Evidence map›Paper›PMID 25204962›Full record

ReviewCellular oncology (Dordrecht, Netherlands)2015

We are all individuals... bioinformatics in the personalized medicine era.

Leander Van Neste, Wim Van Criekinge

Abstract readReview
In one paragraph

Review in Cellular oncology (Dordrecht, Netherlands), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Proteogenomic Approaches for Diseasome Studies.Methods in molecular biology (Clifton, N.J.) · 2025
    Review
  2. Towards the Design of a Patient-Specific Virtual Tumour.Computational and mathematical methods in medicine · 2016
    Article
  3. Personalized cancer medicine: next steps in the genomic era.Cellular oncology (Dordrecht, Netherlands) · 2015
    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

2 authors.

Leander Van NesteDepartment of Pathology, School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, The Netherlands, l.vanneste@maastrichtuniversity.nl.
Wim Van Criekinge

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The medical landscape is evolving at a rapid pace, creating the opportunity for more personalized patient treatment and shifting the way healthcare is approached and thought about. With the availability of (epi)genome-wide, transcriptomic and proteogenomic profiling techniques detailed characterization of a disease at the level of the individual is now possible, offering the opportunity for truly tailored approaches for treatment and patient care. While improvements are still expected, the techniques and the basic analytical tools have reached a state that these can be efficiently deployed in both routine research and clinical practice. Still, some major challenges remain. Notably, holistic approaches, integrating data from several sources, e.g. genomic and epigenomic, will increase the understanding of the underlying biological concepts and provide insight into the causes, effects and effective solutions. However, creating and validating such a knowledge base, potentially for different levels of expertise, and integrating several data points into meaningful information is not trivial.

Indexed as

Computational BiologyHumansPrecision Medicine

Identifiers

PMID25204962
PMCPMC13004265

What OpenQuestion holds

Textmetadata
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.