Author

A. Aparicio

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 Ecology· 2

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:cell type annotation· 2 Research Focus:differential expression· 2 Research Focus:ecology & biodiversity· 2 Organism:human· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:cancer & tumor microenvironment· 1

Frequent Co-Authors

C. J. Logothetis· 2 shared Y.-Y. Liu· 2 shared A. G. Hoang· 1 shared A. K. Jain· 1 shared A. Rumandla· 1 shared B. A. Foster· 1 shared B. Pradhan· 1 shared B. Zhang· 1 shared

Activity by Year

2018-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

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2 shared papersCancer Biology

C. J. Logothetis

Mutual co-authors in cluster

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4 papers

Recent·Most cited

Feasibility in MacArthur's Consumer-Resource Model

A. Aparicio, T. Wang, S. Saavedra, Y.-Y. Liu

This paper identifies conditions for feasibility in MacArthur's consumer-resource model and shows how system complexity and resource growth affect feasibility.

bioRxiv · Apr 14, 2023Ecology

KDM4A promotes the progression of neuroendocrine prostate cancer

C. S. L. Mak, M. Zhu, X. Liang, F. Wang, F. Yuan, A. G. Hoang, X. Song, P. Shepherd, D. Liang, J. Suh, B. Pradhan, J. Park, M. Zhang, E. Metzger, R. Schule, , G. Wang

This study identifies KDM4A as a key driver of neuroendocrine prostate cancer progression and shows that targeting KDM4A inhibits tumor growth in preclinical models.

bioRxiv · May 14, 2022 · PreprintCancer Biology

Transcriptional Inactivation of TP53 and the BMP Pathway Mediates Therapy-induced Dedifferentiation and Metastasis in Prostate Cancer

H. Han, Y. Wang, J. N. Curto, S. Gurrapu, S. Laudato, A. Rumandla, G. Chakraborty, X. Wang, H. Chen, Y. Jiang, D. Kumar, E. G. Caggiano, B. Zhang, Y. Ji, S. N. Maity, , F. G. Giancotti

The paper identifies a novel subtype of therapy-induced prostate cancer cells with hybrid E/M and stem-like traits, showing their dependency on HER2/3 signaling and resistance to AR inhibition.

bioRxiv · Apr 14, 2021 · PreprintCancer Biology

Identifying sensor species to predict critical transitions in complex ecosystems

A. Aparicio, J. X. Velasco, C. H. Moog, Y.-Y. Liu, M. T. Angulo

The paper develops a method to identify sensor species in ecosystems to predict critical transitions using network structure, validated on experimental lake data.

bioRxiv · Nov 19, 2018 · PreprintEcology