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Connection

Hae Kyung Im to Transcriptome

This is a "connection" page, showing publications Hae Kyung Im has written about Transcriptome.
Connection Strength

4.964
  1. scPrediXcan integrates deep learning methods and single-cell data into a cell-type-specific transcriptome-wide association study framework. Cell Genom. 2025 May 14; 5(5):100875.
    View in: PubMed
    Score: 0.604
  2. RatXcan: A framework for cross-species integration of genome-wide association and gene expression data. PLoS Genet. 2025 Mar; 21(3):e1011583.
    View in: PubMed
    Score: 0.599
  3. A multi-tissue, splicing-based joint transcriptome-wide association study identifies susceptibility genes for breast cancer. Am J Hum Genet. 2024 06 06; 111(6):1100-1113.
    View in: PubMed
    Score: 0.563
  4. Polygenic transcriptome risk scores (PTRS) can improve portability of polygenic risk scores across ancestries. Genome Biol. 2022 01 13; 23(1):23.
    View in: PubMed
    Score: 0.479
  5. Integrating predicted transcriptome from multiple tissues improves association detection. PLoS Genet. 2019 01; 15(1):e1007889.
    View in: PubMed
    Score: 0.390
  6. Meet the author: Hae Kyung Im. Cell Genom. 2025 May 14; 5(5):100880.
    View in: PubMed
    Score: 0.151
  7. Multi-INTACT: integrative analysis of the genome, transcriptome, and proteome identifies causal mechanisms of complex traits. Genome Biol. 2025 Feb 03; 26(1):19.
    View in: PubMed
    Score: 0.148
  8. Transcriptome-wide association study of the plasma proteome reveals cis and trans regulatory mechanisms underlying complex traits. Am J Hum Genet. 2024 03 07; 111(3):445-455.
    View in: PubMed
    Score: 0.138
  9. Multivariate adaptive shrinkage improves cross-population transcriptome prediction and association studies in underrepresented populations. HGG Adv. 2023 10 12; 4(4):100216.
    View in: PubMed
    Score: 0.133
  10. A joint transcriptome-wide association study across multiple tissues identifies candidate breast cancer susceptibility genes. Am J Hum Genet. 2023 06 01; 110(6):950-962.
    View in: PubMed
    Score: 0.131
  11. Probabilistic integration of transcriptome-wide association studies and colocalization analysis identifies key molecular pathways of complex traits. Am J Hum Genet. 2023 01 05; 110(1):44-57.
    View in: PubMed
    Score: 0.128
  12. Polygenic transcriptome risk scores for COPD and lung function improve cross-ethnic portability of prediction in the NHLBI TOPMed program. Am J Hum Genet. 2022 05 05; 109(5):857-870.
    View in: PubMed
    Score: 0.122
  13. Population-scale tissue transcriptomics maps long non-coding RNAs to complex disease. Cell. 2021 05 13; 184(10):2633-2648.e19.
    View in: PubMed
    Score: 0.114
  14. Cell type-specific genetic regulation of gene expression across human tissues. Science. 2020 09 11; 369(6509).
    View in: PubMed
    Score: 0.109
  15. Transcriptomic signatures across human tissues identify functional rare genetic variation. Science. 2020 09 11; 369(6509).
    View in: PubMed
    Score: 0.109
  16. CORE GREML for estimating covariance between random effects in linear mixed models for complex trait analyses. Nat Commun. 2020 08 21; 11(1):4208.
    View in: PubMed
    Score: 0.109
  17. Genetic regulatory variation in populations informs transcriptome analysis in rare disease. Science. 2019 10 18; 366(6463):351-356.
    View in: PubMed
    Score: 0.102
  18. Shared and distinct genetic risk factors for childhood-onset and adult-onset asthma: genome-wide and transcriptome-wide studies. Lancet Respir Med. 2019 06; 7(6):509-522.
    View in: PubMed
    Score: 0.099
  19. Imputed gene associations identify replicable trans-acting genes enriched in transcription pathways and complex traits. Genet Epidemiol. 2019 09; 43(6):596-608.
    View in: PubMed
    Score: 0.099
  20. Opportunities and challenges for transcriptome-wide association studies. Nat Genet. 2019 04; 51(4):592-599.
    View in: PubMed
    Score: 0.099
  21. A Transcriptome-Wide Association Study Among 97,898 Women to Identify Candidate Susceptibility Genes for Epithelial Ovarian Cancer Risk. Cancer Res. 2018 09 15; 78(18):5419-5430.
    View in: PubMed
    Score: 0.094
  22. Imputing Gene Expression in Uncollected Tissues Within and Beyond GTEx. Am J Hum Genet. 2016 Apr 07; 98(4):697-708.
    View in: PubMed
    Score: 0.080
  23. Integrative analyses of genetic variation, epigenetic regulation, and the transcriptome to elucidate the biology of platinum sensitivity. BMC Genomics. 2014 Apr 16; 15:292.
    View in: PubMed
    Score: 0.070
  24. Genetic architecture of microRNA expression: implications for the transcriptome and complex traits. Am J Hum Genet. 2012 Jun 08; 90(6):1046-63.
    View in: PubMed
    Score: 0.062
  25. On sharing quantitative trait GWAS results in an era of multiple-omics data and the limits of genomic privacy. Am J Hum Genet. 2012 Apr 06; 90(4):591-8.
    View in: PubMed
    Score: 0.061
  26. The Farm Animal Genotype-Tissue Expression (FarmGTEx) Project. Nat Genet. 2025 Apr; 57(4):786-796.
    View in: PubMed
    Score: 0.037
  27. Exploiting the GTEx resources to decipher the mechanisms at GWAS loci. Genome Biol. 2021 01 26; 22(1):49.
    View in: PubMed
    Score: 0.028
  28. Functionally oriented analysis of cardiometabolic traits in a trans-ethnic sample. Hum Mol Genet. 2019 04 01; 28(7):1212-1224.
    View in: PubMed
    Score: 0.025
  29. Gene expression imputation across multiple brain regions provides insights into schizophrenia risk. Nat Genet. 2019 04; 51(4):659-674.
    View in: PubMed
    Score: 0.025
  30. Genetic architecture of gene expression traits across diverse populations. PLoS Genet. 2018 08; 14(8):e1007586.
    View in: PubMed
    Score: 0.024
  31. Protein quantitative trait loci identify novel candidates modulating cellular response to chemotherapy. PLoS Genet. 2014 Apr; 10(4):e1004192.
    View in: PubMed
    Score: 0.017
  32. Population differences in microRNA expression and biological implications. RNA Biol. 2011 Jul-Aug; 8(4):692-701.
    View in: PubMed
    Score: 0.014
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.