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  1. Alexander Franks Bio. I am an Associate Professor in the Department of Statistics and Applied Probability at the University of California, Santa Barbara. My research interests include covariance estimation, sensitivity analysis and causal inference, missing data and measurement error, high throughput applications in biology (“omics”), Bayesian statistics and sports.

    • Publications

      A mixture-of-modelers approach to forecasting NCAA...

    • Teaching

      (Fall18, Fall19, Fall20, Winter22) PSTAT 131: Introduction...

    • CV

      2017 10 Alexander Franks, Edoardo Airoldi, and Nikolai...

  2. Cell 162 (6), 1286-1298. , 2015. 487. 2015. Accounting for experimental noise reveals that mRNA levels, amplified by post-transcriptional processes, largely determine steady-state protein levels in yeast. G Csárdi, A Franks, DS Choi, EM Airoldi, DA Drummond. PLoS genetics 11 (5), e1005206.

  3. www.afranks.com › files › alexander-franks-cv-2021Alexander Franks

    Alexander M Franks, Alexander DAmour, and Avi Feller. Flexible sensitivity analysis for observational studies without observable implica-tions. Journal of the American Statistical Association, pages 1{33, 2019. Albert Chen, Alexander Franks, and Nikolai Slavov. Dart-id in-creases single-cell proteome coverage. PLos Computational Biology, Just ...

  4. Alexander Franks , Gabor Csardi, D. Allan Drummond, and Edoardo M. Airoldi. Estimating a structured covariance model from multilab mesaurements in high-throughput biology. Journal of the American Statistical Association, 110 (509):27--44, 2015 [link] Alexander Franks , Edoardo M. Airoldi, and Donald B. Rubin. Conditionally specified models for ...

  5. Department of Statistics and Applied Probability UC Santa Barbara Santa Barbara CA 93106-3110. Campus MailCode: 3110 Campus Maps

  6. Alex Franks is an Assistant Professor in the Department of Statistics and Applied Probability at the University of California, Santa Barbara. His research interests include multivariate analysis and high dimensional data, causal inference, missing data, and errors-in-variables models. He has applied research interests that include computational ...

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