Evidence map›Paper›PMID 38200084›Full record

ArticleEuropean journal of human genetics : EJHG2024

LanDis: the disease landscape explorer.

Horacio Caniza, Juan J Cáceres, Mateo Torres, Alberto Paccanaro

Abstract read
In one paragraph

Article in European journal of human genetics : EJHG, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Artificial intelligence - the next generation of sequencing?European journal of human genetics : EJHG · 2024
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Horacio CanizaUniversidad Paraguayo Alemana de Ciencias Aplicadas, Facultad de Ciencias de la Ingeniería, San Lorenzo, Paraguay.
Juan J CáceresDepartment of Computer Science, Centre for Systems and Synthetic Biology, Royal Holloway University of London, Egham, UK.
Mateo TorresEscola de Matemática Aplicada, Fundação Getúlio Vargas, Rio de Janeiro, Brazil.ORCID http://orcid.org/0000-0002-9796-1742
Alberto PaccanaroDepartment of Computer Science, Centre for Systems and Synthetic Biology, Royal Holloway University of London, Egham, UK. alberto.paccanaro@rhul.ac.uk.ORCID http://orcid.org/0000-0001-8059-1346

Funding

RCUK | Biotechnology and Biological Sciences Research Council (BBSRC) BB/F00964X/1RCUK | Biotechnology and Biological Sciences Research Council (BBSRC) BB/K004131/1RCUK | Biotechnology and Biological Sciences Research Council (BBSRC) BB/M025047/1RCUK | Medical Research Council (MRC) MR/T001070/1
6 · The paper itself

Abstract

From a network medicine perspective, a disease is the consequence of perturbations on the interactome. These perturbations tend to appear in a specific neighbourhood on the interactome, the disease module, and modules related to phenotypically similar diseases tend to be located in close-by regions. We present LanDis, a freely available web-based interactive tool ( https://paccanarolab.org/landis ) that allows domain experts, medical doctors and the larger scientific community to graphically navigate the interactome distances between the modules of over 44 million pairs of heritable diseases. The map-like interface provides detailed comparisons between pairs of diseases together with supporting evidence. Every disease in LanDis is linked to relevant entries in OMIM and UniProt, providing a starting point for in-depth analysis and an opportunity for novel insight into the aetiology of diseases as well as differential diagnosis.

Identifiers

PMID38200084
PMCPMC10999415

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.