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  • Author: Li SC
  • References

Author: Li SC


References 21 references


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  • Iyer KR, et al. (2023) Identification of triazenyl indoles as inhibitors of fungal fatty acid biosynthesis with broad-spectrum activity. Cell Chem Biol 30(7):795-810.e8 PMID:37369212
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  • Forster DT, et al. (2022) BIONIC: biological network integration using convolutions. Nat Methods 19(10):1250-1261 PMID:36192463
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  • Ohnuki S, et al. (2022) High-throughput platform for yeast morphological profiling predicts the targets of bioactive compounds. NPJ Syst Biol Appl 8(1):3 PMID:35087094
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  • Persaud R, et al. (2022) Clionamines stimulate autophagy, inhibit Mycobacterium tuberculosis survival in macrophages, and target Pik1. Cell Chem Biol 29(5):870-882.e11 PMID:34520745
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  • Safizadeh H, et al. (2021) Improving Measures of Chemical Structural Similarity Using Machine Learning on Chemical-Genetic Interactions. J Chem Inf Model 61(9):4156-4172 PMID:34318674
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  • Zhou FL, et al. (2020) Publisher Correction: Integrating yeast chemical genomics and mammalian cell pathway analysis. Acta Pharmacol Sin 41(5):729 PMID:32081979
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  • Simpkins SW, et al. (2019) Using BEAN-counter to quantify genetic interactions from multiplexed barcode sequencing experiments. Nat Protoc 14(2):415-440 PMID:30635653
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  • Zhou FL, et al. (2019) Integrating yeast chemical genomics and mammalian cell pathway analysis. Acta Pharmacol Sin 40(9):1245-1255 PMID:31138898
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  • de Paula E Silva ACA, et al. (2019) Decyl Gallate as a Possible Inhibitor of N-Glycosylation Process in Paracoccidioides lutzii. Antimicrob Agents Chemother 63(11) PMID:31451502
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  • Nelson J, et al. (2018) MOSAIC: a chemical-genetic interaction data repository and web resource for exploring chemical modes of action. Bioinformatics 34(7):1251-1252 PMID:29206899
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  • Simpkins SW, et al. (2018) Predicting bioprocess targets of chemical compounds through integration of chemical-genetic and genetic interactions. PLoS Comput Biol 14(10):e1006532 PMID:30376562
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  • Piotrowski JS, et al. (2017) Functional annotation of chemical libraries across diverse biological processes. Nat Chem Biol 13(9):982-993 PMID:28759014
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  • Costanzo M, et al. (2016) A global genetic interaction network maps a wiring diagram of cellular function. Science 353(6306) PMID:27708008
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  • Shin JJ, et al. (2016) Systematic identification of genes involved in metabolic acid stress resistance in yeast and their potential as cancer targets. Dis Model Mech 9(9):1039-49 PMID:27519690
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  • Piotrowski JS, et al. (2015) Plant-derived antifungal agent poacic acid targets β-1,3-glucan. Proc Natl Acad Sci U S A 112(12):E1490-7 PMID:25775513
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  • Piotrowski JS, et al. (2015) Chemical genomic profiling via barcode sequencing to predict compound mode of action. Methods Mol Biol 1263:299-318 PMID:25618354
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  • Li SC, et al. (2014) The signaling lipid PI(3,5)P₂ stabilizes V₁-V(o) sector interactions and activates the V-ATPase. Mol Biol Cell 25(8):1251-62 PMID:24523285
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  • Li SC, et al. (2012) Vacuolar H+-ATPase works in parallel with the HOG pathway to adapt Saccharomyces cerevisiae cells to osmotic stress. Eukaryot Cell 11(3):282-91 PMID:22210831
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  • Lin M, et al. (2012) Regulation of vacuolar H+-ATPase activity by the Cdc42 effector Ste20 in Saccharomyces cerevisiae. Eukaryot Cell 11(4):442-51 PMID:22327006
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  • Young BP, et al. (2010) Phosphatidic acid is a pH biosensor that links membrane biogenesis to metabolism. Science 329(5995):1085-8 PMID:20798321
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  • Li SC and Kane PM (2009) The yeast lysosome-like vacuole: endpoint and crossroads. Biochim Biophys Acta 1793(4):650-63 PMID:18786576
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