Evidence map›Paper›PMID 29529131›Full record

ReviewBriefings in functional genomics2018

ChIP-ping the branches of the tree: functional genomics and the evolution of eukaryotic gene regulation.

Georgi K Marinov, Anshul Kundaje

Abstract readReview
In one paragraph

Review in Briefings in functional genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Georgi K Marinov
Anshul Kundaje

Funding

High-throughput systematic characterization of regulatory element functionUM1HG009436 · NHGRI · STANFORD UNIVERSITY · PI BASSIK, MICHAEL C, GREENLEAF, WILLIAM JAMES · 2017 to 2021
$5.4M
Decoding the regulatory architecture of the human genome across cell types, individuals and diseaseU01HG009431 · NHGRI · STANFORD UNIVERSITY · PI PRITCHARD, JONATHAN K · 2017 to 2021
$3.5M
Deep learning frameworks for regulatory genomics.DP2GM123485 · NIGMS · STANFORD UNIVERSITY · PI KUNDAJE, ANSHUL · 2016 to 2016
$2.4M
NHGRI NIH HHS U01 HG009431NHGRI NIH HHS UM1 HG009436
6 · The paper itself

Abstract

Advances in the methods for detecting protein-DNA interactions have played a key role in determining the directions of research into the mechanisms of transcriptional regulation. The most recent major technological transformation happened a decade ago, with the move from using tiling arrays [chromatin immunoprecipitation (ChIP)-on-Chip] to high-throughput sequencing (ChIP-seq) as a readout for ChIP assays. In addition to the numerous other ways in which it is superior to arrays, by eliminating the need to design and manufacture them, sequencing also opened the door to carrying out comparative analyses of genome-wide transcription factor occupancy across species and studying chromatin biology in previously less accessible model and nonmodel organisms, thus allowing us to understand the evolution and diversity of regulatory mechanisms in unprecedented detail. Here, we review the biological insights obtained from such studies in recent years and discuss anticipated future developments in the field.

Indexed as

Evolution, MolecularGene Expression RegulationAnimalsChromatin ImmunoprecipitationGene Regulatory NetworksGenomicsHumansTranscription FactorsTranscription Factors

Identifiers

PMID29529131
PMCPMC5889016

What OpenQuestion holds

Textmetadata
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.