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Tensor-cell2cell v2 unravels coordinated dynamics of protein- and metabolite-mediated cell–cell communication

Erick Armingol et al.

Bioinformatics2026https://doi.org/10.1093/bioinformatics/btaf667article
ABDC A
Weight
0.37

What the paper says

Tensor-cell2cell v2 and its new coupled tensor component analysis are implemented in Python and available as part of the cell2cell framework at https://github.com/earmingol/cell2cell. This python library is available on PyPI. Code for the analyses of this manuscript can be found in a Code Ocean capsule at https://doi.org/10.24433/CO.0061424.v3, where analyses can be also run and reproduced online. Tutorials can be found at https://cell2cell.readthedocs.io.

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https://doi.org/https://doi.org/10.1093/bioinformatics/btaf667

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@article{erick2026,
  title        = {{Tensor-cell2cell v2 unravels coordinated dynamics of protein- and metabolite-mediated cell–cell communication}},
  author       = {Erick Armingol et al.},
  journal      = {Bioinformatics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1093/bioinformatics/btaf667},
}

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Tensor-cell2cell v2 unravels coordinated dynamics of protein- and metabolite-mediated cell–cell communication

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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