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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
1222014
The current state and future of CRISPR-Cas9 gRNA design tools
LOW Wilson, AR O’Brien, DC Bauer
Frontiers in pharmacology 9, 749, 2018
902018
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
472019
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
372018
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
342015
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
232018
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), 1-10, 2019
222019
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
172015
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
62021
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
62020
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
22019
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), 1-4, 2021
12021
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
12021
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
Generalisable Methods for Improving CRISPR Efficiency and Outcome Specificity using Machine Learning Algorithms
AR O'Brien
PQDT-Global, 2021
2021
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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Articles 1–17