| Data mining in bioinformatics using Weka E Frank, M Hall, L Trigg, G Holmes, IH Witten Bioinformatics 20 (15), 2479-2481, 2004 | 1182 | 2004 |
| K*: An instance-based learner using an entropic distance measure JG Cleary, LE Trigg Machine Learning Proceedings 1995, 108-114, 1995 | 1110 | 1995 |
| Weka: Practical machine learning tools and techniques with Java implementations IH Witten, E Frank, LE Trigg, MA Hall, G Holmes, SJ Cunningham | 964 | 1999 |
| Weka-a machine learning workbench for data mining E Frank, M Hall, G Holmes, R Kirkby, B Pfahringer, IH Witten, L Trigg Data mining and knowledge discovery handbook, 1269-1277, 2010 | 835 | 2010 |
| Best practices for benchmarking germline small-variant calls in human genomes P Krusche, L Trigg, PC Boutros, CE Mason, FM De La Vega, BL Moore, ... Nature biotechnology 37 (5), 555-560, 2019 | 363 | 2019 |
| An open resource for accurately benchmarking small variant and reference calls JM Zook, J McDaniel, ND Olson, J Wagner, H Parikh, H Heaton, SA Irvine, ... Nature biotechnology 37 (5), 561-566, 2019 | 328 | 2019 |
| Naive Bayes for regression E Frank, L Trigg, G Holmes, IH Witten Machine Learning 41, 5-25, 2000 | 313 | 2000 |
| Comparing variant call files for performance benchmarking of next-generation sequencing variant calling pipelines JG Cleary, R Braithwaite, K Gaastra, BS Hilbush, S Inglis, SA Irvine, ... BioRxiv, 023754, 2015 | 191 | 2015 |
| Jumble java byte code to measure the effectiveness of unit tests SA Irvine, T Pavlinic, L Trigg, JG Cleary, S Inglis, M Utting Testing: Academic and industrial conference practice and research techniques …, 2007 | 97 | 2007 |
| Joint variant and de novo mutation identification on pedigrees from high-throughput sequencing data JG Cleary, R Braithwaite, K Gaastra, BS Hilbush, S Inglis, SA Irvine, ... Journal of Computational Biology 21 (6), 405-419, 2014 | 95 | 2014 |
| Data mining and knowledge discovery handbook E Frank, M Hall, G Holmes, R Kirkby, B Pfahringer, IH Witten, L Trigg US: Springer, 1305-14, 2005 | 73 | 2005 |
| Reproducible integration of multiple sequencing datasets to form high-confidence SNP, indel, and reference calls for five human genome reference materials JM Zook, J McDaniel, H Parikh, H Heaton, SA Irvine, L Trigg, R Truty, ... BioRxiv, 281006, 2018 | 52 | 2018 |
| Weka 3: Data mining software in Java E Frank, M Hall, L Trigg The University of Waikato: Hamilton, New Zealand, 2006 | 34 | 2006 |
| Assessing reproducibility of inherited variants detected with short-read whole genome sequencing B Pan, L Ren, V Onuchic, M Guan, R Kusko, S Bruinsma, L Trigg, ... Genome biology 23, 1-26, 2022 | 32 | 2022 |
| Attribute-relation file format (ARFF) G Paynter, L Trigg, E Frank, R Kirkby Online] http://www. cs. waikato. ac. nz/ml/weka/arff. html, 2008 | 19 | 2008 |
| Method and system for sequence correlation SJ Inglis, LE Trigg, RH Littin, DW Ware, SA Irvine, JG Cleary, GC Gaylard, ... US Patent App. 13/681,215, 2013 | 16 | 2013 |
| Weka 3-Data Mining with Open Source Machine Learning Software in Java E Frank, M Hall, L Trigg, R Kirkby, G Schmidberger, M Ware, X Xu, ... The University of Waikato, 2000 | 16 | 2000 |
| Objective measurement of mushroom quality N Kusabs, F Bollen, L Trigg, G Holmes, S Inglis Proc New Zealand Institute of Agricultural Science and the New Zealand …, 1998 | 13 | 1998 |
| A diagnostic tool for tree based supervised classification learning algorithms G Holmes, L Trigg ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on …, 1999 | 12 | 1999 |
| Method and system for evaluating sequences SJ Inglis, LE Trigg, ATJ Jackson, SA Irvine US Patent App. 13/681,046, 2013 | 11 | 2013 |
Sean A. IrvineReal Time GenomicsVerified email at realtimegenomics.com
