| A closer look at cross-validation for assessing the accuracy of gene regulatory networks and models S Tabe-Bordbar, A Emad, SD Zhao, S Sinha Scientific reports 8 (1), 6620, 2018 | 60 | 2018 |
| Semiquantitative group testing A Emad, O Milenkovic IEEE Transactions on Information Theory 60 (8), 4614-4636, 2014 | 47 | 2014 |
| Learning interpretable classification rules with boolean compressed sensing DM Malioutov, KR Varshney, A Emad, S Dash Transparent Data Mining for Big and Small Data, 95-121, 2017 | 46 | 2017 |
| Knowledge-guided analysis of" omics" data using the KnowEnG cloud platform C Blatti III, A Emad, MJ Berry, L Gatzke, M Epstein, D Lanier, P Rizal, J Ge, ... PLoS biology 18 (1), e3000583, 2020 | 38 | 2020 |
| Tissue-guided LASSO for prediction of clinical drug response using preclinical samples EW Huang, A Bhope, J Lim, S Sinha, A Emad PLoS computational biology 16 (1), e1007607, 2020 | 37 | 2020 |
| A new correlation clustering method for cancer mutation analysis JP Hou, A Emad, GJ Puleo, J Ma, O Milenkovic Bioinformatics 32 (24), 3717-3728, 2016 | 36 | 2016 |
| Knowledge-guided gene prioritization reveals new insights into the mechanisms of chemoresistance A Emad, J Cairns, KR Kalari, L Wang, S Sinha Genome biology 18, 1-21, 2017 | 34 | 2017 |
| Poisson group testing: A probabilistic model for nonadaptive streaming boolean compressed sensing A Emad, O Milenkovic 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014 | 31 | 2014 |
| Superior breast cancer metastasis risk stratification using an epithelial-mesenchymal-amoeboid transition gene signature A Emad, T Ray, TW Jensen, M Parat, R Natrajan, S Sinha, PS Ray Breast Cancer Research 22, 1-13, 2020 | 25 | 2020 |
| CaSPIAN: a causal compressive sensing algorithm for discovering directed interactions in gene networks A Emad, O Milenkovic PloS one 9 (3), e90781, 2014 | 25 | 2014 |
| A network-informed analysis of SARS-CoV-2 and hemophagocytic lymphohistiocytosis genes’ interactions points to Neutrophil extracellular traps as mediators of thrombosis in COVID-19 J Ding, DE Hostallero, MR El Khili, GJ Fonseca, S Milette, N Noorah, ... PLoS Computational Biology 17 (3), e1008810, 2021 | 24 | 2021 |
| RAPPPID: towards generalizable protein interaction prediction with AWD-LSTM twin networks J Szymborski, A Emad Bioinformatics 38 (16), 3958-3967, 2022 | 19 | 2022 |
| MARSY: a multitask deep-learning framework for prediction of drug combination synergy scores MR El Khili, SA Memon, A Emad Bioinformatics 39 (4), btad177, 2023 | 17 | 2023 |
| Looking at the BiG picture: incorporating bipartite graphs in drug response prediction DE Hostallero, Y Li, A Emad Bioinformatics 38 (14), 3609-3620, 2022 | 16 | 2022 |
| A semiquantitative group testing approach for learning interpretable clinical prediction rules A Emad, KR Varshney, DM Malioutov Proc. Signal Process. Adapt. Sparse Struct. Repr. Workshop, Cambridge, UK, 2015 | 15 | 2015 |
| Inference of phenotype-relevant transcriptional regulatory networks elucidates cancer type-specific regulatory mechanisms in a pan-cancer study A Emad, S Sinha NPJ systems biology and applications 7 (1), 9, 2021 | 12 | 2021 |
| Symmetric group testing and superimposed codes A Emad, J Shen, O Milenkovic 2011 IEEE Information Theory Workshop, 20-24, 2011 | 10 | 2011 |
| Interpretable deep learning architectures for improving drug response prediction performance: myth or reality? Y Li, DE Hostallero, A Emad biorxiv, 2022.10. 03.510614, 2022 | 9 | 2022 |
| Code construction and decoding algorithms for semi-quantitative group testing with nonuniform thresholds A Emad, O Milenkovic IEEE Transactions on Information Theory 62 (4), 1674-1687, 2016 | 8 | 2016 |
| Poisson group testing: A probabilistic model for Boolean compressed sensing A Emad, O Milenkovic IEEE Transactions on Signal Processing 63 (16), 4396-4410, 2015 | 8 | 2015 |
Olgica MilenkovicUniversity of IllinoisVerified email at illinois.edu
