Evidence map›Paper›PMID 29855947›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2018

Protein Interactomics by Two-Hybrid Methods.

Soon Gang Choi, Aaron Richardson, Luke Lambourne, David E Hill, Marc Vidal

Abstract read
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.4field-weighted citation impact, top 12% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. A Yeast BiFC-seq Method for Genome-wide Interactome Mapping.Genomics, proteomics & bioinformatics · 2022
    Article
  4. Article
  5. 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 at 2 institutions in 1 country.

Soon Gang ChoiCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA.
Aaron RichardsonCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA.
Luke LambourneCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA.
David E HillCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA.
Marc VidalCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA. marc_vidal@dfci.harvard.edu.
Dana-Farber Cancer Institute · USHarvard University · US

Funding

Genomic Analysis of Network Perturbations in Human DiseaseP50HG004233 · NHGRI · DANA-FARBER CANCER INST · PI VIDAL, MARC · 2007 to 2017
$31.6M
Resource ProjectU41HG001715 · NHGRI · DANA-FARBER CANCER INST · PI HILL, DAVID E. · 2015 to 2017
$4.7M
NHGRI NIH HHS P50 HG004233NHGRI NIH HHS U41 HG001715
6 · The paper itself

Abstract

Comprehensive identification of direct, physical interactions between biological macromolecules, such as protein-protein, protein-DNA, and protein-RNA interactions, is critical for our understanding of the function of gene products as well as the global organization and interworkings of various molecular machines within the cell. The accurate and comprehensive detection of direct interactions, however, remains a huge challenge due to the inherent structural complexity arising from various post-transcriptional and translational modifications coupled with huge heterogeneity in concentration, affinity, and subcellular location differences existing for any interacting molecules. This has created a need for developing multiple orthogonal and complementary assays for detecting various types of biological interactions. In this introduction, we discuss the methods developed for measuring different types of molecular interactions with an emphasis on direct protein-protein interactions, critical issues for generating high-quality interactome datasets, and the insights into biological networks and human diseases that current interaction mapping efforts provide. Further, we will discuss what future might lie ahead for the continued evolution of two-hybrid methods and the role of interactomics for expanding the advancement of biomedical science.

Indexed as

Two-Hybrid System TechniquesComputational BiologyHumansProtein Interaction MappingProteinsProteomicsProteinsEdgeticsInteractome networkInteractomicsProtein-protein interactionSystems biologyTwo-hybrid

Identifiers

PMID29855947
PMCPMC6948107
OpenAlexW2806193784

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.