Florian Nigsch

2005-2008 Chemistry University of Cambridge, Cambridge, England, United Kingdom 
 2009- Novartis Institutes for BioMedical Research, Cambridge, MA, United States 
"Florian Nigsch"
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Dafflon C, Craig VJ, Méreau H, et al. (2016) Complementary activities of DOT1L and Menin inhibitors in MLL-rearranged leukemia. Leukemia
Paricharak S, IJzerman AP, Jenkins JL, et al. (2016) Data-driven Derivation of an "Informer Compound Set" for Improved Selection of Active Compounds in High-Throughput Screening. Journal of Chemical Information and Modeling
Wang Y, Cornett A, King FJ, et al. (2016) Evidence-Based and Quantitative Prioritization of Tool Compounds in Phenotypic Drug Discovery. Cell Chemical Biology
Paricharak S, IJzerman AP, Bender A, et al. (2016) Analysis of Iterative Screening with Stepwise Compound Selection Based on Novartis In-house HTS Data. Acs Chemical Biology. 11: 1255-64
Jaeger S, Min J, Nigsch F, et al. (2014) Causal Network Models for Predicting Compound Targets and Driving Pathways in Cancer. Journal of Biomolecular Screening. 19: 791-802
Hoepfner D, Helliwell SB, Sadlish H, et al. (2014) High-resolution chemical dissection of a model eukaryote reveals targets, pathways and gene functions. Microbiological Research. 169: 107-20
Hutz JE, Nelson T, Wu H, et al. (2013) The multidimensional perturbation value: a single metric to measure similarity and activity of treatments in high-throughput multidimensional screens. Journal of Biomolecular Screening. 18: 367-77
Petrone PM, Simms B, Nigsch F, et al. (2012) Rethinking molecular similarity: comparing compounds on the basis of biological activity. Acs Chemical Biology. 7: 1399-409
Nigsch F, Hutz J, Cornett B, et al. (2012) Determination of minimal transcriptional signatures of compounds for target prediction. Eurasip Journal On Bioinformatics & Systems Biology. 2012: 2
Lowe R, Mussa HY, Nigsch F, et al. (2012) Predicting the mechanism of phospholipidosis. Journal of Cheminformatics. 4: 2
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