Evidence map›Paper›PMID 24515121›Full record

ArticleGenome research2014

ISMARA: automated modeling of genomic signals as a democracy of regulatory motifs.

Piotr J Balwierz, Mikhail Pachkov, Phil Arnold, Andreas J Gruber, Mihaela Zavolan, Erik van Nimwegen

Open access · bronzeAbstract read
In one paragraph

Article in Genome research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 194 papers.

0numbers the graph read from it
0cells of the map it votes in
194citing 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

194 citing papers in PubMed, 359 citations in OpenAlex.

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134 more citing papers are in PubMed but not listed here.

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

6 authors at 1 institution in 1 country.

Piotr J BalwierzBiozentrum, University of Basel, and Swiss Institute of Bioinformatics, CH-4056 Basel, Switzerland.
Mikhail Pachkov
Phil Arnold
Andreas J Gruber
Mihaela Zavolan
Erik van Nimwegen
SIB Swiss Institute of Bioinformatics · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate reconstruction of the regulatory networks that control gene expression is one of the key current challenges in molecular biology. Although gene expression and chromatin state dynamics are ultimately encoded by constellations of binding sites recognized by regulators such as transcriptions factors (TFs) and microRNAs (miRNAs), our understanding of this regulatory code and its context-dependent read-out remains very limited. Given that there are thousands of potential regulators in mammals, it is not practical to use direct experimentation to identify which of these play a key role for a particular system of interest. We developed a methodology that models gene expression or chromatin modifications in terms of genome-wide predictions of regulatory sites and completely automated it into a web-based tool called ISMARA (Integrated System for Motif Activity Response Analysis). Given only gene expression or chromatin state data across a set of samples as input, ISMARA identifies the key TFs and miRNAs driving expression/chromatin changes and makes detailed predictions regarding their regulatory roles. These include predicted activities of the regulators across the samples, their genome-wide targets, enriched gene categories among the targets, and direct interactions between the regulators. Applying ISMARA to data sets from well-studied systems, we show that it consistently identifies known key regulators ab initio. We also present a number of novel predictions including regulatory interactions in innate immunity, a master regulator of mucociliary differentiation, TFs consistently disregulated in cancer, and TFs that mediate specific chromatin modifications.

Indexed as

Genome, HumanModels, GeneticNucleotide MotifsRegulatory Sequences, Nucleic AcidAlgorithmsAnimalsChromatin Assembly and DisassemblyHumansMiceSequence Analysis, DNA

Identifiers

PMID24515121
PMCPMC4009616
OpenAlexW2115260093

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.