Stochastic and deterministic multiscale models for systems biology: an auxin-transport case study

Building better models of cellular pathways is one of the major challenges of systems biology and functional genomics. There is a need for methods to build on established expert knowledge and reconcile it with results of high-throughput studies. Moreover, the available data sources are heterogeneous and need to be combined in a way specific for the part of the pathway in which they are most informative. Here, we present a compartment specific strategy to integrate edge, node and path data for the refinement of a network hypothesis. Specifically, we use a local-move Gibbs sampler for refining pathway hypotheses from a compendium of heterogeneous data sources, including novel methodology for integrating protein attributes. We demonstrate the utility of this approach in a case study of the pheromone response MAPK pathway in the yeast S. cerevisiae.

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Multimethod optimization in the cloud: A case-study in systems biology modelling

Concurrency and Computation Practice and Experience ◽

10.1002/cpe.4488 ◽

2018 ◽

Vol 30 (12) ◽

pp. e4488 ◽

Cited By ~ 3

Author(s):

Patricia González ◽

David R. Penas ◽

Xoan C. Pardo ◽

Julio R. Banga ◽

Ramón Doallo

Keyword(s):

Systems Biology ◽

Multimethod Optimization

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Agent-Based Modelling in Multicellular Systems Biology

Data Analytics in Medicine ◽

10.4018/978-1-7998-1204-3.ch020 ◽

2020 ◽

pp. 369-389

Author(s):

Sara Montagna ◽

Andrea Omicini

Keyword(s):

Developmental Biology ◽

Drosophila Melanogaster ◽

Systems Biology ◽

Computational Models ◽

The Self ◽

Agent Based Simulation ◽

Agent Based ◽

Agent Based Modelling ◽

Multi Agent

This chapter aims at discussing the content of multi-agent based simulation (MABS) applied to computational biology i.e., to modelling and simulating biological systems by means of computational models, methodologies, and frameworks. In particular, the adoption of agent-based modelling (ABM) in the field of multicellular systems biology is explored, focussing on the challenging scenarios of developmental biology. After motivating why agent-based abstractions are critical in representing multicellular systems behaviour, MABS is discussed as the source of the most natural and appropriate mechanism for analysing the self-organising behaviour of systems of cells. As a case study, an application of MABS to the development of Drosophila Melanogaster is finally presented, which exploits the ALCHEMIST platform for agent-based simulation.

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Emergence

10.1093/acprof:oso/9780190277987.003.0003 ◽

2017 ◽

Author(s):

Matthew Croasmun

Keyword(s):

Systems Biology ◽

Philosophy Of Science ◽

Downward Causation ◽

Feedback Loops ◽

Emergent Properties ◽

Middle Ground ◽

Emergence Theory ◽

Multiple Levels ◽

Causal Structures

Emergence theory in philosophy of science is introduced, first in modest terms of the emergent properties exhibited by complex wholes that are not exhibited by their constituent parts. Then, emergence is treated as a trans-ordinal theory that stakes out a middle ground between reductionism and dualism. The tension between supervenience and downward causation is described as the generative dialectic of emergence. The coherence of downward causation is debated and ultimately affirmed on account of the prevalence of downward causation in the sorts of accounts produced by fields like systems biology. Racism is treated as a case study of the sorts of causal feedback loops generated by complex causal structures that operate at multiple levels of hierarchy.

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