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2020 – today
- 2023
[j5]Axel Schmidt
, Sebastian Röner, Karola Mai, Hannah Klinkhammer, Martin Kircher, Kerstin U. Ludwig:
Predicting the pathogenicity of missense variants using features derived from AlphaFold2. Bioinform. 39(5) (2023)- 2022
- [j4]Luca Cappelletti, Alessandro Petrini, Jessica Gliozzo, Elena Casiraghi, Max Schubach, Martin Kircher, Giorgio Valentini:
Boosting tissue-specific prediction of active cis-regulatory regions through deep learning and Bayesian optimization techniques. BMC Bioinform. 23-S(2): 154 (2022) - 2020
- [j3]Philip Kleinert, Beth K. Martin, Martin Kircher:
HemoMIPs - Automated analysis and result reporting pipeline for targeted sequencing data. PLoS Comput. Biol. 16(6) (2020) - [c1]Luca Cappelletti, Alessandro Petrini, Jessica Gliozzo, Elena Casiraghi, Max Schubach, Martin Kircher, Giorgio Valentini:
Bayesian Optimization Improves Tissue-Specific Prediction of Active Regulatory Regions with Deep Neural Networks. IWBBIO 2020: 600-612
2010 – 2019
- 2019
- [j2]Philipp Rentzsch, Daniela M. Witten, Gregory M. Cooper, Jay Shendure, Martin Kircher:
CADD: predicting the deleteriousness of variants throughout the human genome. Nucleic Acids Res. 47(Database-Issue): D886-D894 (2019) - 2013
- [j1]Gabriel Renaud, Martin Kircher, Udo Stenzel, Janet Kelso:
freeIbis: an efficient basecaller with calibrated quality scores for Illumina sequencers. Bioinform. 29(9): 1208-1209 (2013) - 2011
- [b1]Martin Kircher:
Understanding and improving high-throughput sequencing data production and analysis. Leipzig University, Germany, 2011
Coauthor Index
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