Evidence map›Paper›PMID 24895436›Full record

ArticleNucleic acids research2014

DiseaseConnect: a comprehensive web server for mechanism-based disease-disease connections.

Chun-Chi Liu, Yu-Ting Tseng, Wenyuan Li, Chia-Yu Wu, Ilya Mayzus, Andrey Rzhetsky, Fengzhu Sun, Michael Waterman, Jeremy J W Chen, Preet M Chaudhary and 3 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing 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

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

  1. Applications of network analysis to routinely collected health care data: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2018
    Pooled it
  2. Article
  3. Molecular Morbidity Score-Can MicroRNAs Assess the Burden of Disease?International journal of molecular sciences · 2024
    Review
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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

13 authors.

Chun-Chi LiuInstitute of Genomics and Bioinformatics, National Chung Hsing University, Taichung 402, Taiwan Agricultural Biotechnology Center, National Chung Hsing University, Taichung 402, Taiwan xjzhou@usc.edu.
Yu-Ting TsengInstitute of Genomics and Bioinformatics, National Chung Hsing University, Taichung 402, Taiwan.
Wenyuan LiMolecular and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA.
Chia-Yu WuInstitute of Genomics and Bioinformatics, National Chung Hsing University, Taichung 402, Taiwan.
Ilya MayzusComputation Institute, Institute for Genomics and Systems Biology University of Chicago, Chicago, IL 60637, USA.
Andrey RzhetskyComputation Institute, Institute for Genomics and Systems Biology University of Chicago, Chicago, IL 60637, USA.
Fengzhu SunMolecular and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA.
Michael WatermanMolecular and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA.
Jeremy J W ChenAgricultural Biotechnology Center, National Chung Hsing University, Taichung 402, Taiwan Institute of Molecular Biology, National Chung Hsing University, Taichung 402, Taiwan Institute of Biomedical Sciences, National Chung Hsing University, Taichung 402, Taiwan.
Preet M ChaudharyJane Anne Nohl Division of Hematology and Center for the Study of Blood Diseases, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA.
Joseph LoscalzoDepartment of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
Edward CrandallWill Rogers Institute Pulmonary Research Center, University of Southern California, Los Angeles, CA 90033, USA Department of Medicine, University of Southern California, Los Angeles, CA 90089, USA.
Xianghong Jasmine ZhouMolecular and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA xjzhou@usc.edu.

Funding

Modeling the temporal succession of phenotypes & environnnental cuesP50MH094267 · NIMH · UNIVERSITY OF CHICAGO · PI RZHETSKY, ANDREY · 2011 to 2015
$10.2M
MAPGen Knowledge Base (MAPGenKB) and Coordination CenterU01HL108634 · NHLBI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI ZHOU, XIANGHONG JASMINE · 2011 to 2015
$5.3M
GPx-3 and Peroxide Flux in the Endothelial CellR37HL061795 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI LOSCALZO, JOSEPH · 2007 to 2016
$4.3M
The Phathophenotype Landscape of Complex DiseaseU01HL108630 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI LOSCALZO, JOSEPH · 2011 to 2014
$2.7M
Integrative Analysis of Public RNA-seq RepositoriesR01GM105431 · NIGMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI ZHOU, XIANGHONG JASMINE · 2013 to 2016
$1.3M
NHLBI NIH HHS R37 HL061795NHLBI NIH HHS U01HL108630NHLBI NIH HHS U01 HL108634NHLBI NIH HHS U01HL108634NIGMS NIH HHS R01 GM105431NIGMS NIH HHS R01GM105431NIMH NIH HHS P50 MH094267
6 · The paper itself

Abstract

The DiseaseConnect (http://disease-connect.org) is a web server for analysis and visualization of a comprehensive knowledge on mechanism-based disease connectivity. The traditional disease classification system groups diseases with similar clinical symptoms and phenotypic traits. Thus, diseases with entirely different pathologies could be grouped together, leading to a similar treatment design. Such problems could be avoided if diseases were classified based on their molecular mechanisms. Connecting diseases with similar pathological mechanisms could inspire novel strategies on the effective repositioning of existing drugs and therapies. Although there have been several studies attempting to generate disease connectivity networks, they have not yet utilized the enormous and rapidly growing public repositories of disease-related omics data and literature, two primary resources capable of providing insights into disease connections at an unprecedented level of detail. Our DiseaseConnect, the first public web server, integrates comprehensive omics and literature data, including a large amount of gene expression data, Genome-Wide Association Studies catalog, and text-mined knowledge, to discover disease-disease connectivity via common molecular mechanisms. Moreover, the clinical comorbidity data and a comprehensive compilation of known drug-disease relationships are additionally utilized for advancing the understanding of the disease landscape and for facilitating the mechanism-based development of new drug treatments.

Indexed as

SoftwareComorbidityDiseaseDrug TherapyGene ExpressionHumansInternetMicroRNAsPolymorphism, Single NucleotideMicroRNAs

Identifiers

PMID24895436
PMCPMC4086092

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.