Evidence map›Paper›PMID 29355848›Full record

ArticleNature methods2018

Interactome INSIDER: a structural interactome browser for genomic studies.

Michael J Meyer, Juan Felipe Beltrán, Siqi Liang, Robert Fragoza, Aaron Rumack, Jin Liang, Xiaomu Wei, Haiyuan Yu

Abstract read
In one paragraph

Article in Nature methods, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 100 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
100citing papers in PubMed, 1 pooled it
–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

100 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. The aging genome exhibits organized vulnerability to somatic mutations.bioRxiv : the preprint server for biology · 2026
    Article
  5. Article
  6. Article
  7. An interpretable molecular framework for predicting cancer driver missense mutations.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
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  18. Review
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40 more citing papers are in PubMed but not listed here.

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

8 authors.

Michael J MeyerDepartment of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, USA.
Juan Felipe BeltránDepartment of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, USA.
Siqi LiangDepartment of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, USA.
Robert FragozaWeill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York, USA.
Aaron RumackDepartment of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, USA.
Jin LiangWeill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York, USA.
Xiaomu WeiDepartment of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, USA.
Haiyuan YuDepartment of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, USA.ORCID 0000-0001-7597-6049

Funding

Identification and Functional Validation of Human Infertility AllelesR01HD082568 · NICHD · CORNELL UNIVERSITY · PI SCHIMENTI, JOHN C · 2015 to 2024
$6.0M
High-throughput functional characterization of human enhancersUM1HG009393 · NHGRI · CORNELL UNIVERSITY · PI LIS, JOHN T, YU, HAIYUAN · 2017 to 2021
$4.1M
Whole Genome Sequencing to Discover Familial Myeloma Risk GenesR01CA167824 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI LIPKIN, STEVEN M, OFFIT, KENNETH · 2012 to 2016
$1.9M
Towards a comprehensive protein interactome network in Schizosaccharomyces pombeR01GM097358 · NIGMS · CORNELL UNIVERSITY · PI YU, HAIYUAN · 2012 to 2016
$1.7M
Using Protein Interactome Networks to Understand the Functional Role of Coding DNR01GM104424 · NIGMS · WEILL MEDICAL COLL OF CORNELL UNIV · PI LIPKIN, STEVEN M, YU, HAIYUAN · 2013 to 2016
$1.7M
Towards a comprehensive multiscale 3D human interactome networkR01GM124559 · NIGMS · CORNELL UNIVERSITY · PI YU, HAIYUAN · 2017 to 2020
$1.5M
NCI NIH HHS R01 CA167824NHGRI NIH HHS UM1 HG009393NICHD NIH HHS R01 HD082568NIGMS NIH HHS R01 GM097358NIGMS NIH HHS R01 GM104424NIGMS NIH HHS R01 GM124559
6 · The paper itself

Abstract

We present Interactome INSIDER, a tool to link genomic variant information with structural protein-protein interactomes. Underlying this tool is the application of machine learning to predict protein interaction interfaces for 185,957 protein interactions with previously unresolved interfaces in human and seven model organisms, including the entire experimentally determined human binary interactome. Predicted interfaces exhibit functional properties similar to those of known interfaces, including enrichment for disease mutations and recurrent cancer mutations. Through 2,164 de novo mutagenesis experiments, we show that mutations of predicted and known interface residues disrupt interactions at a similar rate and much more frequently than mutations outside of predicted interfaces. To spur functional genomic studies, Interactome INSIDER (http://interactomeinsider.yulab.org) enables users to identify whether variants or disease mutations are enriched in known and predicted interaction interfaces at various resolutions. Users may explore known population variants, disease mutations, and somatic cancer mutations, or they may upload their own set of mutations for this purpose.

Indexed as

MutationProtein Interaction MappingSoftwareDatabases, FactualGenomicsHumansMutagenesisProteinsProteins

Identifiers

PMID29355848
PMCPMC6026581

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.