@InProceedings{aukerman_et_al:LIPIcs.SoCG.2020.11, author = {Aukerman, Andrew and Carri\`{e}re, Mathieu and Chen, Chao and Gardner, Kevin and Rabad\'{a}n, Ra\'{u}l and Vanguri, Rami}, title = {{Persistent Homology Based Characterization of the Breast Cancer Immune Microenvironment: A Feasibility Study}}, booktitle = {36th International Symposium on Computational Geometry (SoCG 2020)}, pages = {11:1--11:20}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-143-6}, ISSN = {1868-8969}, year = {2020}, volume = {164}, editor = {Cabello, Sergio and Chen, Danny Z.}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2020.11}, URN = {urn:nbn:de:0030-drops-121695}, doi = {10.4230/LIPIcs.SoCG.2020.11}, annote = {Keywords: Topological data analysis, persistence diagrams} }
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