| Replacing testing with formal verification in intel coretm i7 processor execution engine validation R Kaivola, R Ghughal, N Narasimhan, A Telfer, J Whittemore, S Pandav, ... International Conference on Computer Aided Verification, 414-429, 2009 | 223 | 2009 |
| Conserved non-AUG uORFs revealed by a novel regression analysis of ribosome profiling data P Spealman, AW Naik, GE May, S Kuersten, L Freeberg, RF Murphy, ... Genome research 28 (2), 214-222, 2018 | 81 | 2018 |
| Determining the subcellular location of new proteins from microscope images using local features LP Coelho, JD Kangas, AW Naik, E Osuna-Highley, E Glory-Afshar, ... Bioinformatics 29 (18), 2343-2349, 2013 | 81 | 2013 |
| Active machine learning-driven experimentation to determine compound effects on protein patterns AW Naik, JD Kangas, DP Sullivan, RF Murphy Elife 5, e10047, 2016 | 52 | 2016 |
| Efficient discovery of responses of proteins to compounds using active learning JD Kangas, AW Naik, RF Murphy BMC bioinformatics 15, 1-11, 2014 | 40 | 2014 |
| Efficient modeling and active learning discovery of biological responses AW Naik, JD Kangas, CJ Langmead, RF Murphy PLoS One 8 (12), e83996, 2013 | 35 | 2013 |
| Point process models for localization and interdependence of punctate cellular structures Y Li, TD Majarian, AW Naik, GR Johnson, RF Murphy Cytometry Part A 89 (7), 633-643, 2016 | 15 | 2016 |
| Deciding when to stop: efficient experimentation to learn to predict drug-target interactions M Temerinac-Ott, AW Naik, RF Murphy BMC bioinformatics 16, 1-10, 2015 | 10 | 2015 |
| uORF-seqr: a machine Learning-Based approach to the identification of upstream open reading frames in yeast P Spealman, A Naik, J McManus Ribosome Profiling: Methods and Protocols, 313-329, 2021 | 5 | 2021 |
| Formal verification of high-level conformance with symbolic simulation R Kaivola, A Naik Tenth IEEE International High-Level Design Validation and Test Workshop …, 2005 | 4 | 2005 |
| Formal verification of high-level conformance with symbolic simulation R Kaivola, A Naik Tenth IEEE International High-Level Design Validation and Test Workshop …, 2005 | 4 | 2005 |
| Deciding when to stop: Efficient stopping of active learning guided drug-target prediction M Temerinac-Ott, AW Naik, RF Murphy arXiv preprint arXiv:1504.02406, 2015 | 3 | 2015 |
| Electronic system with a data engine for processing retrieved data in displaying graphical data for a graphical user interface on an external input/output device AW Naik, JD Kangas, CJ Langmead, RF Murphy US Patent App. 16/296,088, 2020 | | 2020 |
| Learning to predict effects of compounds on targets AW Naik, JD Kangas, CJ Langmead, RF Murphy US Patent App. 13/985,247, 2014 | | 2014 |
| Active Learning to Improve Efficiency of Drug Discovery and Development JD Kangas, RF Murphy, AW Naik | | |
