| Year |
Citation |
Score |
| 2019 |
Hung YC, Michailidis G. Modeling and Optimization of Time-Of-Use Electricity Pricing Systems. Ieee Transactions On Smart Grid. 10: 4116-4127. PMID 32864049 DOI: 10.1109/Tsg.2018.2850326 |
0.551 |
|
| 2019 |
Ma J, Shojaie A, Michailidis G. A comparative study of topology-based pathway enrichment analysis methods. Bmc Bioinformatics. 20: 546. PMID 31684881 DOI: 10.1186/S12859-019-3146-1 |
0.585 |
|
| 2019 |
Hung Y, Michailidis G. Modeling and Optimization of Time-of-Use Electricity Pricing Systems Ieee Transactions On Smart Grid. 10: 4116-4127. DOI: 10.1109/TSG.2018.2850326 |
0.512 |
|
| 2016 |
Ma J, Shojaie A, Michailidis G. Network-based pathway enrichment analysis with incomplete network information. Bioinformatics (Oxford, England). PMID 27357170 DOI: 10.1093/Bioinformatics/Btw410 |
0.614 |
|
| 2016 |
Kaushik AK, Shojaie A, Panzitt K, Sonavane R, Venghatakrishnan H, Manikkam M, Zaslavsky A, Putluri V, Vasu VT, Zhang Y, Khan AS, Lloyd S, Szafran AT, Dasgupta S, Bader DA, ... ... Michailidis G, et al. Inhibition of the hexosamine biosynthetic pathway promotes castration-resistant prostate cancer. Nature Communications. 7: 11612. PMID 27194471 DOI: 10.1038/Ncomms11612 |
0.573 |
|
| 2016 |
Kallitsis M, Stoev SA, Bhattacharya S, Michailidis G. AMON: An Open Source Architecture for Online Monitoring, Statistical Analysis, and Forensics of Multi-Gigabit Streams Ieee Journal On Selected Areas in Communications. 34: 1834-1848. DOI: 10.1109/Jsac.2016.2558958 |
0.356 |
|
| 2016 |
Xia D, Mankad S, Michailidis G. Measuring Influence of Users in Twitter Ecosystems Using a Counting Process Modeling Framework Technometrics. 58: 360-370. DOI: 10.1080/00401706.2016.1142906 |
0.324 |
|
| 2015 |
Basu S, Shojaie A, Michailidis G. Network Granger Causality with Inherent Grouping Structure. Journal of Machine Learning Research : Jmlr. 16: 417-453. PMID 34267606 |
0.611 |
|
| 2015 |
Guo J, Cheng J, Levina E, Michailidis G, Zhu J. ESTIMATING HETEROGENEOUS GRAPHICAL MODELS FOR DISCRETE DATA WITH AN APPLICATION TO ROLL CALL VOTING. The Annals of Applied Statistics. 9: 821-848. PMID 27182289 DOI: 10.1214/13-Aoas700 |
0.431 |
|
| 2015 |
Guo J, Levina E, Michailidis G, Zhu J. Graphical Models for Ordinal Data. Journal of Computational and Graphical Statistics : a Joint Publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America. 24: 183-204. PMID 26120267 DOI: 10.1080/10618600.2014.889023 |
0.389 |
|
| 2015 |
Mankad S, Michailidis G, Banerjee M. Threshold value estimation using adaptive two-stage plans in R Journal of Statistical Software. 67. DOI: 10.18637/Jss.V067.I03 |
0.347 |
|
| 2015 |
Basu S, Michailidis G. Regularized estimation in sparse high-dimensional time series models Annals of Statistics. 43: 1535-1567. DOI: 10.1214/15-Aos1315 |
0.378 |
|
| 2015 |
Mankad S, Michailidis G. Analysis of multiview legislative networks with structured matrix factorization: Does twitter influence translate to the real world? Annals of Applied Statistics. 9: 1950-1972. DOI: 10.1214/15-Aoas858 |
0.341 |
|
| 2015 |
Tang R, Banerjee M, Michailidis G, Mankad S. Two-Stage Plans for Estimating the Inverse of a Monotone Function Technometrics. 57: 395-407. DOI: 10.1080/00401706.2014.940773 |
0.49 |
|
| 2015 |
Hung YC, Michailidis G. Optimal routing for electric vehicle service systems European Journal of Operational Research. 247: 515-524. DOI: 10.1016/j.ejor.2015.06.013 |
0.491 |
|
| 2015 |
