How computational models contribute to our understanding of the germ line

Abstract

SUMMARYComputational models are an invaluable tool in modern biology. They provide a framework within which to summarize existing knowledge, enable competing hypotheses to be compared qualitatively and quantitatively, and to facilitate the interpretation of complex data. Moreover, models allow questions to be investigated that are difficult to approach experimentally. Theories can be tested in context, identifying the gaps in our understanding and potentially leading to new hypotheses. Models can be developed on a variety of scales and with different levels of mechanistic detail, depending on the available data, the biological questions of interest, and the available mathematical and computational tools. The goal of this review is to provide a broad picture of how modeling has been applied to reproductive biology. Specifically, we look at four uses of modeling: (i) comparing hypotheses; (ii) interpreting data; (iii) exploring experimentally challenging questions; and (iv) hypothesis evaluation and generation. We present examples of each of these applications in reproductive biology, drawing from a range of organismsÀ Àincluding Drosophila, Caenorhabditis elegans, mouse, and humans. We aim to describe the data and techniques used to construct each model, and to highlight the benefits of modeling to the field, as complementary to experimental work.Mol. Reprod. Dev. 83: 944À957, 2016. ß 2016 Wiley Periodicals, Inc. [T]he process of developing and`r unning'' a formal model requires that the assumptions underlying specific hypotheses are made explicit, and exposes potential gaps in current knowledge.

Modeling the C. elegans germline stem cell genetic network using automated reasoning

“…Several computational models for studying network topology ( Albert and Othmer, 2003 ), C. elegans vulval precursor cells (VPC) cell fate specification ( Fisher et al, 2007 , Fisher et al, 2005 , Kam et al, 2008 ) and the C. elegans germ line ( Atwell et al, 2015 , Setty et al, 2012 ) (particularly in the context of proliferative germ cell behavior — see Atwell et al, 2016 and references within) have been developed in the past years. Albert and Othmer (2003) applied the Boolean network approach for analyzing and manipulating genetic circuits in Drosophila melanogaster , focusing on the segment polarity gene network developed earlier ( Von Dassow et al, 2000 ).…”

“…Computational models of germline development have been constructed for C. elegans , D. melanogaster and human (see Atwell et al, 2016 and references therein). In Klein et al (2010) modeling is used to study different stem cell-maintenance hypotheses in the context of mouse spermatogenesis.…”

Modeling the C. elegans Germline Stem Cell Genetic Network using Automated Reasoning

“…Several computational models for studying the C . elegans germ line have been developed in the past years (see [4] and references within), particularly in the context of proliferative germ cell behavior. Among the first models, exploring germ line development (larva) and maintenance (adult), is the model proposed by Setty [5].…”

“…Development of logical rules leading to an activity of each component, using the Boolean operators AND, OR, and NOT. 4. Encoding a set of components and interactions in the reasoning framework.…”