ReviewCurrent cardiology reports2021
Taking Data Science to Heart: Next Scale of Gene Regulation.
Review in Current cardiology reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Single-Cell Transcriptomics of Human Acute Myocardial Infarction Reveals Oxidative Stress-Associated Cardiomyocyte Subpopulations and Candidate Predictive Signatures.Antioxidants (Basel, Switzerland) · 2025Article
- genomeSidekick: A user-friendly epigenomics data analysis tool.Frontiers in bioinformatics · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
purpose of reviewTechnical advances have facilitated high-throughput measurements of the genome in the context of cardiovascular biology. These techniques bring a deluge of gargantuan datasets, which in turn present two fundamentally new opportunities for innovation-data processing and knowledge integration-toward the goal of meaningful basic and translational discoveries. RECENT
findingsBig data, integrative analyses, and machine learning have brought cardiac investigations to the cutting edge of chromatin biology, not only to reveal basic principles of gene regulation in the heart, but also to aid in the design of targeted epigenetic therapies. SUMMARY: Cardiac studies using big data are only beginning to integrate the millions of recorded data points and the tools of machine learning are aiding this process. Future experimental design should take into consideration insights from existing genomic datasets, thereby focusing on heretofore unexplored epigenomic contributions to disease pathology.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.