Lim N, d’Alché-Buc F, Auliac C, Michailidis G. Operator-valued kernel-based vector autoregressive models for network inference Machine Learning. 99: 489-513. DOI: 10.1007/S10994-014-5479-3 |
0.37 |
|
| 2015 |
Basu S, Shojaie A, Michailidis G. Network Granger causality with inherent grouping structure Journal of Machine Learning Research. 16: 417-453. |
0.533 |
|
| 2014 |
Șenbabaoğlu Y, Michailidis G, Li JZ. Critical limitations of consensus clustering in class discovery. Scientific Reports. 4: 6207. PMID 25158761 DOI: 10.1038/Srep06207 |
0.697 |
|
| 2014 |
Henderson J, Michailidis G. Network reconstruction using nonparametric additive ODE models. Plos One. 9: e94003. PMID 24732037 DOI: 10.1371/Journal.Pone.0094003 |
0.397 |
|
| 2014 |
Shojaie A, Jauhiainen A, Kallitsis M, Michailidis G. Inferring regulatory networks by combining perturbation screens and steady state gene expression profiles. Plos One. 9: e82393. PMID 24586224 DOI: 10.1371/Journal.Pone.0082393 |
0.651 |
|
| 2014 |
Kaushik AK, Vareed SK, Basu S, Putluri V, Putluri N, Panzitt K, Brennan CA, Chinnaiyan AM, Vergara IA, Erho N, Weigel NL, Mitsiades N, Shojaie A, Palapattu G, Michailidis G, et al. Metabolomic profiling identifies biochemical pathways associated with castration-resistant prostate cancer. Journal of Proteome Research. 13: 1088-100. PMID 24359151 DOI: 10.1021/Pr401106H |
0.589 |
|
| 2014 |
Hung YC, Michailidis G, Chuang SC. Estimation and monitoring of traffic intensities with application to control of stochastic systems Applied Stochastic Models in Business and Industry. 30: 200-217. DOI: 10.1002/Asmb.1961 |
0.573 |
|
| 2013 |
Michailidis G, d'Alché-Buc F. Autoregressive models for gene regulatory network inference: sparsity, stability and causality issues. Mathematical Biosciences. 246: 326-34. PMID 24176667 DOI: 10.1016/J.Mbs.2013.10.003 |
0.379 |
|
| 2013 |
Lim N, Senbabaoglu Y, Michailidis G, d'Alché-Buc F. OKVAR-Boost: a novel boosting algorithm to infer nonlinear dynamics and interactions in gene regulatory networks. Bioinformatics (Oxford, England). 29: 1416-23. PMID 23574736 DOI: 10.1093/Bioinformatics/Btt167 |
0.749 |
|
| 2013 |
Panzitt K, Shojaie A, Putluri N, Basu S, Putluri V, Samanta S, Ittmann M, Vergara I, Michailidis G, Palapattu G, Sreekumar A. Abstract 5387: Integrative analysis of transcriptomic and metabolomic data reveals a critical role for aminosugar metabolism in prostate cancer. Cancer Research. 73: 5387-5387. DOI: 10.1158/1538-7445.Am2013-5387 |
0.569 |
|
| 2013 |
Kallitsis MG, Stoev SA, Michailidis G. Fast algorithms for optimal link selection in large-scale network monitoring Ieee Transactions On Signal Processing. 61: 2088-2103. DOI: 10.1109/Tsp.2013.2242066 |
0.359 |
|
| 2013 |
Katenka N, Levina E, Michailidis G. Tracking multiple targets using binary decisions from wireless sensor networks Journal of the American Statistical Association. 108: 398-410. DOI: 10.1080/01621459.2013.770284 |
0.735 |
|
| 2013 |
Vaughan J, Stoev S, Michailidis G. Network-wide statistical modeling, prediction, and monitoring of computer traffic Technometrics. 55: 79-93. DOI: 10.1080/00401706.2012.723959 |
0.602 |
|
| 2013 |
Hamidieh K, Stoev S, Michailidis G. Intensity-based estimation of extreme loss event probability and value at risk Applied Stochastic Models in Business and Industry. 29: 171-186. DOI: 10.1002/Asmb.1915 |
0.754 |
|
| 2012 |
Jauhiainen A, Nerman O, Michailidis G, Jörnsten R. Transcriptional and metabolic data integration and modeling for identification of active pathways. Biostatistics (Oxford, England). 13: 748-61. PMID 22699861 DOI: 10.1093/Biostatistics/Kxs016 |
