New causal discovery algorithm over censored variables identifies subtype-specific drivers of breast cancer progression

Tyler C Lovelace, Panayiotis V Benos

Open source

DOI: 10.1093/gigascience/giag060
Published: 2026
Container: GigaScience
Publisher: Oxford University Press (OUP)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1093/gigascience/giag060,
  title = {New causal discovery algorithm over censored variables identifies subtype-specific drivers of breast cancer progression},
  author = {Tyler C Lovelace and Panayiotis V Benos},
  year = {2026},
  journal = {GigaScience},
  doi = {10.1093/gigascience/giag060},
  url = {https://doi.org/10.1093/gigascience/giag060}
}

RIS

TY  - JOUR
TI  - New causal discovery algorithm over censored variables identifies subtype-specific drivers of breast cancer progression
AU  - Tyler C Lovelace
AU  - Panayiotis V Benos
PY  - 2026
JO  - GigaScience
DO  - 10.1093/gigascience/giag060
UR  - https://doi.org/10.1093/gigascience/giag060
ER  -

APA

Lovelace, T. C., & Benos, P. V. (2026). New causal discovery algorithm over censored variables identifies subtype-specific drivers of breast cancer progression. GigaScience. https://doi.org/10.1093/gigascience/giag060

Source records

crossref · retrieved 2026-09-24T23:14:50.082Z