Evidence map›Paper›PMID 39051984›Full record

ArticleACS synthetic biology2024

The BioRECIPE Knowledge Representation Format.

Emilee Holtzapple, Gaoxiang Zhou, Haomiao Luo, Difei Tang, Niloofar Arazkhani, Casey Hansen, Cheryl A Telmer, Natasa Miskov-Zivanov

Abstract read
In one paragraph

Article in ACS synthetic biology, 2024. 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. Article
  2. Article
  3. 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

8 authors.

Emilee HoltzappleORCID 0000-0003-3907-1597
Haomiao Luo
Difei Tang
Niloofar Arazkhani
Casey Hansen
Cheryl A TelmerDepartment of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States.
Natasa Miskov-ZivanovORCID 0000-0003-1110-3403

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The BioRECIPE (Biological system Representation for Evaluation, Curation, Interoperability, Preserving, and Execution) knowledge representation format was introduced to standardize and facilitate human-machine interaction while creating, verifying, evaluating, curating, and expanding executable models of intra- and intercellular signaling. This format allows a human user to easily preview and modify any model component, while it is at the same time readable by machines and can be processed by a suite of model development and analysis tools. The BioRECIPE format is compatible with multiple representation formats, natural language processing tools, modeling tools, and databases that are used by the systems and synthetic biology communities.

Indexed as

Synthetic BiologyDatabases, FactualHumansModels, BiologicalNatural Language ProcessingSoftwareSystems BiologyautomationFAIR principlesmodelingnetworksrepresentation formatsignaling pathways

Identifiers

PMID39051984
PMCPMC11334182

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.