| Machine learning using intrinsic genomic signatures for rapid classification of novel pathogens: COVID-19 case study GS Randhawa, MPM Soltysiak, H El Roz, CPE de Souza, KA Hill, L Kari Plos one 15 (4), e0232391, 2020 | 456 | 2020 |
| ML-DSP: Machine Learning with Digital Signal Processing for ultrafast, accurate, and scalable genome classification at all taxonomic levels GS Randhawa, KA Hill, L Kari BMC genomics 20, 1-21, 2019 | 62 | 2019 |
| MLDSP-GUI: an alignment-free standalone tool with an interactive graphical user interface for DNA sequence comparison and analysis GS Randhawa, KA Hill, L Kari Bioinformatics 36 (7), 2258-2259, 2020 | 32 | 2020 |
| Efficacy of Genetic Algorithms in Staging Cervical Cancer SRP Singh, GS Randhawa, RS Virk International journal of cancer research 47 (2), 1164, 2013 | 3 | 2013 |
| Environment and taxonomy shape the genomic signature of prokaryotic extremophiles PM Arias, J Butler, GS Randhawa, MPM Soltysiak, KA Hill, L Kari Scientific Reports 13 (1), 16105, 2023 | 2 | 2023 |
| Cost Optimization of Pipeline Systems using Genetic Algorithm P Sharma, GSR Shelza, RS Virk International Journal of Computer Engineering & Technology (IJCET) 4 (4 …, 2013 | 2 | 2013 |
| Machine Learning-Based Analysis of Genomes Suggests Associations between Wuhan 2019-nCoV and bat Betacoronaviruses.[(accessed on 9 November 2020)] GS Randhawa, MP Soltysiak, H El Roz, CP de Souza, KA Hill, L Kari https://www. biorxiv. org/content/10.1101/2020.02 3, v2, 0 | 2 | |
| Heaps' Law in GPT-Neo Large Language Model Emulated Corpora U Lai, GS Randhawa, P Sheridan arXiv preprint arXiv:2311.06377, 2023 | | 2023 |
| Mutational Patterns Observed in SARS-CoV-2 Genomes Sampled From Successive Epochs Delimited by Major Public Health Events in Ontario, Canada: Genomic Surveillance Study D Chen, GS Randhawa, MPM Soltysiak, CPE de Souza, L Kari, SM Singh, ... JMIR Bioinformatics and Biotechnology 3 (1), e42243, 2022 | | 2022 |
| SomaticSiMu: a mutational signature simulator D Chen, GS Randhawa, MPM Soltysiak, CPE de Souza, L Kari, SM Singh, ... Bioinformatics 38 (9), 2619-2620, 2022 | | 2022 |
| Investigating Genomic and Mutational Signatures of Organisms Living in Extreme Environments. MPM Soltysiak, GS Randhawa, A Osman, CPE de Souza, KA Hill, L Kari ENVIRONMENTAL AND MOLECULAR MUTAGENESIS 61, 90-91, 2020 | | 2020 |
| SomaticSiMu: A Mutational Signature Simulator for Benchmarking Alignment-free Machine Learning Classification of Genomic Signatures. D Chen, GS Randhawa, MPM Soltysiak, L Kara, KA Hill ENVIRONMENTAL AND MOLECULAR MUTAGENESIS 61, 42-43, 2020 | | 2020 |
| Alignment-free genome analysis of SARS-CoV-2 using Machine learning. GS Randhawa, MPM Soltysiak, HEL Roz, CPE de Souza, KA Hill, L Kari ENVIRONMENTAL AND MOLECULAR MUTAGENESIS 61, 55-55, 2020 | | 2020 |
| Machine Learning Applied to Mouse Genotypes Accurately Classifies Genetic Background: Relevance to Human Genotype Classification for Detection of Environmental Mutagen Exposures. HA Pavanel, GS Randhawa, NA Boehler, RD Kelly, TA Miller, ... ENVIRONMENTAL AND MOLECULAR MUTAGENESIS 61, 38-39, 2020 | | 2020 |
| Machine Learning with Digital Signal Processing for Rapid and Accurate Alignment-Free Genome Analysis: From Methodological Design to a Covid-19 Case Study GS Randhawa The University of Western Ontario (Canada), 2020 | | 2020 |
| A Stand-Alone Software Tool With a Graphical User Interface Employing Machine-Learning and Digital Signal Processing (ML-DSP) for Accurate Genome-Wide Classification of Human … GS Randhawa, KA Hill, L Kari ENVIRONMENTAL AND MOLECULAR MUTAGENESIS 60, 79-80, 2019 | | 2019 |
| Machine Learning-Digital Signal Processing and genomic signatures to elucidate the ancestral proteobacterial origin of mitochondria. M Soltysiak, GS Randhawa, L Kari, KA Hill ENVIRONMENTAL AND MOLECULAR MUTAGENESIS 60, 80-80, 2019 | | 2019 |
| Genomic Signatures: Machine Learning and Digital Signal Processing of Genomic Sequences Provides Ultrafast and Accurate Taxonomic Classification. GS Randhawa, KA Hill, L Kari ENVIRONMENTAL AND MOLECULAR MUTAGENESIS 59, 104-104, 2018 | | 2018 |
| Tracking down contributors to genomic signatures: Cross-species comparisons of subsequence avoidance. M Soltvsiak, GS Randhawa, NA Boehler, L Kari, KA Hill ENVIRONMENTAL AND MOLECULAR MUTAGENESIS 59, 104-104, 2018 | | 2018 |
| uating Information Access (EVIA 2023), a Satellite Work-shop of the NTCIR-17 Conference, December 12-15, 2023 Tokyo Japan Q Ai, DW Oard, I Soboroff, A Aizawa, I Kang, Y Liu, P Thomas, T Sakai, ... | | |
Kathleen HillWestern University在 uwo.ca 的电子邮件经过验证
