Evidence map›Paper›PMID 35092413›Full record

ArticleJournal of biosciences2022

Graph-theoretic constraints on vesicle traffic networks.

Somya Mani, Kesav Krishnan, Mukund Thattai

Abstract read
PubMed
In one paragraph

Article in Journal of biosciences, 2022. 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, top 95% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

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

3 authors at 1 institution in 1 country.

Somya ManiCenter for Soft and Living Matter, Institute for Basic Science, Ulsan, South Korea.
Kesav Krishnan
Mukund Thattai
Institute for Basic Science · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Eukaryotic cells use small membrane-enclosed vesicles to transport molecular cargo between intracellular compartments. Interactions between molecules on vesicles and compartments determine the source and target compartment of each vesicle type. The set of compartment and vesicle types in a cell define the nodes and edges of a transport graph known as the vesicle traffic network. The transmembrane SNARE proteins that regulate vesicle fusion to target compartments travel in cycles through the transport graph, but the paths they follow must be tightly regulated to avoid aberrant vesicle fusion. Here we use graph-theoretic ideas to understand how such molecular constraints place constraints on the structure of the transport graph. We identify edge connectivity (the minimum number of edges that must be removed to disconnect a graph) as a key determinant that separates allowed and disallowed types of transport graphs. As we increase the flexibility of molecular regulation, the required edge connectivity decreases, so more types of vesicle transport graphs are allowed. These results can be used to aid the discovery of new modes of molecular regulation and new vesicle traffic pathways.

Indexed as

Computer GraphicsComputational BiologyEukaryotic CellsSNARE ProteinsTransport VesiclesSNARE Proteins

Identifiers

PMID35092413
OpenAlexW4225546913

What OpenQuestion holds

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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.