Author

S. E. Clare

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Cancer Biology· 2

Signature Assays, Organisms & Methods

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Organism:human· 2 Research Focus:cancer & tumor microenvironment· 1 Research Focus:chromatin & epigenetic regulation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1 Research Focus:metabolism & bioenergetics· 1

Frequent Co-Authors

S. A. Khan· 2 shared A. B. M. M. K. Islam· 1 shared A. Vo· 1 shared C. Mao· 1 shared C. W. McCloskey· 1 shared E. V. Benevolenskaya· 1 shared F. R. Palma· 1 shared G. Cottone· 1 shared

Activity by Year

2019-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 31 mutual co-author links

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2 shared papersCancer Biology

S. A. Khan

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2 papers

Recent·Most cited

Metabolic shift to serine pathway induced by lipids confers oncogenic properties in non-transformed breast cells

M. B. Eduardo, G. Cottone, C. W. McCloskey, S. Liu, M. P. Zappia, E. V. Benevolenskaya, A. B. M. M. K. Islam, M. V. Frolov, F. R. Palma, P. Gao, J. Setya, H. Gao, X. Xuei, R. Khokha, J. Locasale, , S. E. Clare

The paper shows that lipid metabolism, specifically through OA, shifts metabolic pathways in breast cells, increasing SAM and 2-HG, which contribute to oncogenic properties and epigenetic changes.

bioRxiv · Feb 21, 2024 · PreprintCancer Biology

Deep learning for cancer type classification

Z. Zeng, C. Mao, A. Vo, J. O. Nugent, S. A. Khan, S. E. Clare, Y. Luo

This study introduces DeepCues, a deep learning model that improves cancer type classification using DNA sequencing data, achieving 77.6% accuracy on TCGA data and showing significant improvement over conventional methods.

bioRxiv · Apr 17, 2019 · PreprintCancer Biology