Pablo G Cámara, PhD

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Assistant Professor of Genetics
Senior Fellow, Institute for Biomedical Informatics (IBI), Perelman School of Medicine
Faculty Member, Center for AI and Data Science in Integrated Diagnostics, Perelman School of Medicine
Department: Genetics

Contact information
D105 Richards Building
3700 Hamilton Walk
Philadelphia, PA 19104-6145
Office: 215-746-3545
Education:
BS (Theoretical Physics)
Universidad Autonoma de Madrid, Spain, 2002.
PhD (Theoretical Physics)
Universidad Autonoma de Madrid, Spain, 2006.
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Description of Research Expertise

Research in the Camara lab is focused on the development and application of innovative computational approaches to the study of cellular heterogeneity and its role in disease. To this end, we draw ideas from topology, geometry, statistics, physics, and computer science. Combining these approaches with the use of high-throughput single-cell technologies and large-scale population studies, we aim to achieve a better understanding of the cellular composition and cell-to-cell signaling networks of tumors in relation to their genomes. We are particularly interested in deciphering the cellular ecosystem and heterotypic signaling networks of tumors of the central nervous system, both in adults and children; however, we expect our methods to be of utility to a broader community and collaborate with groups working in related areas of research.

Selected Publications

Aubin, R.*, Troisi, E. C.*, Montelongo, J., Alghalith, A. N., Nasrallah, M. P., Santi, M., Camara, P. G.: Pro-Inflammatory Cytokines Mediate the Epithelial-to-Mesenchymal-Like Transition of Pediatric Posterior Fossa Ependymoma. Nature Communications 13: 3936, 2022.

Bai, Z.*, Woodhouse, S.*, Zhao, Z., Arya, R., Govek, K., Kim, D., Lundh, S., Baysoy, A., Sun, H., Deng, Y., Xiao, Y., Barrett, D. M., Myers, R. M., Grupp, S. A., June, C. H., Fan, R.#, Camara, P. G.#, Melenhorst, J. J.#: Single-cell antigen-specific activation landscape of CAR T infusion product identifies determinants of CD19-positive relapse in patients with ALL. Science Advances 8: eabj2820, 2022 Notes: #corresponding authors. *authors contributed equally. Contribution: I supervised all the computational analyses for this work. These analyses were performed by my postdoc (Dr. Steven Woodhouse) and a graduate student in the group of Dr. Rong Fan (Zhiliang Bai).

Govek, K. W., Troisi, E. C., Miao, Z., Aubin, R. G., Woodhouse, S., Camara, P. G.: Single-Cell Transcriptomic Analysis of mIHC Images via Antigen Mapping. Science Advances 7(10): eabc5464, 2021.

Rabadan R., Mohamedi Y., Rubin U., Chu T., Alghalith A. N., Elliott O., Arnes L., Cal S., Obaya A. J., Levine A. J., Camara P. G.: Identification of Relevant Genetic Alterations in Cancer using Topological Data Analysis. Nature Communications 11(3808), 2020 Notes: I initiated this project during my postdoc at the laboratory of Raul Rabadan and I continued supervising it as the last author during my probationary period at Penn.

Govek K. W., Yamajala V. S., Camara P. G.: Clustering-Independent Analysis of Genomic Data using Spectral Simplicial Theory. PLOS Computational Biology 15(11): e1007509, 2019.

Rizvi, A. H.*, Camara, P. G.*, Kandror, E. K., Roberts, T. J., Schieren, I., Maniatis, T., Rabadan, R.: Single-cell topological RNA-seq analysis reveals insights into cellular differentiation and development. Nature Biotechnology 35(6): 551-560, 2017 Notes: *equal contributing authors.

Camara, P. G.: Topological methods for genomics: present and future directions. Current Opinion in Systems Biology 1: 95-101, 2017.

Lee, J.-K., Wang, J., Sa, J. K., Ladewig, E., Lee, H.-O., Lee, I.-H., Kang, H. J., Rosenbloom, D. S., Camara, P. G., Liu, Z., van Nieuwenhuizen, P., Jung, S. W., Choi, S. W., Kim, J., Chen, A., Kim, K. T., Shin, S., Seo, Y. J., Oh, J. M., Shin, Y. J., Park, C. K., Kong, D. S., Seol, H. J., Blumberg, A., Lee, J. I., Iavarone, A., Park, W. Y., Rabadan, R., Nam, D. H.: Spatiotemporal genomic architecture informs precision oncology in glioblastoma. Nature Genetics 49(4): 594-599, 2017.

Camara, P. G., Rosenbloom, D. S., Emmett, K. J., Levine, A. J., Rabadan, R.: Topological data analysis generates high-resolution, genome-wide maps of human recombination. Cell Systems 3(1): 83-94, 2016.

Camara, P. G., Levine, A. J., Rabadan, R.: Inference of ancestral recombination graphs through topological data analysis. PLOS Computational Biology 12(8): e1005071, 2016.

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Last updated: 11/17/2023
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