Verena Rubel
Postdoc
Address
Erwin-Schroedinger-Street
Building 14, Room 262
67663 Kaiserslautern
Postbox 3049
67663 Kaiserslautern
Contact
Tel.: +49 631 205 3253
E-Mail: v.rubel(at)rhrk.uni-kl.de
Curriculum Vitae
| 2022 | Ph.D., University of Kaiserslautern |
| 2019 | M. Sc., University of Kaiserslautern |
| 2017 | B. Sc., University of Kaiserslautern |
Publications
2021
Dully V, Rech G, Wilding TA, Lanzén A, MacKichan K, Berrill I & Stoeck T
Comparing sediment preservation methods for genomic biomonitoring of coastal marine ecosystems.
Marine Pollution Bulletin 173: 113129, doi: 10.1016/j.marpolbul.2021.113129
Dully V, Wilding TA, Mühlhaus T & Stoeck T
Identifying the minimum amplicon sequence depth to adequately predict classes in eDNA-based marine biomonitoring using supervised machine learning
Computational and Structural Biotechnolgy Journal 19: 2256-2268, doi: 10.1016/j.csbj.2021.04.005
Frühe L, Dully V, Forster D, Keeley NB, Laroche O, Pochon X, Robinson SMC, Wilding TA & Stoeck T
Global trends of benthic bacterial diversity and community composition along organic enrichment gradients of salmon farms
Frontiers in Microbiology (section Aquatic Microbiology) 12: 637811, doi: 10.3389/fmicb.2021.637811
2020
Dully V, Balliet H, Frühe L, Däumer M, Thielen A, Gallie S, Berril I & Stoeck T
Robustness, sensitivity and reproducibility of eDNA metabarcoding as an environmental biomonitoring tool in coastal salmon aquaculture - An inter-laboratory study.
Ecological Indicators, doi: 10.1016/j.ecolind.2020.107049
Frühe L, Cordier T, Dully V, Breiner HW, Lentendu G, Pawlowski J, Martins C, Wilding TA & Stoeck T
Supervised machine learning is superior to indicator value inference in monitoring the environmental impacts of salmon aquaculture using eDNA metabarcodes.
Molecular Ecology, doi: 10.1111/mec15434
2018
Stoeck T, Pan H, Dully V, Forster D & Jung T
Towards an eDNA metabarcode-based performance indicator for full-scale municipal wastewater treatment plants.
Water Research, doi: 10.1016/j.watres.2019.07.051
| 2021 | Predicting classifications in marine biomonitoring with supervised machine learning: how much data is required? 1. DNAqua International Conference, Evian, France |
| 2021 | Towards a standard protocol in coastal aquaculture biomonitoring: an interlaboratory study to assess reproducibility of the wet lab protocol and of Illumina sequencing (poster) 1. DNAqua International Conference, Evian, France |
| 2020 | Inter-laboratory reproducibility of machine learning predictions in applied environmental coastal monitoring Faculty meeting, University of Kaiserslautern |
| 2021 | Award for the best student oral presentation 1. DNAqua International Conference, Evian, France |
| 2020 | Award for an outstanding Master thesis Kreissparkassen-Stiftung Kaiserslautern |