Evidence map›Paper›PMID 26816396›Full record

ArticleIET systems biology2016

Knowledge-based three-body potential for transcription factor binding site prediction.

Wenyi Qin, Guijun Zhao, Matthew Carson, Caiyan Jia, Hui Lu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in IET systems biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Wenyi QinDepartment of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA.
Guijun ZhaoKey Laboratory of Molecular Embryology, Ministry of Health & Shanghai Key Laboratory of Embryo and Reproduction Engineering, Shanghai 200040, People's Republic of China.
Matthew CarsonDepartment of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA.
Caiyan JiaSchool of Computer and Information Technology & Beijing Key Lab of Traffic Data Analysis, Beijing Jiaotong University, Beijing, People's Republic of China.
Hui LuDepartment of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA. huilu.bioinfo@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A structure-based statistical potential is developed for transcription factor binding site (TFBS) prediction. Besides the direct contact between amino acids from TFs and DNA bases, the authors also considered the influence of the neighbouring base. This three-body potential showed better discriminate powers than the two-body potential. They validate the performance of the potential in TFBS identification, binding energy prediction and binding mutation prediction.

Indexed as

Binding SitesProtein ConformationComputational BiologyCrystallography, X-RayDatabases, ProteinEscherichia coli ProteinsKnowledge BasesModels, StatisticalSequence Analysis, ProteinThermodynamicsTranscription FactorsEscherichia coli ProteinsTranscription Factors

Identifiers

PMID26816396
PMCPMC8687219

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.