Persistent homology for the automatic classification of prostate cancer aggressiveness in histopathology images

Lawson, Peter J.; Schupbach, Jordan; Fasy, Brittany Terese; Sheppard, John W.

doi:10.1117/12.2513137

Cited by 6 publications

(1 citation statement)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Lawson et al 19,20 explore the cellular architecture of prostate cancer. The Gleason grading system is a one to five scale that is a powerful prognostic indicator based on increasingly neoplastic tissue organization of the prostate: a uniform cellular architecture becomes disrupted forming glands that eventually form solid cell types.…”

Section: Cellular Architecturementioning

confidence: 99%

The shape of things to come: Topological data analysis and biology, from molecules to organisms

Amézquita

Quigley

Ophelders

et al. 2020

Developmental Dynamics

View full text Add to dashboard Cite

Shape is data and data is shape. Biologists are accustomed to thinking about how the shape of biomolecules, cells, tissues, and organisms arise from the effects of genetics, development, and the environment. Less often do we consider that data itself has shape and structure, or that it is possible to measure the shape of data and analyze it. Here, we review applications of topological data analysis (TDA) to biology in a way accessible to biologists and applied mathematicians alike. TDA uses principles from algebraic topology to comprehensively measure shape in data sets. Using a function that relates the similarity of data points to each other, we can monitor the evolution of topological features—connected components, loops, and voids. This evolution, a topological signature, concisely summarizes large, complex data sets. We first provide a TDA primer for biologists before exploring the use of TDA across biological sub‐disciplines, spanning structural biology, molecular biology, evolution, and development. We end by comparing and contrasting different TDA approaches and the potential for their use in biology. The vision of TDA, that data are shape and shape is data, will be relevant as biology transitions into a data‐driven era where the meaningful interpretation of large data sets is a limiting factor.

show abstract

Section: Cellular Architecturementioning

confidence: 99%