Gene Expression Elucidates Functional Impact of Polygenic Risk for Schizophrenia M Fromer, P Roussos, SK Sieberts, JS Johnson, DH Kavanagh, ... bioRxiv 52209 (052209), 052209, 2016 | 1131 | 2016 |
Unsupervised analysis of transcriptomics in bacterial sepsis across multiple datasets reveals three robust clusters TE Sweeney, TD Azad, M Donato, WA Haynes, TM Perumal, R Henao, ... Critical care medicine 46 (6), 915-925, 2018 | 279 | 2018 |
Integrating pathways of Parkinson's disease in a molecular interaction map KA Fujita, M Ostaszewski, Y Matsuoka, S Ghosh, E Glaab, C Trefois, ... Molecular neurobiology 49, 88-102, 2014 | 279 | 2014 |
Meta-analysis of the Alzheimer’s disease human brain transcriptome and functional dissection in mouse models YW Wan, R Al-Ouran, CG Mangleburg, TM Perumal, TV Lee, K Allison, ... Cell reports 32 (2), 2020 | 238 | 2020 |
A community approach to mortality prediction in sepsis via gene expression analysis TE Sweeney, TM Perumal, R Henao, M Nichols, JA Howrylak, AM Choi, ... Nature communications 9 (1), 694, 2018 | 203 | 2018 |
Landscape of conditional eQTL in dorsolateral prefrontal cortex and co-localization with schizophrenia GWAS A Dobbyn, LM Huckins, J Boocock, LG Sloofman, BS Glicksberg, ... The American Journal of Human Genetics 102 (6), 1169-1184, 2018 | 150 | 2018 |
Remote smartphone monitoring of Parkinson’s disease and individual response to therapy L Omberg, E Chaibub Neto, TM Perumal, A Pratap, A Tediarjo, J Adams, ... Nature Biotechnology 40 (4), 480-487, 2022 | 115 | 2022 |
Large-scale identification of common trait and disease variants affecting gene expression ME Hauberg, W Zhang, C Giambartolomei, O Franzén, DL Morris, TJ Vyse, ... The American Journal of Human Genetics 100 (6), 885-894, 2017 | 109 | 2017 |
Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions SK Sieberts, TM Perumal, MM Carrasquillo, M Allen, JS Reddy, ... Scientific data 7 (1), 340, 2020 | 94 | 2020 |
Gene Regulatory Network Inference of Immunoresponsive Gene 1 (IRG1) Identifies Interferon Regulatory Factor 1 (IRF1) as Its Transcriptional Regulator in Mammalian Macrophages. MA Tallam A, Perumal TM, Antony PM, Jäger C, Fritz JV, Vallar L, Balling R ... PLoS One 11 (2), e0149050, 2016 | 92 | 2016 |
Detecting the impact of subject characteristics on machine learning-based diagnostic applications E Chaibub Neto, A Pratap, TM Perumal, M Tummalacherla, P Snyder, ... NPJ digital medicine 2 (1), 99, 2019 | 71 | 2019 |
Molecular, phenotypic, and sample-associated data to describe pluripotent stem cell lines and derivatives K Daily, SJ Ho Sui, LM Schriml, PJ Dexheimer, N Salomonis, R Schroll, ... Scientific data 4 (1), 1-10, 2017 | 67 | 2017 |
Identifying drug targets for neurological and psychiatric disease via genetics and the brain transcriptome DA Baird, JZ Liu, J Zheng, SK Sieberts, T Perumal, B Elsworth, ... PLoS genetics 17 (1), e1009224, 2021 | 61 | 2021 |
Detecting cellular reprogramming determinants by differential stability analysis of gene regulatory networks I Crespo, TM Perumal, W Jurkowski, A Del Sol BMC systems biology 7, 1-14, 2013 | 59 | 2013 |
A novel systems biology approach to evaluate mouse models of late-onset Alzheimer’s disease C Preuss, R Pandey, E Piazza, A Fine, A Uyar, T Perumal, D Garceau, ... Molecular neurodegeneration 15, 1-16, 2020 | 54 | 2020 |
Crowdsourcing digital health measures to predict Parkinson’s disease severity: the Parkinson’s Disease Digital Biomarker DREAM Challenge SK Sieberts, J Schaff, M Duda, BÁ Pataki, M Sun, P Snyder, JF Daneault, ... NPJ digital medicine 4 (1), 53, 2021 | 49 | 2021 |
Understanding dynamics using sensitivity analysis: caveat and solution TM Perumal, R Gunawan BMC systems biology 5, 1-10, 2011 | 45 | 2011 |
Meta-analysis of the human brain transcriptome identifies heterogeneity across human AD coexpression modules robust to sample collection and methodological approach BA Logsdon, TM Perumal, V Swarup, M Wang, C Funk, C Gaiteri, M Allen, ... BioRxiv, 510420, 2019 | 43 | 2019 |
Personalized hypothesis tests for detecting medication response in Parkinson disease patients using iPhone Sensor data E CHAIBUB NETO, BM Bot, T PERUMAL, L Omberg, J Guinney, M Kellen, ... Biocomputing 2016: Proceedings of the Pacific Symposium, 273-284, 2016 | 37 | 2016 |
A Permutation Approach to Assess Confounding in Machine Learning Applications for Digital Health E Chaibub Neto, A Pratap, TM Perumal, M Tummalacherla, BM Bot, ... Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 21 | 2019 |