Juan Ramón Tejedor (ORCID 0000-0002-4061-9698) has 107 indexed works with ~1,203 citations and an h-index of 20, with productivity accelerating sharply — 30 works in 2023 and 9 in 2026 alone. His topic profile is tightly focused on DNA methylation (score 0.89) and gene regulation. His most-cited outputs come from productive collaborations: two 2014 Molecular Cell papers on splicing regulation (~96–175 citations each) during his time with Juan Valcárcel at Universitat Pompeu Fabra , followed by sustained methylation-aging work with Fraga and Fernández at Universidad de Oviedo, including a well-cited Aging Cell paper distinguishing hypomethylation signatures of aging versus cancer and longitudinal early-life methylome work .
His 2026 preprints are scientifically ambitious and methodologically current. The entropy study reanalyzed 1,531 healthy 450K profiles across 14 tissues with careful cell-composition adjustment (EpiDISH/EpiScore) and LMG variance partitioning, reporting that cumulative stem-cell divisions (epiTOC2 TNSC, r = 0.7562) dwarf chronological age (r = 0.1443) as correlates of adjusted methylation entropy — ~90% of explained variance pan-tissue — with the brain a biologically coherent exception (TNSC 45.3% vs age 29.8%) . The companion repeat-epigenomics study integrates 766 ChIP-seq experiments and 171 hematological malignancies to define five repeat-element chromatin epitypes, including a novel dual-heterochromatin state (H3K36me3 + H3K9me3), and links repeat remodeling to aging and B-cell transformation . These are correlational, largely public-data reanalyses (bulk 450K arrays, mitotic history inferred rather than measured, no single-cell validation, hematopoietic-only scope in the repeat study), but the statistical pipelines are transparent, software versions reported, and limitations candidly disclosed — hallmarks of good epistemic practice.
Interpretation: citation flow is respectable but concentrated in mid-author roles within established groups (Fraga, Fernández, Valcárcel); there is no evidence yet of an independent flagship lab or paradigm-defining first-author high-impact series. The ~90% variance-partitioning figure should be read cautiously — LMG on correlated predictors in cross-sectional public data can inflate attribution, and the authors themselves note the possible shared PRC2-substrate confounder . Overall: a rigorously trained, productive epigenomics scientist at the transition to independent leadership; what would change this assessment is independent functional validation of the entropy and repeat-epitype claims in prospective, single-cell, or interventional designs.
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