Chloe-Agathe Azencott, Ph.D.
Affiliations: | 2010 | Computer Science - Ph.D. | University of California, Irvine, Irvine, CA |
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"Chloe-Agathe Azencott"Parents
Sign in to add mentor| Pierre Baldi | grad student | 2010 | UC Irvine | |
| (Statistical machine learning and data mining for chemoinformatics and drug discovery.) | ||||
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Publications
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| Climente-González H, Azencott CA, Kaski S, et al. (2019) Block HSIC Lasso: model-free biomarker detection for ultra-high dimensional data. Bioinformatics (Oxford, England). 35: i427-i435 |
| Azencott CA. (2019) Machine learning and genomics: precision medicine versus patient privacy. Philosophical Transactions. Series a, Mathematical, Physical, and Engineering Sciences. 376 |
| Playe B, Azencott CA, Stoven V. (2018) Efficient multi-task chemogenomics for drug specificity prediction. Plos One. 13: e0204999 |
| Grimm DG, Azencott CA, Aicheler F, et al. (2015) The evaluation of tools used to predict the impact of missense variants is hindered by two types of circularity. Human Mutation. 36: 513-23 |
| Kayala MA, Azencott CA, Chen JH, et al. (2011) Learning to predict chemical reactions. Journal of Chemical Information and Modeling. 51: 2209-22 |
| Baldi P, Azencott C, Swamidass SJ. (2011) Bridging the gap between neural network and kernel methods: Applications to drug discovery Frontiers in Artificial Intelligence and Applications. 226: 3-13 |
| Swamidass SJ, Azencott CA, Daily K, et al. (2010) A CROC stronger than ROC: measuring, visualizing and optimizing early retrieval. Bioinformatics (Oxford, England). 26: 1348-56 |
| Swamidass SJ, Azencott CA, Lin TW, et al. (2009) Influence relevance voting: an accurate and interpretable virtual high throughput screening method. Journal of Chemical Information and Modeling. 49: 756-66 |
| Azencott CA, Ksikes A, Swamidass SJ, et al. (2007) One- to four-dimensional kernels for virtual screening and the prediction of physical, chemical, and biological properties. Journal of Chemical Information and Modeling. 47: 965-74 |