processes
Editorial
Special Issue: Methods in Computational Biology
Ross P. Carlson 1, * and Herbert M. Sauro 2, *
1
Department of Chemical and Biological Engineering, Montana State University, Bozeman, MT 59717, USA
2
Department of Bioengineering, University of Washington, Seattle, WA 98195-5061, USA
* Correspondence: rossc@montana.edu (R.P.C.); hsauro@uw.edu (H.M.S.); Tel.: +406-994-3631 (R.P.C.);
+206-685-2119 (H.M.S.)
Received: 8 April 2019; Accepted: 8 April 2019; Published: 11 April 2019
Biological systems are multiscale with respect to time and space, exist at the interface of biological
and physical constraints, and their interactions with the environment are often nonlinear. These
systems are being quantified in ever increasing detail using rapidly developing omics technologies;
yet, it is difficult to predict the dynamic and spatial behavior of even the simplest model systems.
Computational biology approaches are essential for leveraging the omics data to develop and test
new theories on biological organization. This is a major challenge for the life sciences, including the
medical, environmental, and bioprocess fields.
A primary goal of this Special Issue “Methods in Computational Biology” is the communication
of computational biology methods, which can extract biological design principles from complex
data, described in enough detail to permit reproduction of the results. This issue integrates highly
interdisciplinary researchers such as biologists, computer scientists, engineers and mathematicians to
advance biological systems analysis. A summary of the contributions to the Special Issue are provided
in the following section; many of the contributions are mentioned more than once because their content
includes themes that fall under multiple categories.
Reviews of Computational Methods
The Special Issue includes two contributions which review and synthesize important aspects of
computational analysis. In Hunt et al. [1], the authors summarize, organize and provide examples of
seven different ‘mechanism-oriented’ model types and discuss how they can be employed to analyze
biological phenomena. Coverage includes not only a mathematical description, but also solvers and
simulation considerations. Norton et al. [2] provide a thorough review of agent-based modeling
of tumor cells, tumor cell heterogeneity as well as tumor interactions with host immune system
components and local physical environments.
Computational Analysis of Biological Dynamics: From Molecular to Cellular to Tissue/Consortia Level
Life is an inherently dynamic process. The Special Issue includes analysis of dynamic processes
on molecular, cellular, tissue and microbial consortia size scales. A comparison of the different
size scales identifies mathematical and computational approaches that span scales. Porubsky and
Sauro [3] examine molecular level processes—for instance, gene networks—and present methodologies
for optimizing parameters necessary to obtain models that exhibit oscillating behavior. Erhardt [4]
examines cellular scale systems and the role of calcium-induced oscillations in cardiac cells and its
role in cardiac arrhythmis. The study applies a number of theories and methods including bifurcation
theory, numerical bifurcation analysis, and geometric singular perturbation theory to study nonlinear
multi time scale systems. Pool et al. [5] studies intra- and extracellular processes associated with
cholesterol and lipoprotein metabolism and how intervention strategies such as statins or diet can
influence metabolism. Farzan and Ierapetritou [6] report on multicellular scale systems and analyze
interactions between mammalian cells and the bioreactor environment with the ultimate goal of
Processes 2019, 7, 205; doi:10.3390/pr7040205
www.mdpi.com/journal/processes
1
Editorial
Special Issue: Methods in Computational Biology
Ross P. Carlson 1, * and Herbert M. Sauro 2, *
1
Department of Chemical and Biological Engineering, Montana State University, Bozeman, MT 59717, USA
2
Department of Bioengineering, University of Washington, Seattle, WA 98195-5061, USA
* Correspondence: rossc@montana.edu (R.P.C.); hsauro@uw.edu (H.M.S.); Tel.: +406-994-3631 (R.P.C.);
+206-685-2119 (H.M.S.)
Received: 8 April 2019; Accepted: 8 April 2019; Published: 11 April 2019
Biological systems are multiscale with respect to time and space, exist at the interface of biological
and physical constraints, and their interactions with the environment are often nonlinear. These
systems are being quantified in ever increasing detail using rapidly developing omics technologies;
yet, it is difficult to predict the dynamic and spatial behavior of even the simplest model systems.
Computational biology approaches are essential for leveraging the omics data to develop and test
new theories on biological organization. This is a major challenge for the life sciences, including the
medical, environmental, and bioprocess fields.
A primary goal of this Special Issue “Methods in Computational Biology” is the communication
of computational biology methods, which can extract biological design principles from complex
data, described in enough detail to permit reproduction of the results. This issue integrates highly
interdisciplinary researchers such as biologists, computer scientists, engineers and mathematicians to
advance biological systems analysis. A summary of the contributions to the Special Issue are provided
in the following section; many of the contributions are mentioned more than once because their content
includes themes that fall under multiple categories.
Reviews of Computational Methods
The Special Issue includes two contributions which review and synthesize important aspects of
computational analysis. In Hunt et al. [1], the authors summarize, organize and provide examples of
seven different ‘mechanism-oriented’ model types and discuss how they can be employed to analyze
biological phenomena. Coverage includes not only a mathematical description, but also solvers and
simulation considerations. Norton et al. [2] provide a thorough review of agent-based modeling
of tumor cells, tumor cell heterogeneity as well as tumor interactions with host immune system
components and local physical environments.
Computational Analysis of Biological Dynamics: From Molecular to Cellular to Tissue/Consortia Level
Life is an inherently dynamic process. The Special Issue includes analysis of dynamic processes
on molecular, cellular, tissue and microbial consortia size scales. A comparison of the different
size scales identifies mathematical and computational approaches that span scales. Porubsky and
Sauro [3] examine molecular level processes—for instance, gene networks—and present methodologies
for optimizing parameters necessary to obtain models that exhibit oscillating behavior. Erhardt [4]
examines cellular scale systems and the role of calcium-induced oscillations in cardiac cells and its
role in cardiac arrhythmis. The study applies a number of theories and methods including bifurcation
theory, numerical bifurcation analysis, and geometric singular perturbation theory to study nonlinear
multi time scale systems. Pool et al. [5] studies intra- and extracellular processes associated with
cholesterol and lipoprotein metabolism and how intervention strategies such as statins or diet can
influence metabolism. Farzan and Ierapetritou [6] report on multicellular scale systems and analyze
interactions between mammalian cells and the bioreactor environment with the ultimate goal of
Processes 2019, 7, 205; doi:10.3390/pr7040205
www.mdpi.com/journal/processes
1