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Biological Data Integration and Model Building

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Encyclopedia of Complexity and Systems Science

Definition of the Subject

Data integration and model building have become essential activities in biological research as technological advancements continue to empower themeasurement of biological data of increasing diversity and scale. High‐throughput technologies provide a wealth of global data sets(e. g. genomics, transcriptomics, proteomics, metabolomics), and the challenge becomes how to integrate this data to maximize the amount of usefulbiological information that can be extracted. Integrating biological data is important and challenging because of the nature of biology. Biologicalsystems have evolved over the course of billions of years, and in that time biological mechanisms have become very diverse, with molecular machines ofintricate detail. Thus, while there are certainly great general scientific principles to be distilled – such as the foundational evolutionarytheory – much of biology is found in the details of these evolved systems. This emphasis on the details of systems...

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Abbreviations

Constraint-based analysis:

A modeling framework based on excluding infeasible network states via environmental, physicochemical, and regulatory constraints to improve predictions of achievable cellular states and behavior.

Data space:

Multidimensional space containing all possible states of a system; this space can be reduced using defined constraints.

Interaction network:

A graph where the nodes represent biomolecules (e. g. genes) and the edges represent defined interactions between the nodes, whether they be direct physical interactions (e. g. protein–protein binding, protein–DNA binding) or functional relationships (e. g. synthetic lethality).

Biochemical reaction network:

Collection of metabolic, signaling, or regulatory chemical reactions described in stoichiometric detail.

Statistical inferrence network:

A network model designed from statistical inference from large-scale biological data sets to be quantitatively predictive for novel perturbations and/or environmental conditions.

Genome:

The complete DNA nucleotide sequence in all chromosomes of an organism.

Transcriptome:

The complete set of RNA transcripts produced from an organism's genome under a particular set of conditions.

Proteome:

The complete set of expressed proteins produced by the genome.

Metabolome:

The complete set of small molecules which are the intermediates and products of an organism's metabolism.

Boolean network:

A set of N discrete‐valued variables, \( { \sigma _1 ,\sigma _2 , \dots ,\sigma _N } \) where \( { \sigma _n \in \{ {0,1} \} } \). To each node a set of \( { k_n } \) nodes, \( { \sigma _{n_1} ,\sigma _{n_2} , \dots ,\sigma _{n_{k_n} } } \) is assigned, which controls the value of \( { \sigma _n } \) through the equation \( \sigma _n (t+1)=f_n (\sigma _{n_1} (t), \dots ,\sigma _{n_{k_n} } (t)) \). In the case of Boolean networks, the functions \( { f_n } \) can be chosen from the ensemble of all possible Boolean functions.

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Author information

Authors and Affiliations

  1. Department of Bioengineering, University of Illinois, Urbana-Champaign, USA

    James A. Eddy & Nathan D. Price

  2. Department of Chemical and Biomolecular Engineering, University of Illinois, Urbana-Champaign, USA

    Nathan D. Price

  3. Institute for Genomic Biology, University of Illinois, Urbana-Champaign, USA

    Nathan D. Price

Authors
  1. James A. Eddy
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  2. Nathan D. Price
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Editor information

Editors and Affiliations

  1. RAMTECH LIMITED, 122 Escalle Lane, Larkspur, CA, 94939, USA

    Robert A. Meyers Ph. D. (Editor-in-Chief) (Editor-in-Chief)

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© 2009 Springer-Verlag

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Eddy, J.A., Price, N.D. (2009). Biological Data Integration and Model Building. In: Meyers, R. (eds) Encyclopedia of Complexity and Systems Science. Springer, New York, NY. https://doi.org/10.1007/978-0-387-30440-3_34

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