Evidence map›Paper›PMID 23062343›Full record

ArticleBiophysical journal2012

TATA binding proteins can recognize nontraditional DNA sequences.

Sunmin Ahn, Chia-Ling Huang, Emre Ozkumur, Xirui Zhang, Jyothsna Chinnala, Ayca Yalcin, Sabita Bandyopadhyay, Shelly Russek, M Selim Unlü, Charles DeLisi and 1 more

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In one paragraph

Article in Biophysical journal, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.2field-weighted citation impact, top 21% of its field
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

6 citing papers in PubMed, 16 citations in OpenAlex.

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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

11 authors at 1 institution in 1 country.

Sunmin AhnDepartment of Biomedical Engineering, Boston University, Boston, MA, USA.
Chia-Ling Huang
Emre Ozkumur
Xirui Zhang
Jyothsna Chinnala
Ayca Yalcin
Sabita Bandyopadhyay
Shelly Russek
M Selim Unlü
Charles DeLisi
Rostem J Irani
Boston University · US

Funding

High-throughput, Label-free Promoter Sequence DiscoveryR21GM074872 · NIGMS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI UNLU, M SELIM · 2006 to 2007
$428k
NIGMS NIH HHS GM074872-02NIGMS NIH HHS R21 GM074872
6 · The paper itself

Abstract

We demonstrate an accurate, quantitative, and label-free optical technology for high-throughput studies of receptor-ligand interactions, and apply it to TATA binding protein (TBP) interactions with oligonucleotides. We present a simple method to prepare single-stranded and double-stranded DNA microarrays with comparable surface density, ensuring an accurate comparison of TBP activity with both types of DNA. In particular, we find that TBP binds tightly to single-stranded DNA, especially to stretches of polythymine (poly-T), as well as to the traditional TATA box. We further investigate the correlation of TBP activity with various lengths of DNA and find that the number of TBPs bound to DNA increases >7-fold as the oligomer length increases from 9 to 40. Finally, we perform a full human genome analysis and discover that 35.5% of human promoters have poly-T stretches. In summary, we report, for the first time to our knowledge, the activity of TBP with poly-T stretches by presenting an elegant stepwise analysis of multiple techniques: discovery by a novel quantitative detection of microarrays, confirmation by a traditional gel electrophoresis, and a full genome prediction with computational analyses.

Indexed as

Base SequenceDNADNA, Single-StrandedHumansPoly TProtein BindingSubstrate SpecificityTATA BoxTATA-Box Binding ProteinDNADNA, Single-StrandedPoly TTATA-Box Binding Protein

Identifiers

PMID23062343
PMCPMC3471470
OpenAlexW2160972778

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.