TY - JOUR
T1 - PhyloOncology
T2 - Understanding cancer through phylogenetic analysis
AU - Somarelli, Jason A.
AU - Ware, Kathryn E.
AU - Kostadinov, Rumen
AU - Robinson, Jeffrey M.
AU - Diogo, Rui
AU - Robinson, Jeffrey M.
AU - Fourie, Nicolaas
AU - Amri, Hakima
AU - Abu-Asab, Mones
AU - Swofford, David
AU - Townsend, Jeffrey P.
N1 - Publisher Copyright:
© 2016 Elsevier B.V.
PY - 2017/4/1
Y1 - 2017/4/1
N2 - Despite decades of research and an enormity of resultant data, cancer remains a significant public health problem. New tools and fresh perspectives are needed to obtain fundamental insights, to develop better prognostic and predictive tools, and to identify improved therapeutic interventions. With increasingly common genome-scale data, one suite of algorithms and concepts with potential to shed light on cancer biology is phylogenetics, a scientific discipline used in diverse fields. From grouping subsets of cancer samples to tracing subclonal evolution during cancer progression and metastasis, the use of phylogenetics is a powerful systems biology approach. Well-developed phylogenetic applications provide fast, robust approaches to analyze high-dimensional, heterogeneous cancer data sets. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.
AB - Despite decades of research and an enormity of resultant data, cancer remains a significant public health problem. New tools and fresh perspectives are needed to obtain fundamental insights, to develop better prognostic and predictive tools, and to identify improved therapeutic interventions. With increasingly common genome-scale data, one suite of algorithms and concepts with potential to shed light on cancer biology is phylogenetics, a scientific discipline used in diverse fields. From grouping subsets of cancer samples to tracing subclonal evolution during cancer progression and metastasis, the use of phylogenetics is a powerful systems biology approach. Well-developed phylogenetic applications provide fast, robust approaches to analyze high-dimensional, heterogeneous cancer data sets. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.
KW - Cancer stratification
KW - Cancer types
KW - Clonal evolution
KW - Tumor heterogeneity
KW - Tumor trees
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U2 - 10.1016/j.bbcan.2016.10.006
DO - 10.1016/j.bbcan.2016.10.006
M3 - Article
C2 - 27810337
AN - SCOPUS:85006804252
SN - 0304-419X
VL - 1867
SP - 101
EP - 108
JO - Biochimica et Biophysica Acta - Reviews on Cancer
JF - Biochimica et Biophysica Acta - Reviews on Cancer
IS - 2
ER -