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Sebastian Spänig
Sebastian Spänig
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Year
EDGAR 2.0: an enhanced software platform for comparative gene content analyses
J Blom, J Kreis, S Spänig, T Juhre, C Bertelli, C Ernst, A Goesmann
Nucleic acids research 44 (W1), W22-W28, 2016
3582016
The virtual doctor: An interactive clinical-decision-support system based on deep learning for non-invasive prediction of diabetes
S Spänig, A Emberger-Klein, JP Sowa, A Canbay, K Menrad, D Heider
Artificial Intelligence in Medicine 100, 101706, 2019
942019
Encodings and models for antimicrobial peptide classification for multi-resistant pathogens
S Spänig, D Heider
BioData Mining 12, 1-29, 2019
762019
A large-scale comparative study on peptide encodings for biomedical classification
S Spänig, S Mohsen, G Hattab, AC Hauschild, D Heider
NAR Genomics and Bioinformatics 3 (2), lqab039, 2021
172021
Males, the Wrongly Neglected Partners of the Biologically Unprecedented Male–Female Interaction of Schistosomes
Z Lu, S Spänig, O Weth, CG Grevelding
Frontiers in genetics 10, 2019
172019
A multi-omics study on quantifying antimicrobial resistance in European freshwater lakes
S Spänig, L Eick, JK Nuy, D Beisser, M Ip, D Heider, J Boenigk
Environment International 157, 106821, 2021
132021
Multivalent binding kinetics resolved by fluorescence proximity sensing
C Schulte, A Soldà, S Spänig, N Adams, I Bekić, W Streicher, D Heider, ...
Communications biology 5 (1), 1070, 2022
82022
A parametric approach for molecular encodings using multilevel atomic neighborhoods applied to peptide classification
G Hattab, A Anžel, S Spänig, N Neumann, D Heider
NAR Genomics and Bioinformatics 5 (1), lqac103, 2023
12023
Predicting hosts and cross-species transmission of Streptococcus agalactiae by interpretable machine learning
Y Ren, C Li, DN Sapugahawatte, C Zhu, S Spänig, D Jamrozy, J Rothen, ...
Computers in Biology and Medicine, 108185, 2024
2024
Unsupervised encoding selection through ensemble pruning for biomedical classification
S Spänig, A Michel, D Heider
BioData Mining 16 (1), 10, 2023
2023
Integration of Multi-Omic Datasets on Antimicrobial Resistance for Large-Scale Biomedical Data Science
S Spänig
Philipps-Universität Marburg, 2022
2022
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