| Fixed-parameter algorithms for scaffold filling L Bulteau, AP Carrieri, R Dondi Theoretical Computer Science 568, 72-83, 2015 | 17 | 2015 |
| Streaming histogram sketching for rapid microbiome analytics WPM Rowe, AP Carrieri, C Alcon-Giner, S Caim, A Shaw, K Sim, JS Kroll, ... Microbiome 7 (1), 1-13, 2019 | 15 | 2019 |
| Explaining evolution via constrained persistent perfect phylogeny P Bonizzoni, AP Carrieri, G Della Vedova, G Trucco BMC genomics 15 (S6), S10, 2014 | 13 | 2014 |
| When and how the perfect phylogeny model explains evolution P Bonizzoni, AP Carrieri, G Della Vedova, R Dondi, TM Przytycka Discrete and Topological Models in Molecular Biology, 67-83, 2014 | 11 | 2014 |
| A colored graph approach to perfect phylogeny with persistent characters P Bonizzoni, AP Carrieri, G Della Vedova, R Rizzi, G Trucco Theoretical Computer Science 658, 60-73, 2017 | 10 | 2017 |
| Human Skin, Oral, and Gut Microbiomes Predict Chronological Age S Huang, N Haiminen, AP Carrieri, R Hu, L Jiang, L Parida, B Russell, ... Msystems 5 (1), 2020 | 8 | 2020 |
| Topological signatures for population admixture L Parida, F Utro, D Yorukoglu, AP Carrieri, D Kuhn, S Basu International Conference on Research in Computational Molecular Biology, 261-275, 2015 | 7 | 2015 |
| A fast machine learning workflow for rapid phenotype prediction from whole shotgun metagenomes AP Carrieri, WPM Rowe, M Winn, EO Pyzer-Knapp Proceedings of the AAAI Conference on Artificial Intelligence 33, 9434-9439, 2019 | 6 | 2019 |
| Accelerating molecular discovery through data and physical sciences: Applications to peptide-membrane interactions F Cipcigan, AP Carrieri, EO Pyzer-Knapp, R Krishna, YW Hsiao, M Winn, ... The Journal of chemical physics 148 (24), 241744, 2018 | 6 | 2018 |
| Host phenotype prediction from differentially abundant microbes using rodeo AP Carrieri, N Haiminen, L Parida International Meeting on Computational Intelligence Methods for …, 2016 | 5 | 2016 |
| Sampling ARG of multiple populations under complex configurations of subdivision and admixture AP Carrieri, F Utro, L Parida Bioinformatics 32 (7), 1048-1056, 2016 | 3 | 2016 |
| Explainable AI reveals changes in skin microbiome composition linked to phenotypic differences AP Carrieri, N Haiminen, S Maudsley-Barton, LJ Gardiner, B Murphy, ... bioRxiv, 2020 | 2* | 2020 |
| Utilizing stability criteria in choosing feature selection methods yields reproducible results in microbiome data L Jiang, N Haiminen, AP Carrieri, S Huang, Y Vázquez-Baeza, L Parida, ... arXiv preprint arXiv:2012.00001, 2020 | | 2020 |
| Challenges in Benchmarking Metagenomic Profilers YY Liu, Z Sun, S Huang, M Zhang, QY Zhu, N Haiminen, AP Carrieri, ... | | 2020 |
| Using human in vitro transcriptome analysis to build trustworthy machine learning models for prediction of animal drug toxicity LJ Gardiner, AP Carrieri, J Wilshaw, S Checkley, EO Pyzer-Knapp, ... Scientific Reports 10 (1), 1-8, 2020 | | 2020 |
| Microbial context predicts SARS-CoV-2 prevalence in patients and the hospital built environment C Marotz, P Belda-Ferre, F Ali, P Das, S Huang, K Cantrell, L Jiang, ... medRxiv, 2020 | | 2020 |
| Challenges in Benchmarking Metagenomic Profilers Z Sun, S Huang, M Zhang, Q Zhu, N Haiminen, AP Carrieri, ... bioRxiv, 2020 | | 2020 |
| EMPress enables tree-guided, interactive, and exploratory analyses of multi-omic datasets K Cantrell, MW Fedarko, G Rahman, D McDonald, Y Yang, T Zaw, ... bioRxiv, 2020 | | 2020 |
| Using human in vitro transcriptome analysis to build trustworthy machine learning models for prediction of animal drug toxicity G Laura-Jayne, AP Carrieri, J Wilshaw, S Checkley, EO Pyzer-Knapp, ... Scientific Reports (Nature Publisher Group) 10 (1), 2020 | | 2020 |
| Combining human cell line transcriptome analysis and Bayesian inference to build trustworthy machine learning models for prediction of animal toxicity in drug development LJ Gardiner, AP Carrieri, J Wilshaw, S Checkley, EO Pyzer-Knapp, ... arXiv preprint arXiv:1911.04374, 2019 | | 2019 |
Laxmi ParidaIBM ResearchAdresse e-mail validée de us.ibm.com