0.351 |
|
| 2012 |
Farfán F, Ma J, Sartor MA, Michailidis G, Jagadish HV. THINK Back: KNowledge-based Interpretation of High Throughput data. Bmc Bioinformatics. 13: S4. PMID 22536867 DOI: 10.1186/1471-2105-13-S2-S4 |
0.348 |
|
| 2012 |
Hamidieh K, Stoev S, Michailidis G. Intensity Based Estimation of Extreme Loss Event Probability and Value-at-Risk Applied Stochastic Models in Business and Industry. 29: 171-186. DOI: 10.2139/Ssrn.1107538 |
0.753 |
|
| 2012 |
Singhal H, Michailidis G. Optimal experiment design in a filtering context with application to sampled network data Annals of Applied Statistics. 6: 78-93. DOI: 10.1214/09-Aoas283 |
0.566 |
|
| 2012 |
Kallitsis MG, Michailidis G, Devetsikiotis M. Optimal power allocation under communication network externalities Ieee Transactions On Smart Grid. 3: 162-173. DOI: 10.1109/Tsg.2011.2169995 |
0.323 |
|
| 2012 |
Hung YC, Michailidis G. Stability and control of acyclic stochastic processing networks with shared resources Ieee Transactions On Automatic Control. 57: 489-494. DOI: 10.1109/Tac.2011.2164012 |
0.607 |
|
| 2012 |
Shojaie A, Basu S, Michailidis G. Adaptive Thresholding for Reconstructing Regulatory Networks from Time-Course Gene Expression Data Statistics in Biosciences. 4: 66-83. DOI: 10.1007/S12561-011-9050-5 |
0.653 |
|
| 2011 |
Mallik A, Sen B, Banerjee M, Michailidis G. Threshold estimation based on a p-value framework in dose-response and regression settings. Biometrika. 98: 887-900. PMID 23049132 DOI: 10.1093/Biomet/Asr051 |
0.345 |
|
| 2011 |
Guo J, Levina E, Michailidis G, Zhu J. Joint estimation of multiple graphical models. Biometrika. 98: 1-15. PMID 23049124 DOI: 10.1093/Biomet/Asq060 |
0.408 |
|
| 2011 |
Putluri N, Shojaie A, Vasu VT, Vareed SK, Nalluri S, Putluri V, Thangjam GS, Panzitt K, Tallman CT, Butler C, Sana TR, Fischer SM, Sica G, Brat DJ, Shi H, ... ... Michailidis G, et al. Metabolomic profiling reveals potential markers and bioprocesses altered in bladder cancer progression. Cancer Research. 71: 7376-86. PMID 21990318 DOI: 10.1158/0008-5472.Can-11-1154 |
0.56 |
|
| 2011 |
Putluri N, Shojaie A, Vasu VT, Nalluri S, Vareed SK, Putluri V, Vivekanandan-Giri A, Byun J, Pennathur S, Sana TR, Fischer SM, Palapattu GS, Creighton CJ, Michailidis G, Sreekumar A. Metabolomic profiling reveals a role for androgen in activating amino acid metabolism and methylation in prostate cancer cells. Plos One. 6: e21417. PMID 21789170 DOI: 10.1371/Journal.Pone.0021417 |
0.56 |
|
| 2011 |
Tang R, Banerjee M, Michailidis G. A two-stage hybrid procedure for estimating an inverse regression function The Annals of Statistics. 39: 956-989. DOI: 10.1214/10-Aos820 |
0.458 |
|
| 2011 |
Culp M, Michailidis G, Johnson K. On adaptive regularization methods in boosting Journal of Computational and Graphical Statistics. 20: 937-955. DOI: 10.1198/Jcgs.2010.09076 |
0.749 |
|
| 2011 |
Singhal H, Michailidis G. Structural models for dual modality data with application to network tomography Ieee Transactions On Information Theory. 57: 5054-5071. DOI: 10.1109/Tit.2011.2158474 |
0.661 |
|
| 2011 |
Stoev SA, Michailidis G, Taqqu MS. Estimating heavy-tail exponents through max self-similarity Ieee Transactions On Information Theory. 57: 1615-1636. DOI: 10.1109/Tit.2010.2103751 |
0.385 |
|
| 2010 |
