ArticleBioinformatics advances2026
Leveraging training expertise to build capacity in computational personalised medicine.
Article in Bioinformatics advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
23 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Summary: Rapid development of genomic technologies in recent years enables personalised medicine to become an essential part of healthcare. Advanced computational methods are required to extract relevant insights that can be applied in clinical settings. This presents a challenge for clinicians and biomedical researchers, who need specialised training to adopt these tools. Within the context of PerMedCoE, the first European Centre of Excellence in Personalised Medicine, we developed and delivered a competency-based training programme to support professionals in the life sciences to work with modelling and simulation tools that integrate omics data to identify biological processes relevant to disease. We identified a set of required competencies in the field and built a series of career profiles with specific competence levels in these. The competencies and profiles contributed to define the focus and target audience of the training activities delivered: a combination of self-paced learning resources, webinars and online and face-to-face synchronous courses. The outputs of the programme (competencies, career profiles and training materials) can be used by biomedical professionals for their own career development or to train others. In addition, the approach can be adopted by other fields with rapid technological advancements and a constant need to upskill professionals. Availability and implementation: The competency framework is reproduced in full in this paper as supplementary material and available on the Competency Hub at https://competency.ebi.ac.uk/framework/permedcoe/2.1.
Identifiers
What OpenQuestion holds
Registered trials
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.