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Aidan O'Brien
Aidan O'Brien
Unknown affiliation
Verified email at anu.edu.au
Title
Cited by
Cited by
Year
GT-Scan: identifying unique genomic targets
A O'Brien, TL Bailey
Bioinformatics, 2673-2675, 2014
1462014
The current state and future of CRISPR-Cas9 gRNA design tools
LOW Wilson, DC Bauer
Frontiers in pharmacology 9, 353115, 2018
1252018
Reproducibility of CRISPR-Cas9 methods for generation of conditional mouse alleles: a multi-center evaluation
CB Gurumurthy, AR O’brien, RM Quadros, J Adams, P Alcaide, S Ayabe, ...
Genome biology 20 (1), 1-14, 2019
812019
High activity target-site identification using phenotypic independent CRISPR-Cas9 core functionality
LOW Wilson, D Reti, AR O'Brien, RA Dunne, DC Bauer
The CRISPR Journal 1 (2), 182-190, 2018
502018
Artificial intelligence and machine learning in bioinformatics
K Lai, N Twine, A O’brien, Y Guo, D Bauer
Encyclopedia of Bioinformatics and Computational Biology: ABC of …, 2018
412018
Unlocking HDR-mediated nucleotide editing by identifying high-efficiency target sites using machine learning
AR o’Brien, LOW Wilson, G Burgio, DC Bauer
Scientific reports 9 (1), 2788, 2019
382019
VariantSpark: population scale clustering of genotype information
AR O’Brien, NFW Saunders, Y Guo, FA Buske, RJ Scott, DC Bauer
BMC genomics 16 (1), 1-9, 2015
372015
Mutation analysis of MATR3 in Australian familial amyotrophic lateral sclerosis
JA Fifita, KL Williams, EP McCann, A O'Brien, DC Bauer, GA Nicholson, ...
Neurobiology of aging 36 (3), 1602.e1-1602.e2, 2015
182015
Domain-specific introduction to machine learning terminology, pitfalls and opportunities in CRISPR-based gene editing
AR O’Brien, G Burgio, DC Bauer
Briefings in bioinformatics 22 (1), 308-314, 2021
152021
VariantSpark: Cloud-based machine learning for association study of complex phenotype and large-scale genomic data
A Bayat, P Szul, AR O’Brien, R Dunne, B Hosking, Y Jain, C Hosking, ...
GigaScience 9 (8), giaa077, 2020
122020
The current state and future of CRISPR-Cas9 gRNA design tools. Front Pharmacol 9: 749
LOW Wilson, AR O’Brien, DC Bauer
62018
VariantSpark, A Random Forest Machine Learning Implementation for Ultra High Dimensional Data
A Bayat, P Szul, AR O’Brien, R Dunne, OJ Luo, Y Jain, B Hosking, ...
bioRxiv, 702902, 2019
32019
Response to correspondence on “Reproducibility of CRISPR-Cas9 methods for generation of conditional mouse alleles: a multi-center evaluation”
CB Gurumurthy, AR O’Brien, RM Quadros, J Adams, P Alcaide, S Ayabe, ...
Genome biology 22, 1-4, 2021
22021
GOANA: A Universal High-Throughput Web Service for Assessing and Comparing the Outcome and Efficiency of Genome Editing Experiments
D Reti, A O'Brien, P Wetzel, A Tay, DC Bauer, LOW Wilson
The CRISPR Journal 4 (2), 243-252, 2021
22021
Predicting CRISPR-Cas12a guide efficiency for targeting using machine learning
A O’Brien, DC Bauer, G Burgio
Plos one 18 (10), e0292924, 2023
12023
Uncovering the functional variants and target genes of the 7q32 pancreatic cancer risk locus
A O'Brien, JW Hoskins, DR Eiser, KE Connelly, J Zhong, T Andresson, ...
Cancer Research 82 (12_Supplement), 1475-1475, 2022
2022
Defining and evaluating an operational definition of potentially preventable hospital readmission
A O'Brien
Macquarie University, 2022
2022
Generalisable Methods for Improving Crispr Efficiency and Outcome Specificity Using Machine Learning Algorithms
AR O'Brien
PQDT-Global, 2020
2020
Breaking the curse of dimensionality for machine learning on genomic data
A O’Brien, P Szul, O Luo, A George, R Dunne, D Bauer
IJCAI 2017, 2017
2017
VariantSpark: Applying Spark-based machine learning methods to genomic information
AR O'Brien, DC Bauer
BigData 2015, 2015
2015
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