Guo J, James G, Levina E, Michailidis G, Zhu J. Principal Component Analysis With Sparse Fused Loadings. Journal of Computational and Graphical Statistics : a Joint Publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America. 19: 930-946. PMID 25878487 DOI: 10.1198/Jcgs.2010.08127 |
0.312 |
|
| 2010 |
Shojaie A, Michailidis G. Penalized likelihood methods for estimation of sparse high-dimensional directed acyclic graphs. Biometrika. 97: 519-538. PMID 22434937 DOI: 10.1093/Biomet/Asq038 |
0.627 |
|
| 2010 |
Shojaie A, Michailidis G. Discovering graphical Granger causality using the truncating lasso penalty. Bioinformatics (Oxford, England). 26: i517-23. PMID 20823316 DOI: 10.1093/Bioinformatics/Btq377 |
0.645 |
|
| 2010 |
Shojaie A, Michailidis G. Network enrichment analysis in complex experiments. Statistical Applications in Genetics and Molecular Biology. 9: Article22. PMID 20597848 DOI: 10.2202/1544-6115.1483 |
0.653 |
|
| 2010 |
Culp M, Johnson K, Michailidis G. The ensemble bridge algorithm: a new modeling tool for drug discovery problems. Journal of Chemical Information and Modeling. 50: 309-16. PMID 20121044 DOI: 10.1021/Ci9003392 |
0.709 |
|
| 2010 |
Putluri N, Vasu VT, Shojaie A, Thangjam GS, Vareed SK, Putluri V, Butler C, Giri JG, Park MA, Ponnala R, Sana TR, Fischer SM, Sica G, Brat DJ, Shi H, ... ... Michailidis G, et al. Abstract A52: Metabolomic profiling reveals impaired xenobiotic metabolism in bladder cancer Cancer Epidemiology, Biomarkers & Prevention. 19. DOI: 10.1158/1055-9965.Disp-10-A52 |
0.575 |
|
| 2010 |
Stoev SA, Michailidis G. On the estimation of the heavy-tail exponent in time series using the max-spectrum Applied Stochastic Models in Business and Industry. 26: 224-253. DOI: 10.1002/Asmb.V26:3 |
0.391 |
|
| 2010 |
Shojaie A, Michailidis G. Penalized principal component regression on graphs for analysis of subnetworks Advances in Neural Information Processing Systems 23: 24th Annual Conference On Neural Information Processing Systems 2010, Nips 2010. |
0.606 |
|
| 2009 |
Shojaie A, Michailidis G. Analysis of gene sets based on the underlying regulatory network. Journal of Computational Biology : a Journal of Computational Molecular Cell Biology. 16: 407-26. PMID 19254181 DOI: 10.1089/Cmb.2008.0081 |
0.623 |
|
| 2009 |
Lan Y, Banerjee M, Michailidis G. Change-point estimation under adaptive sampling Annals of Statistics. 37: 1752-1791. DOI: 10.1214/08-Aos602 |
0.505 |
|
| 2009 |
Culp M, Michailidis G, Johnson K. On multi-view learning with additive models Annals of Applied Statistics. 3: 292-318. DOI: 10.1214/08-Aoas202 |
0.715 |
|
| 2009 |
Hamidieh K, Stoev S, Michailidis G. On the estimation of the extremal index based on scaling and resampling Journal of Computational and Graphical Statistics. 49: 731-755. DOI: 10.1198/Jcgs.2009.08065 |
0.757 |
|
| 2009 |
Culp M, Michailidis G. A co-training algorithm for multi-view data with applications in data fusion Journal of Chemometrics. 23: 294-303. DOI: 10.1002/Cem.1233 |
0.728 |
|
| 2008 |
Culp M, Michailidis G. Graph-based semisupervised learning. Ieee Transactions On Pattern Analysis and Machine Intelligence. 30: 174-9. PMID 18000333 DOI: 10.1109/Tpami.2007.70765 |
0.722 |
|
| 2008 |
Culp M, Michailidis G. An iterative algorithm for extending learners to a semi-supervised setting Journal of Computational and Graphical Statistics. 17: 545-571. DOI: 10.1198/106186008X344748 |
0.703 |
|
| 2008 |
Ranjan P, Bingham D, Michailidis G. Sequential experiment design for contour estimation from complex computer codes Technometrics. 50: 527-541. DOI: 10.1198/004017008000000541 |
0.36 |
|
| 2008 |
