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Network Inference in Molecular Biology

Part of the SpringerBriefs in Electrical and Computer Engineering Book Series

DOI: 10.1007/978-1-4614-3113-8

ISBN: 978-1-4614-3112-1

Publisher: Springer New York - Springer Journals

May 24, 2012

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Chapter 1Overview of Network Inference

Lingeman, Jesse M; Shasha, Dennis

Pages: 1 –9

[Inferring a causal link is useful in many applications, from medicine to economics to engineering. If some A can cause some B to take on a high value (where A could be a gene in our context, a market intervention in economics, or a design element in engineering), then preventing B from taking...
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Chapter 2Clustering Data

Lingeman, Jesse M; Shasha, Dennis

Pages: 11 –22

[Clustering reduces the size of the data by replacing individual genes with artificial super-genes that can be treated as single nodes for the purposes of network inference. By clustering genes that work together as a preprocessing step, we can improve the accuracy of the resulting network by...
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Chapter 3Step 2: Use Steady State Data for Network Inference

Lingeman, Jesse M; Shasha, Dennis

Pages: 23 –50

[We say an organism is in steady state if the values of what we are measuring (e.g. gene expression) won’t change unless we change its conditions in some way. For example, the organism may be in one steady state in a low nutrient condition, another in a high nutrient condition, and still another...
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Chapter 4Step 3: Using Time-Series Data

Lingeman, Jesse M; Shasha, Dennis

Pages: 51 –76

[Time-series data gives information about the values of genes at a series of consecutive time points. This temporal information can be exploited to infer directionality of edges, or help to infer causal relations between genes. However, adding temporal information also creates a more complex...
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Chapter 5Pipelines

Lingeman, Jesse M; Shasha, Dennis

Pages: 77 –95

[Various techniques for gene network inference learn from different types of data, have different theoretical approaches, and use different types of statistics. For example, an algorithm using a Bayesian approach may be extracting different information from the data than one using a regression...

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