Sara Hägg
Molecular Biology · 2013–2021
A researcher in the Science corpus: 6 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 77 citations into it
- Physiology — 26 citations into it
- Pediatrics, Perinatology and Child Health — 21 citations into it
- Aging — 9 citations into it
Whom Sara Hägg trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from Sara Hägg's perspective
Ordered by how strongly the researchers Sara Hägg trusts endorse each paper. Same corpus, a different order for every researcher.
- Modeling the rate of senescence: can estimated biological age predict mortality more accurately than chronological age? (The journals of gerontology. Series A, Biological sciences and medical sciences)
- DNA methylation age of human tissues and cell types (Genome Biology)
- A data-driven approach to preprocessing Illumina 450K methylation array data (BMC Genomics)
- Quantification of biological aging in young adults (Proceedings of the National Academy of Sciences of the United States of America)
- DNA methylation-based biomarkers and the epigenetic clock theory of ageing (Nature reviews genetics)
- An epigenetic clock analysis of race/ethnicity, sex, and coronary heart disease (Genome Biology)
- Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays (Bioinform.)
- Epigenetic clock analysis of diet, exercise, education, and lifestyle factors (Aging)
- A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research.
- Repeated Measures Correlation (Frontiers in Psychology)
Their papers
- A computational solution for bolstering reliability of epigenetic clocks: Implications for clinical trials and longitudinal tracking (2021) — 370 citations
- Genome-wide meta-analysis identifies new loci and functional pathways influencing Alzheimer’s disease risk (2019) — 2,006 citations
- Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function (2018) — 630 citations
- Biological Age Predictors (2017) — 1,030 citations
- GWAS of 126,559 Individuals Identifies Genetic Variants Associated with Educational Attainment (2013) — 874 citations
- Identification of seven loci affecting mean telomere length and their association with disease (2013) — 909 citations