There is an increasing awareness that to properly understand how tumors
originate and grow, and then how to develop effective cures, it must be taken into account
the dynamics of tumors and its great complexity. Tumors are characterized not only by the
coexistence
of multiple scales, both temporal and spatial, but also by multiple and quite
different kinds of interactions, from chemical to mechanical. This makes the
study
of tumors remarkably complicated. A genuine explosion of data concerning the
multi-faceted aspects of this family of phenomena collectively called cancers,
is now becoming available. At the same time, it is becoming quite evident that
traditional tools from biostatistics and bioinformatics cannot manage these
data. Mathematics, theoretical biophysics and computer sciences are needed to
qualitatively and
quantitatively interpret experimental and clinical results, in order to make
realistic predictions.
For more information please click the “Full Text” above.
Citation: Alberto d’Onofrio, Paola Cerrai, Alberto Gandolfi. From the Guest Editors[J]. Mathematical Biosciences and Engineering, 2013, 10(1): i-ii. doi: 10.3934/mbe.2013.10.1i
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Abstract
There is an increasing awareness that to properly understand how tumors
originate and grow, and then how to develop effective cures, it must be taken into account
the dynamics of tumors and its great complexity. Tumors are characterized not only by the
coexistence
of multiple scales, both temporal and spatial, but also by multiple and quite
different kinds of interactions, from chemical to mechanical. This makes the
study
of tumors remarkably complicated. A genuine explosion of data concerning the
multi-faceted aspects of this family of phenomena collectively called cancers,
is now becoming available. At the same time, it is becoming quite evident that
traditional tools from biostatistics and bioinformatics cannot manage these
data. Mathematics, theoretical biophysics and computer sciences are needed to
qualitatively and
quantitatively interpret experimental and clinical results, in order to make
realistic predictions.
For more information please click the “Full Text” above.