Florian Nigsch
Affiliations: | 2005-2008 | Chemistry | University of Cambridge, Cambridge, England, United Kingdom |
2009- | Novartis Institutes for BioMedical Research, Cambridge, MA, United States |
Website:
https://www.novartis.com/our-science/postdoc-program/research-themes/computational-sciences/florian-nigsch-phdGoogle:
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Publications
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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 |