Evidence map›Paper›PMID 20302666›Full record

ArticleBMC genomics2010

Library of molecular associations: curating the complex molecular basis of liver diseases.

Stefan Buchkremer, Jasmin Hendel, Markus Krupp, Arndt Weinmann, Kai Schlamp, Thorsten Maass, Frank Staib, Peter R Galle, Andreas Teufel

Abstract read
In one paragraph

Article in BMC genomics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Comparison of human cell signaling pathway databases--evolution, drawbacks and challenges.Database : the journal of biological databases and curation · 2015
    Review
  3. CellMinerHCC: a microarray-based expression database for hepatocellular carcinoma cell lines.Liver international : official journal of the International Association for the Study of the Liver · 2014
    Article
  4. Article
  5. Article
  6. 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

9 authors.

Stefan BuchkremerDepartment of Medicine I, Johannes Gutenberg University, Mainz, Germany.
Jasmin Hendel
Markus Krupp
Arndt Weinmann
Kai Schlamp
Thorsten Maass
Frank Staib
Peter R Galle
Andreas Teufel

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSystems biology approaches offer novel insights into the development of chronic liver diseases. Current genomic databases supporting systems biology analyses are mostly based on microarray data. Although these data often cover genome wide expression, the validity of single microarray experiments remains questionable. However, for systems biology approaches addressing the interactions of molecular networks comprehensive but also highly validated data are necessary.

resultsWe have therefore generated the first comprehensive database for published molecular associations in human liver diseases. It is based on PubMed published abstracts and aimed to close the gap between genome wide coverage of low validity from microarray data and individual highly validated data from PubMed. After an initial text mining process, the extracted abstracts were all manually validated to confirm content and potential genetic associations and may therefore be highly trusted. All data were stored in a publicly available database, Library of Molecular Associations http://www.medicalgenomics.org/databases/loma/news, currently holding approximately 1260 confirmed molecular associations for chronic liver diseases such as HCC, CCC, liver fibrosis, NASH/fatty liver disease, AIH, PBC, and PSC. We furthermore transformed these data into a powerful resource for molecular liver research by connecting them to multiple biomedical information resources.

conclusionTogether, this database is the first available database providing a comprehensive view and analysis options for published molecular associations on multiple liver diseases.

Indexed as

Databases, GeneticComputational BiologyData MiningHumansLiver DiseasesUser-Computer Interface

Identifiers

PMID20302666
PMCPMC2851601

What OpenQuestion 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 OpenQuestion graph.