Edoardo M Airoldi - Google Scholar Citations

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引用	14008	11296
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i10 指標	84	72

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共著者

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 XingProfessor of Machine Learning, Language Technology, Computer Science, Cargenie Mellon University確認したメールアドレス: cs.cmu.edu
Olga TroyanskayaPrinceton University and Flatiron Institute, Simons Foundation確認したメールアドレス: princeton.edu
Panagiotis (Panos) ToulisUniversity of Chicago, Booth School確認したメールアドレス: chicagobooth.edu
Bradley MalinProfessor of Biomedical Informatics, Biostatistics, and Computer Science, Vanderbilt確認したメールアドレス: vanderbilt.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
Eric WangUniversity of Florida確認したメールアドレス: ufl.edu
David BotsteinPrinceton University確認したメールアドレス: princeton.edu
D. Allan DrummondAssociate Professor, Biochemistry and Molecular Biology, Human Genetics確認したメールアドレス: uchicago.edu
Tuan Q. PhanAssociate Professor of Business確認したメールアドレス: hku.hk
Nikolai SlavovNortheastern University, MIT, Princeton University, Harvard University確認したメールアドレス: fas.harvard.edu
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
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. ChanAssistant Professor of Electrical and Computer Engineering, Purdue University確認したメールアドレス: purdue.edu
Gábor CsárdiRStudio確認したメールアドレス: rstudio.com
Bang WongBroad Institute of MIT & Harvard確認したメールアドレス: broadinstitute.org
Alexander VolfovskyDuke University確認したメールアドレス: duke.edu

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 - ホームページ

Statistics Causal Inference Network Science Statistical Machine Learning Computational Biology


タイトル	引用先	年
Guidelines for the use and interpretation of assays for monitoring autophagy DJ Klionsky, FC Abdalla, H Abeliovich, RT Abraham, A Acevedo-Arozena, ... Autophagy 8 (4), 445-544, 2012	5962*	2012
Mixed membership stochastic blockmodels EM Airoldi, DM Blei, SE Fienberg, EP Xing Journal of Machine Learning Research 9 (3), 1981-2014, 2008	1725	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, 2010	981	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	713	2010
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	474	2008
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, 2009	247	2009
Stochastic blockmodels with a growing number of classes DS Choi, PJ Wolfe, EM Airoldi Biometrika 99 (2), 273-284, 2012	188	2012
A model of text for experimentation in the social sciences ME Roberts, BM Stewart, EM Airoldi Journal of the American Statistical Association, 00-00, 2016	175	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	162	2015
The structural topic model and applied social science ME Roberts, BM Stewart, D Tingley, EM Airoldi Advances in neural information processing systems workshop on topic models …, 2013	144*	2013
Mixed membership stochastic block models for relational data with application to protein-protein interactions EM Airoldi, DM Blei, SE Fienberg, EP Xing Proceedings of the international biometrics society annual meeting, 2006	137	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	118	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	106	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	103	2009
Integrating utility into face de-identification R Gross, E Airoldi, B Malin, L Sweeney International Workshop on Privacy Enhancing Technologies, 227-242, 2005	95	2005
Differential stoichiometry among core ribosomal proteins N Slavov, S Semrau, EM Airoldi, B Budnik, A van Oudenaarden Cell Reports, 2015	91	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	83*	2015
A network analysis model for disambiguation of names in lists B Malin, E Airoldi, KM Carley Computational & Mathematical Organization Theory 11 (2), 119-139, 2005	80	2005
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	78	2016
Handbook of Mixed Membership Models and Their Applications EM Airoldi, DM Blei, EA Erosheva, SE Fienberg Chapman & Hall/CRC, 2014	75	2014

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