Evidence map›Paper›PMID 37503240›Full record

ArticlebioRxiv : the preprint server for biology2023

Integrative epigenomic and functional characterization assay based annotation of regulatory activity across diverse human cell types.

Tevfik Umut Dincer, Jason Ernst

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Tevfik Umut DincerBioinformatics Interdepartmental Program, University of California, Los Angeles, CA, 90095, USA.
Jason ErnstBioinformatics Interdepartmental Program, University of California, Los Angeles, CA, 90095, USA.

Funding

1/2 Genomic Strategies to Identify High-impact Psychiatric Risk VariantsU01MH105578 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI FREIMER, NELSON B., GESCHWIND, DANIEL H · 2014 to 2018
$8.5M
Leveraging genetic variation to dissect gene regulatory networks of reprogramming to pluripotencyU01HG012079 · NHGRI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Chongyuan Luo, Kathrin Plath · 2021 to 2026
$6.9M
Spatiotemporal epigenomic and chromosomal architectural cell atlas of developing human brainsU01MH130995 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Chongyuan Luo, Mercedes Paredes · 2022 to 2026
$4.4M
Impact of coding and non-coding variation in progressive supranuclear palsyUH3NS104095 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI DICKSON, DENNIS WILLIAM, GESCHWIND, DANIEL H · 2020 to 2021
$2.5M
Deciphering the Relationship between Substance Use and Psychiatric Disorders from Whole Genome Sequencing DataDP1DA044371 · NIDA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ERNST, JASON · 2017 to 2021
$2.3M
NHGRI NIH HHS U01 HG012079NIDA NIH HHS DP1 DA044371NIMH NIH HHS U01 MH105578NIMH NIH HHS U01 MH130995NINDS NIH HHS UH3 NS104095
6 · The paper itself

Abstract

We introduce ChromActivity, a computational framework for predicting and annotating regulatory activity across the genome through integration of multiple epigenomic maps and various functional characterization datasets. ChromActivity generates genomewide predictions of regulatory activity associated with each functional characterization dataset across many cell types based on available epigenomic data. It then for each cell type produces (1) ChromScoreHMM genome annotations based on the combinatorial and spatial patterns within these predictions and (2) ChromScore tracks of overall predicted regulatory activity. ChromActivity provides a resource for analyzing and interpreting the human regulatory genome across diverse cell types.

Indexed as

CRISPR screensepigenomegene regulationgenome annotationhidden markov modelmachine learningmassively parallel reporter assays

Identifiers

PMID37503240
PMCPMC10369970

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 OpenQuestion graph.