Evidence map›Paper›PMID 37181657›Full record

ArticleComputational and structural biotechnology journal2023

PRO-Simat: Protein network simulation and design tool.

Rana Salihoglu, Mugdha Srivastava, Chunguang Liang, Klaus Schilling, Aladar Szalay, Elena Bencurova, Thomas Dandekar

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Computational and structural biotechnology journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 28% of its field
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

5 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Cat-E: A comprehensive web tool for exploring cancer targeting strategies.Computational and structural biotechnology journal · 2024
    Article
  4. Review
  5. 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

7 authors at 1 institution in 2 countries.

Rana SalihogluDepartment of Bioinformatics, University of Würzburg, Würzburg, Germany.
Mugdha SrivastavaDepartment of Bioinformatics, University of Würzburg, Würzburg, Germany.
Chunguang LiangDepartment of Bioinformatics, University of Würzburg, Würzburg, Germany.
Klaus SchillingInformatics VII, Robotics and Telematics, Department of Mathematics and Informatics, Am Hubland, University of Würzburg, D-97074 Würzburg, Germany.
Aladar SzalayDept. of Biochemistry, Biocenter, Am Hubland, University of Würzburg, D-97074 Würzburg, Germany.
Elena BencurovaDepartment of Bioinformatics, University of Würzburg, Würzburg, Germany.
Thomas DandekarDepartment of Bioinformatics, University of Würzburg, Würzburg, Germany.
University of Würzburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PRO-Simat is a simulation tool for analysing protein interaction networks, their dynamic change and pathway engineering. It provides GO enrichment, KEGG pathway analyses, and network visualisation from an integrated database of more than 8 million protein-protein interactions across 32 model organisms and the human proteome. We integrated dynamical network simulation using the Jimena framework, which quickly and efficiently simulates Boolean genetic regulatory networks. It enables simulation outputs with in-depth analysis of the type, strength, duration and pathway of the protein interactions on the website. Furthermore, the user can efficiently edit and analyse the effect of network modifications and engineering experiments. In case studies, applications of PRO-Simat are demonstrated: (i) understanding mutually exclusive differentiation pathways in

Indexed as

Network simulationProtein analysisSignalling pathways, dynamic protein-protein interactions, optogenetics, oncolytic virus, DNA storage

Identifiers

PMID37181657
PMCPMC10172639
OpenAlexW4367043218

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.