Evidence map›Paper›PMID 32863484›Full record

ArticleTrends in analytical chemistry : TRAC2020

Ultraspecific analyte detection by direct kinetic fingerprinting of single molecules.

Tanmay Chatterjee, Zi Li, Kunal Khanna, Karen Montoya, Muneesh Tewari, Nils G Walter, Alexander Johnson-Buck

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Trends in analytical chemistry : TRAC, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

7 authors.

Tanmay ChatterjeeSingle Molecule Analysis Group, Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States.
Zi LiSingle Molecule Analysis Group, Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States.
Kunal KhannaSingle Molecule Analysis Group, Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States.
Karen MontoyaSingle Molecule Analysis Group, Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States.
Muneesh TewariDepartment of Internal Medicine, Division of Hematology/Oncology, University of Michigan, Ann Arbor, Michigan 48109, United States.
Nils G WalterSingle Molecule Analysis Group, Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States.
Alexander Johnson-BuckSingle Molecule Analysis Group, Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States.

Funding

Michigan Chemistry-Biology Interface Training ProgramT32GM132046 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Emily E Scott, Wenjing Wang · 2019 to 2026
$4.1M
Optimization and Validation of Single-Molecule Kinetic Fingerprinting Technology for Rapid, Ultra-Specific Detection of Cancer MutationsR33CA229023 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI TEWARI, MUNEESH, WALTER, NILS G · 2018 to 2020
$1.2M
Single-molecule counting of cancer biomarker miRNAs in human biofluidsR21CA204560 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI WALTER, NILS G · 2017 to 2019
$614k
NCI NIH HHS R21 CA204560NCI NIH HHS R33 CA229023NIGMS NIH HHS T32 GM132046
6 · The paper itself

Abstract

The detection and quantification of biomarkers have numerous applications in biological research and medicine. The most widely used methods to detect nucleic acids require amplification

Indexed as

Disease biomarkerkinetic fingerprintingpolymerase chain reactionsingle-molecule fluorescence detectionsingle-nucleotide polymorphismsingle-nucleotide variant

Identifiers

PMID32863484
PMCPMC7451408

What OpenQuestion holds

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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.