| WhatsHap: Weighted Haplotype Assembly for Future-Generation Sequencing Reads M Patterson, T Marschall, N Pisanti, L Van Iersel, L Stougie, GW Klau, ... Journal of Computational Biology 22 (6), 498-509, 2015 | 359 | 2015 |
| WhatsHap: fast and accurate read-based phasing M Martin, M Patterson, S Garg, S O Fischer, N Pisanti, GW Klau, ... BioRxiv, 085050, 2016 | 262 | 2016 |
| Spike2vec: An efficient and scalable embedding approach for covid-19 spike sequences S Ali, M Patterson 2021 IEEE International Conference on Big Data (Big Data), 1533-1540, 2021 | 53 | 2021 |
| A k-mer Based Approach for SARS-CoV-2 Variant Identification S Ali, B Sahoo, N Ullah, A Zelikovskiy, M Patterson, I Khan Bioinformatics Research and Applications: 17th International Symposium …, 2021 | 52 | 2021 |
| DeCoSTAR: reconstructing the ancestral organization of genes or genomes using reconciled phylogenies W Duchemin, Y Anselmetti, M Patterson, Y Ponty, S Bérard, C Chauve, ... Genome biology and evolution 9 (5), 1312-1319, 2017 | 47 | 2017 |
| Inferring cancer progression from single-cell sequencing while allowing mutation losses S Ciccolella, C Ricketts, M Soto Gomez, M Patterson, D Silverbush, ... Bioinformatics 37 (3), 326-333, 2021 | 46 | 2021 |
| WhatsHap: Haplotype Assembly for Future-Generation Sequencing Reads M Patterson, T Marschall, N Pisanti, L van Iersel, L Stougie, GW Klau, ... Research in Computational Molecular Biology: 18th Annual International …, 2014 | 43 | 2014 |
| Overlap graphs and de Bruijn graphs: data structures for de novo genome assembly in the big data era R Rizzi, S Beretta, M Patterson, Y Pirola, M Previtali, G Della Vedova, ... Quantitative Biology 7, 278-292, 2019 | 41 | 2019 |
| PWM2Vec: An efficient embedding approach for viral host specification from coronavirus spike sequences S Ali, B Bello, P Chourasia, RT Punathil, Y Zhou, M Patterson Biology 11 (3), 418, 2022 | 39 | 2022 |
| Efficient analysis of COVID-19 clinical data using machine learning models S Ali, Y Zhou, M Patterson Medical & Biological Engineering & Computing 60 (7), 1881-1896, 2022 | 35 | 2022 |
| Linearization of ancestral multichromosomal genomes J Maňuch, M Patterson, R Wittler, C Chauve, E Tannier BMC bioinformatics 13, 1-11, 2012 | 35 | 2012 |
| Effective and scalable clustering of SARS-CoV-2 sequences S Ali, TE Ali, MA Khan, I Khan, M Patterson Proceedings of the 5th international conference on big data research, 42-49, 2021 | 33 | 2021 |
| Lateral gene transfer, rearrangement, reconciliation M Patterson, G Szöllősi, V Daubin, E Tannier BMC bioinformatics 14, 1-7, 2013 | 31 | 2013 |
| Grounding for model expansion in k-guarded formulas with inductive definitions MD Patterson Simon Fraser University, 2006 | 27 | 2006 |
| Robust representation and efficient feature selection allows for effective clustering of sars-cov-2 variants Z Tayebi, S Ali, M Patterson Algorithms 14 (12), 348, 2021 | 25 | 2021 |
| O Fischer M Martin, M Patterson, S Garg S., Pisanti, N., Klau, GW, Schöenhuth, A., & Marschall, 2016 | 25 | 2016 |
| From alpha to zeta: Identifying variants and subtypes of sars-cov-2 via clustering A Melnyk, F Mohebbi, S Knyazev, B Sahoo, R Hosseini, P Skums, ... Journal of Computational Biology 28 (11), 1113-1129, 2021 | 23 | 2021 |
| O Fischer S, Pisanti N, Klau GW, et al M Martin, M Patterson, S Garg WhatsHap: fast and accurate read-based phasing. bioRxiv 85050 (10.1101), 085050, 2016 | 22 | 2016 |
| On the gapped consecutive-ones property C Chauve, J Maňuch, M Patterson Electronic Notes in Discrete Mathematics 34, 121-125, 2009 | 19 | 2009 |
| Efficient approximate kernel based spike sequence classification S Ali, B Sahoo, MA Khan, A Zelikovsky, IU Khan, M Patterson IEEE/ACM Transactions on Computational Biology and Bioinformatics 20 (6 …, 2022 | 18 | 2022 |
Sarwan AliPh.D. Student, Georgia State University在 student.gsu.edu 的电子邮件经过验证
