Benchmarks in antimicrobial peptide prediction are biased due to the selection of negative data K Sidorczuk, P Gagat, F Pietluch, J Kała, D Rafacz, L Bąkała, J Słowik, ... Briefings in Bioinformatics 23 (5), bbac343, 2022 | 35 | 2022 |
ampir: an R package for fast genome-wide prediction of antimicrobial peptides LCHW Fingerhut, DJ Miller, JM Strugnell, NL Daly, IR Cooke Bioinformatics 36 (21), 5262-5263, 2020 | 34 | 2020 |
Shotgun Proteomics Analysis of Saliva and Salivary Gland Tissue from the Common Octopus Octopus vulgaris LCHW Fingerhut, JM Strugnell, P Faou, AR Labiaga, J Zhang, IR Cooke Journal of proteome research 17 (11), 3866-3876, 2018 | 24 | 2018 |
The impact of negative data sampling on antimicrobial peptide prediction K Sidorczuk, P Gagat, F Pietluch, J Kała, D Rafacz, L Bąkała, J Słowik, ... bioRxiv, 2022.05. 30.493946, 2022 | 1 | 2022 |
Identifying antimicrobial peptides in genomes using machine learning LCHW Fingerhut James Cook University, 2022 | | 2022 |