, A., . . . Kelly, D. F. (2015). BCR repertoire sequencing: different patterns of B-cell activation after two Meningococcal vaccines. IMMUNOLOGY AND CELL BIOLOGY, 93(10), 885-895. doi:10.1038/icb.2015.57DOI: 10.1038/icb.2015.57
In-depth assessment of within-individual and inter-individual variation in the B cell receptor repertoire (Journal article)
Galson, J. D., Trueck, J., Fowler, A., Muenz, M., Cerundolo, V., Pollard, A. J., . . . Kelly, D. F. (2015). In-depth assessment of within-individual and inter-individual variation in the B cell receptor repertoire. FRONTIERS IN IMMUNOLOGY, 6. doi:10.3389/fimmu.2015.00531DOI: 10.3389/fimmu.2015.00531
2013
DYNAMIC BAYESIAN CLUSTERING (Journal article)
Fowler, A., Menon, V., & Heard, N. A. (2013). DYNAMIC BAYESIAN CLUSTERING. JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY, 11(5). doi:10.1142/S0219720013420018DOI: 10.1142/S0219720013420018
Dynamic Bayesian clustering of gene expression data (Conference Paper)
Fowler, A., & Heard, N. A. (2013). Dynamic Bayesian clustering of gene expression data. In 5th International Conference on Bioinformatics and Computational Biology 2013, BICoB 2013 (pp. 165-170).
2012
On two‐way Bayesian agglomerative clustering of gene expression data (Journal article)
Fowler, A., & Heard, N. A. (2012). On two‐way Bayesian agglomerative clustering of gene expression data. Statistical Analysis and Data Mining: The ASA Data Science Journal, 5(5), 463-476. doi:10.1002/sam.11162DOI: 10.1002/sam.11162
