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1.
Han, S. et al.: TIGER: Technical variation elimination for metabolomics data using ensemble learning architecture. Brief. Bioinform. 23:bbab535 (2022)
2.
Villaverde, A.F.* ; Pathirana, D.* ; Fröhlich, F. ; Hasenauer, J.* & Banga, J.R.*: A protocol for dynamic model calibration. Brief. Bioinform. 23:bbab387 (2022)
3.
Deutelmoser, H.* et al.: Robust Huber-LASSO for improved prediction of protein, metabolite and gene expression levels relying on individual genotype data. Brief. Bioinform. 22:bbaa230 (2021)
4.
Peschel, S. ; Müller, C. ; von Mutius, E. ; Boulesteix, A.L.* & Depner, M.: NetCoMi: Network construction and comparison for microbiome data in R. Brief. Bioinform. 22, DOI: 10.1093/bib/bbaa290 (2021)
5.
Guala, D.* ; Ogris, C. ; Müller, N.S. & Sonnhammer, E.L.L.*: Genome-wide functional association networks: Background, data & state-of-the-art resources. Brief. Bioinform. 21, 1224-1237 (2020)
6.
Hoksza, D.* ; Gawron, P.* ; Ostaszewski, M.* ; Hasenauer, J. & Schneider, R.*: Closing the gap between formats for storing layout information in systems biology. Brief. Bioinform. 21, 1249-1260 (2020)
7.
Hoksza, D.* ; Gawron, P.* ; Ostaszewski, M.* ; Hasenauer, J. & Schneider, R.*: Closing the gap between formats for storing layout information in systems biology. Brief. Bioinform. 22, 608 (2020)
8.
Omony, J. ; Nussbaumer, T. & Gutzat, R.*: DNA methylation analysis in plants: review of computational tools and future perspectives. Brief. Bioinform. 21, 906-918 (2020)
9.
Pitea, A. et al.: Copy number aberrations from Affymetrix SNP 6.0 genotyping data-how accurate are commonly used prediction approaches? Brief. Bioinform. 21, 272-281 (2020)
10.
Ostaszewski, M.* et al.: Community-driven roadmap for integrated disease maps. Brief. Bioinform. 20, 659-670 (2019)
11.
Villmann, T.* ; Schleif, F.M.* ; Kostrzewa, M.* ; Walch, A.K. & Hammer, B.*: Classification of mass-spectrometric data in clinical proteomics using learning vector quantization methods. Brief. Bioinform. 9, 129-143 (2008)
12.
Yuille, M.* et al.: Biobanking for Europe. Brief. Bioinform. 9, 14-24 (2008)
13.
Mueller, J.C.: Linkage disequilibrium for different scales and applications. Brief. Bioinform. 5, 1-10 (2004)
14.
Werner, T.: The state of the art of mammalian promoter recognition. Brief. Bioinform. 4, 22-30 (2003)
15.
Hrabě de Angelis, M. & Strivens, M.*: Large-scale production of mouse phenotypes : the search for animal models for inherited diseases in humans. Brief. Bioinform. 2, 170-180 (2001)
16.
Werner, T.: Identification and functional modelling of DNA sequence elements of transcription. Brief. Bioinform. 1, 372-380 (2000)