Edoardo M Airoldi

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Stephen E Fienberg 1942-2016Maurice Falk University Professor of Statistics and Social Science確認したメールアドレス: cs.cmu.edu
David BleiProfessor of Statistics and Computer Science, Columbia University確認したメールアドレス: columbia.edu
Eric XingPresident at Mohamed bin Zayed University of AI, Professor of Computer Science, Carnegie Mellon U確認したメールアドレス: cs.cmu.edu
Gábor CsárdiRStudio確認したメールアドレス: rstudio.com
Panagiotis (Panos) ToulisUniversity of Chicago, Booth School確認したメールアドレス: chicagobooth.edu
Olga TroyanskayaPrinceton University and Flatiron Institute, Simons Foundation確認したメールアドレス: princeton.edu
Alexander FranksDepartment of Statistics and Applied Probability, University of California Santa Barbara確認したメールアドレス: pstat.ucsb.edu
Bradley MalinAccenture Professor of Biomedical Informatics, Biostatistics, and Computer Science, Vanderbilt確認したメールアドレス: vanderbilt.edu
Eric WangUniversity of Florida確認したメールアドレス: ufl.edu
Tamás NepuszDepartment of Biological Physics, Eötvös Loránd University確認したメールアドレス: hal.elte.hu
Margaret E. RobertsPolitical Science, University of California San Diego確認したメールアドレス: ucsd.edu
Brandon StewartAssistant Professor of Sociology, Princeton University確認したメールアドレス: princeton.edu
D. Allan DrummondAssociate Professor, Biochemistry and Molecular Biology, Genetic Medicine確認したメールアドレス: uchicago.edu
Nikolai SlavovNortheastern University, MIT, Princeton University, Harvard University確認したメールアドレス: fas.harvard.edu
Tuan Q. PhanAssociate Professor of Business確認したメールアドレス: hku.hk
David BotsteinPrinceton University確認したメールアドレス: princeton.edu
Patrick J. WolfeProfessor of Statistics, University College London確認したメールアドレス: stat.harvard.edu
Dave ChoiCarnegie Mellon University確認したメールアドレス: andrew.cmu.edu
Stanley H. ChanAssociate Professor of Electrical and Computer Engineering, Purdue University確認したメールアドレス: purdue.edu
Jean Pouget-AbadieGoogle Research確認したメールアドレス: google.com

Edoardo M Airoldi

Professor of Statistics & Data Science Temple University & PI, Harvard University

確認したメールアドレス: fas.harvard.edu

Statistics Causal Inference Network Science Statistical Machine Learning Computational Biology


タイトル引用回数順公開年順タイトル順	引用先引用先	年
Statistical network analysis with the igraph software package G Csárdi, T Nepusz, EM Airoldi New York, NY: Springer, 2016	7713*	2016
Guidelines for the use and interpretation of assays for monitoring autophagy DJ Klionsky, K Abdelmohsen, A Abe, MJ Abedin, H Abeliovich, ... Autophagy 12 (1), 1-222, 2016	7641*	2016
Mixed membership stochastic blockmodels EM Airoldi, DM Blei, SE Fienberg, EP Xing Journal of Machine Learning Research 9 (3), 1981-2014, 2008	2114	2008
Analysis and design of RNA sequencing experiments for identifying isoform regulation Y Katz, ET Wang, EM Airoldi, CB Burge Nature methods 7 (12), 1009-1015, 2010	1190	2010
A survey of statistical network models A Goldenberg, AX Zheng, SE Fienberg, EM Airoldi Foundations and Trends in Machine Learning 2 (2), 129-233, 2010	898	2010
The structural topic model and applied social science ME Roberts, BM Stewart, D Tingley, EM Airoldi NIPS Workshop on Topic Models: Computation, Application, and Evaluation 4, 1-20, 2013	670*	2013
Coordination of growth rate, cell cycle, stress response, and metabolic activity in yeast MJ Brauer, C Huttenhower, EM Airoldi, R Rosenstein, JC Matese, ... Molecular biology of the cell 19 (1), 352-367, 2008	554	2008
A model of text for experimentation in the social sciences ME Roberts, BM Stewart, EM Airoldi Journal of the American Statistical Association 111 (515), 988-1003, 2016	319	2016
Reversible, specific, active aggregates of endogenous proteins assemble upon heat stress EWJ Wallace, JL Kear-Scott, EV Pilipenko, MH Schwartz, PR Laskowski, ... Cell 162 (6), 1286-1298, 2015	276	2015
Systems-level dynamic analyses of fate change in murine embryonic stem cells R Lu, F Markowetz, RD Unwin, JT Leek, EM Airoldi, BD MacArthur, ... Nature 462 (7271), 358-362, 2009	276	2009
Stochastic blockmodels with a growing number of classes DS Choi, PJ Wolfe, EM Airoldi Biometrika 99 (2), 273-284, 2012	226	2012
Mixed membership stochastic block models for relational data with application to protein-protein interactions EM Airoldi, DM Blei, SE Fienberg, EP Xing ENAR International Biometrics Society Annual Meeting, 2006	178	2006
Stochastic blockmodel approximation of a graphon: Theory and consistent estimation EM Airoldi, TB Costa, SH Chan Advances in Neural Information Processing Systems (NIPS), 2013	162	2013
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, 2015	143	2015
Differential stoichiometry among core ribosomal proteins N Slavov, S Semrau, EM Airoldi, B Budnik, A van Oudenaarden Cell Reports, 2015	133	2015
Quantitative visualization of alternative exon expression from RNA-seq data Y Katz, ET Wang, J Silterra, S Schwartz, B Wong, H Thorvaldsdóttir, ... Bioinformatics 31 (14), 2400-2402, 2015	121*	2015
Predicting cellular growth from gene expression signatures EM Airoldi, C Huttenhower, D Gresham, C Lu, AA Caudy, MJ Dunham, ... PLoS Computational Biology 5 (1), e1000257, 2009	120	2009
Integrating utility into face de-identification R Gross, E Airoldi, B Malin, L Sweeney International Workshop on Privacy Enhancing Technologies (PET), 227-242, 2005	119	2005
Summarizing topical content with word frequency and exclusivity J Bischof, EM Airoldi Proceedings of the 29th International Conference on Machine Learning (ICML …, 2012	114	2012
Defining the essential function of yeast Hsf1 reveals a compact transcriptional program for maintaining eukaryotic proteostasis EJ Solís, JP Pandey, X Zheng, DX Jin, PB Gupta, EM Airoldi, D Pincus, ... Molecular Cell, 2016	111	2016

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