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Konstantin Bob
Konstantin Bob
Verified email at uni-mainz.de
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Cited by
Cited by
Year
The effect of numerical aperture on quantitative use-wear studies and its implication on reproducibility
I Calandra, L Schunk, K Bob, W Gneisinger, A Pedergnana, E Paixao, ...
Scientific reports 9 (1), 6313, 2019
282019
Polish is quantitatively different on quartzite flakes used on different worked materials
A Pedergnana, I Calandra, AA Evans, K Bob, A Hildebrandt, A Olle
Plos one 15 (12), e0243295, 2020
172020
Evaluating the microscopic effect of brushing stone tools as a cleaning procedure
A Pedergnana, I Calandra, K Bob, W Gneisinger, E Paixao, L Schunk, ...
Quaternary International 569, 263-276, 2020
162020
Surface texture analysis in Toothfrax and MountainsMap® SSFA module: Different software packages, different results?
I Calandra, K Bob, G Merceron, F Blateyron, A Hildebrandt, ...
Peer Community Journal 2, 2022
52022
Locality-sensitive hashing enables efficient and scalable signal classification in high-throughput mass spectrometry raw data
K Bob, D Teschner, T Kemmer, D Gomez-Zepeda, S Tenzer, B Schmidt, ...
BMC bioinformatics 23 (1), 1-16, 2022
42022
CorCast: A Distributed Architecture for Bayesian Epidemic Nowcasting and its Application to District-Level SARS-CoV-2 Infection Numbers in Germany
AK Hildebrandt, K Bob, D Teschner, T Kemmer, J Leclaire, B Schmidt, ...
medRxiv, 2021.06. 02.21258209, 2021
42021
Ionmob: A Python Package for Prediction of Peptide Collisional Cross-Section Values
D Teschner, D Gomez-Zepeda, A Declercq, MK Łącki, S Avci, K Bob, ...
Bioinformatics, btad486, 2023
32023
Enhancing lithic analysis: Introducing 3D-EdgeAngle as a semi-automated 3D digital method to systematically quantify stone tool edge angle and design
L Schunk, A Cramer, K Bob, I Calandra, G Heinz, O Jöris, J Marreiros
12023
Bestimmung von Pionzerfallsraten für Hyperkernexperimente an MAMI
K Bob
Bachelorarbeit, Johannes Gutenberg-Universität, Mainz, 2014
12014
Modern methods in bayesian probabilistic modeling and their applications.
K Bob
University of Mainz, Germany, 2022
2022
Locality-sensitive hashing enables signal classification in high-throughput mass spectrometry raw data at scale
K Bob, D Teschner, T Kemmer, D Gomez-Zepeda, S Tenzer, B Schmidt, ...
bioRxiv, 2021.07. 01.450702, 2021
2021
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