Evidence map›Paper›PMID 24534749›Full record

ReviewCurrent opinion in chemical biology2014

Recent discoveries and applications involving small-molecule microarrays.

Jiyoung A Hong, Dylan V Neel, Dina Wassaf, Francisco Caballero, Angela N Koehler

Abstract readReview
In one paragraph

Review in Current opinion in chemical biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Machine Learning Informs RNA-Binding Chemical Space.Angewandte Chemie (International ed. in English) · 2023
    Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Probing theMedChemComm · 2018
    Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Review
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.

Jiyoung A HongDivision of Hematology/Oncology, Boston Children's Hospital, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Dylan V NeelBroad Institute of MIT and Harvard, Cambridge, MA, USA.
Dina WassafBroad Institute of MIT and Harvard, Cambridge, MA, USA.
Francisco CaballeroBroad Institute of MIT and Harvard, Cambridge, MA, USA.
Angela N KoehlerBroad Institute of MIT and Harvard, Cambridge, MA, USA; David H. Koch Institute for Integrative Cancer Research, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. Electronic address: koehler@mit.edu.

Funding

Developing Direct Small-Molecule Probes of Myc-Dependent TranscriptionR01CA160860 · NCI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI KOEHLER, ANGELA NICOLE · 2012 to 2015
$1.4M
NCI NIH HHS R01 CA160860
6 · The paper itself

Abstract

High-throughput and unbiased binding assays have proven useful in probe discovery for a myriad of biomolecules, including targets of unknown structure or function and historically challenging target classes. Over the past decade, a number of novel formats for executing large-scale binding assays have been developed and used successfully in probe discovery campaigns. Here we review the use of one such format, the small-molecule microarray (SMM), as a tool for discovering protein-small molecule interactions. This review will briefly highlight selected recent probe discoveries using SMMs as well as novel uses of SMMs in profiling applications.

Indexed as

BiomarkersCell SurvivalHumansMicroarray AnalysisProtein BindingProteinsSmall Molecule LibrariesBiomarkersProteinsSmall Molecule Libraries

Identifiers

PMID24534749
PMCPMC3943826

What OpenQuestion holds

Textmetadata
LicenceTDM
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.