Evidence map›Paper›PMID 39436597›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2025

From Gene to Whole Cell: Modeling, Visualization, and Analysis.

Bjorn Sommer, Sabrina Jaeger-Honz

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Bjorn SommerInnovation Design Engineering, School of Design, Royal College of Art, London, UK. bjorn.sommer@rca.ac.uk.
Sabrina Jaeger-HonzLife Science Informatics, Department of Computer and Information Science, University of Konstanz, Konstanz, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Proteogenomics combines proteomic and genetic data to gain new insights in molecular mechanisms. Here, we extend this approach toward structural biology from a tool perspective. The chapter starts with tools which can be used to explore genetic information and then enrich those with proteomic data. Based on the corresponding identifiers, three-dimensional structures of proteins are identified and used to embed them in their molecular environment, here the surrounding membrane. This membrane is then mapped onto the surface of an interpretative three-dimensional cell model. Then, the embedded protein and the cell environment are associated with a metabolic pathway, again based on the identifiers provided by biomedical databases. Accompanying the different chapters, related work is discussed which can alternatively be used. Finally, an outlook toward immersive analytics is given.

Indexed as

ProteomicsComputational BiologyHumansMetabolic Networks and PathwaysModels, MolecularSoftwareCell visualizationData integrationImmersive analyticsIntegrative bioinformaticsMolecular modelingProteogenomicsStructural biology

Identifiers

What OpenQuestion holds

Textmetadata
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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.