Katenka N, Levina E, Michailidis G. Robust target localization from binary decisions in wireless sensor networks Technometrics. 50: 448-461. DOI: 10.1198/004017008000000424 |
0.749 |
|
| 2008 |
Singhal H, Michailidis G. Optimal sampling in state space models with applications to network monitoring Sigmetrics'08: Proceedings of the 2008 Acm Sigmetrics International Conference On Measurement and Modeling of Computer Systems. 36: 145-156. DOI: 10.1145/1375457.1375474 |
0.621 |
|
| 2008 |
Hung YC, Michailidis G. Modeling, scheduling, and simulation of switched processing systems Acm Transactions On Modeling and Computer Simulation. 18. DOI: 10.1145/1371574.1371578 |
0.555 |
|
| 2008 |
Katenka N, Levina E, Michailidis G. Local vote decision fusion for target detection in wireless sensor networks Ieee Transactions On Signal Processing. 56: 329-338. DOI: 10.1109/Tsp.2007.900165 |
0.738 |
|
| 2007 |
Hung YC, Michailidis G. A measurement based dynamic policy for switched processing systems Ieee International Conference On Communications. 301-306. DOI: 10.1109/ICC.2007.57 |
0.543 |
|
| 2007 |
Singhal H, Michailidis G. Identifiability of flow distributions from link measurements with applications to computer networks Inverse Problems. 23: 1821-1849. DOI: 10.1088/0266-5611/23/5/004 |
0.634 |
|
| 2006 |
Lawrence E, Michailidis G, Nair VN. Network delay tomography using flexicast experiments Journal of the Royal Statistical Society. Series B: Statistical Methodology. 68: 785-813. DOI: 10.1111/J.1467-9868.2006.00567.X |
0.411 |
|
| 2006 |
Hung YC, Michailidis G. Improving quality of service for switched processing systems 2006 11th International Workshop On Computer-Aided Modeling, Analysis and Design of Communication Links and Networks. 2006: 46-53. DOI: 10.1109/CAMAD.2006.1649717 |
0.488 |
|
| 2006 |
Stoev S, Taqqu MS, Park C, Michailidis G, Marron JS. LASS: A tool for the local analysis of self-similarity Computational Statistics and Data Analysis. 50: 2447-2471. DOI: 10.1016/J.Csda.2004.12.014 |
0.346 |
|
| 2006 |
Xu P, Michailidis G, Devetsikiotis M. Profit-oriented resource allocation using online scheduling in flexible heterogeneous networks Telecommunication Systems. 31: 289-303. DOI: 10.1007/S11235-006-6525-7 |
0.351 |
|
| 2005 |
Michailidis G, De Leeuw J. Homogeneity analysis using absolute deviations Computational Statistics and Data Analysis. 48: 587-603. DOI: 10.1016/J.Csda.2004.03.007 |
0.333 |
|
| 2005 |
Rolls DA, Michailidis G, Hernández-Campos F. Queueing analysis of network traffic: Methodology and visualization tools Computer Networks. 48: 447-473. DOI: 10.1016/J.Comnet.2004.11.016 |
0.338 |
|
| 2005 |
Bambos N, Michailidis G. Queueing networks of random link topology: Stationary dynamics of maximal throughput schedules Queueing Systems. 50: 5-52. DOI: 10.1007/S11134-005-0858-X |
0.333 |
|
| 2004 |
Bambos N, Michailidis G. Queueing and scheduling in random environments Advances in Applied Probability. 36: 293-317. DOI: 10.1239/Aap/1077134474 |
0.314 |
|
| 2003 |
Michailidis G, Shedden K. The application of rule-based methods to class prediction problems in genomics. Journal of Computational Biology : a Journal of Computational Molecular Cell Biology. 10: 689-98. PMID 14633393 DOI: 10.1089/106652703322539033 |
0.336 |
|
| 1998 |
Michailidis G, De Leeuw J. The Gifi System of Descriptive Multivariate Analysis Statistical Science. 13: 307-336. DOI: 10.1214/Ss/1028905828 |
0.308 |
|
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