Ng, Bernard
Rush University Medical Center
8 papers on CoChatORCID 0000-0002-8688-3873
Most cited papers
- Verified
Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression
eQTLGen, Wray, N. R., 23andMe, the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Ripke, S., Mattheisen, M., Trzaskowski, M., Byrne, E. M., Abdellaoui, A., Adams, M. J., et al. (2018) · Nature Genetics
Genetic Associations and EpidemiologyTreatment of Major Depression
Cited by 3,005
- Verified
An xQTL map integrates the genetic architecture of the human brain's transcriptome and epigenome
Ng, B., White, C. C., Klein, H.-U., Sieberts, S. K., McCabe, C., Patrick, E., Xu, J., Yu, L., Gaiteri, C., Bennett, D. A., et al. (2017) · Nature Neuroscience
Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals
Cited by 452
- Verified
Integrative transcriptome analyses of the aging brain implicate altered splicing in Alzheimer’s disease susceptibility
Raj, T., Li, Y. I., Wong, G., Humphrey, J., Wang, M., Ramdhani, S., Wang, Y.-C., Ng, B., Gupta, I., Haroutunian, V., et al. (2018) · Nature Genetics
RNA Research and SplicingAlzheimer's disease research and treatments
Cited by 410
- Verified
Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors
Mullins, N., Kang, J., Campos, A. I., Coleman, J. R. I., Edwards, A. C., Galfalvy, H., Levey, D. F., Lori, A., Shabalin, A., Starnawska, A., et al. (2022) · Biological Psychiatry
Suicide and Self-Harm StudiesGenetic Associations and Epidemiology
Cited by 238
- Verified
Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns
Czamara, D., Eraslan, G., Page, C. M., Lahti, J., Lahti-Pulkkinen, M., Hämäläinen, E., Kajantie, E., Laivuori, H., Villa, P. M., Reynolds, R. M., et al. (2019) · Nature Communications
Epigenetics and DNA MethylationBirth, Development, and Health
Cited by 143
- Verified
Benchmarking of deep neural networks for predicting personal gene expression from DNA sequence highlights shortcomings
Sasse, A., Ng, B., Spiro, A. E., Tasaki, S., Bennett, D. A., Gaiteri, C., De Jager, P. L., Chikina, M., & Mostafavi, S. (2023) · Nature Genetics
Genetic Associations and EpidemiologyGenomics and Chromatin Dynamics
Cited by 139
- Verified
Cell-subtype specific effects of genetic variation in the aging and Alzheimer cortex
Fujita, M., Gao, Z., Zeng, L., McCabe, C., White, C. C., Ng, B., Green, G. S., Rozenblatt-Rosen, O., Phillips, D., Amir-Zilberstein, L., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory)
Genetic Associations and EpidemiologySingle-cell and spatial transcriptomics
Cited by 36
- Verified
Uncovering Plaque-Glia Niches in Human Alzheimer’s Disease Brains Using Spatial Transcriptomics
Avey, D. R., Ng, B., Vialle, R. A., Kearns, N. A., de Paiva Lopes, K., Iatrou, A., De Tissera, S., Vyas, H., Saunders, D. M., Flood, D. J., et al. (2024) · Molecular Neurodegeneration Advances
Alzheimer's disease research and treatmentsNeuroinflammation and Neurodegeneration Mechanisms
Cited by 24
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