From Toy Models to Quantifying Mosaic Development

Time travel in the Terminator metaverse. COURTESY: Michael Talley.

Almost two years ago, Richard Gordon and I published a paper in the journal Biosystems called "Toy Models for Macroevolutionary Patterns and Trends" [1]. Now, almost exactly two years later [2], we have published a second paper (not quite a follow-up) called "Quantifying Mosaic Development: towards an evo-devo postmodern synthesis of the evolution of development via differentiation trees of embryos". While the title is quite long, the approach can be best described as computational/ statistical evolution of development (evo-devo).

Sketch of a generic differentiation tree, which figures prominently in our theoretical synthesis and analysis. COURTESY: Dr. Richard Gordon.

This paper is part of a special issue in the journal Biology called "Beyond the Modern Evolutionary Synthesis- what have we missed?" and a product of the DevoWorm project. The paper itself is a hybrid theoretical synthesis/research report, and introduces a variety of comparative statistical and computational techniques [3] that are used to analyze quantitative spatial and temporal datasets representing early embryogenesis. Part of this approach was previewed in our most recent public lecture to the OpenWorm Foundation.

The comparative data analysis involves investigations within and between two species from different parts of the tree of life: Caenorhabditis elegans (Nematode, invertebrate) and Ciona intestinalis (Tunicate, chordate). The main comparison involves different instances of early mosaic development, or a developmental process that is deterministic with respect to cellular fate. We also reference data from the regulative developing Axolotl (Amphibian, vertebrate) in one of the analyses. All of the analyses involve the reuse and analysis of secondary data, which is becoming an important part of the scientific process for many research groups.

One of the techniques featured in the paper is an information-theoretic technique called information isometry [4]. This method was developed within the DevoWorm group, and uses a mathematical representation called an isometric graph to visualize cell lineages organized in different ways (e.g. a lineage tree vs. a differentiation tree). This method is summarized and validated in our paper "Information Isometry Technique Reveals Organizational Features in Developmental Cell Lineages" [4]. Briefly, each level of the cell lineage is represented as an isoline, which contains points of a specific Hamming distance. The Hamming distance is the distance between that particular cell in two alternative cell lineage orderings (the forementioned lineage and differentiation trees).

An example of an isometric graph from Caenorhabditis elegans, taken from Figure 12 in [5]. The position of a point representing a cell is based on the depth of its node in the cell lineage. The positions of all points are rotated 45 degrees clockwise from a bottom-to-top differentiation tree (in this case) ordering, where the one-cell stage is at the bottom of the graph.

A final word on the new Biology paper as it related to the use of references. Recently, I ran across a paper called "The Memory of Science: Inflation, Myopia, and the Knowledge Network" [6], which introduced me to the statistical definition of citation age. This inspired me to calculate the citation age of all journal references from three papers: Toy Models, Quantifying Mosaic Development, and a Nature Reviews Neuroscience paper from Bohil, Alicea (me), and Biocca, published in 2011. This was used as an analytical control -- as it is a review, it should contain papers which are older than the contemporary literature. Here are the age distributions for all three papers.

Distribution of Citation Ages from "Toy Models for Macroevolutionary Patterns and Trends" (circa 2014).

Distribution of Citation Ages from "Quantifying Mosaic Development: Towards an Evo-Devo Postmodern Synthesis of the Evolution of Development Via Differentiation Trees of Embryos" (circa 2016).

Distribution of Citation Ages from "Virtual Reality in Neuroscience Research and Therapy" (circa 2011).

What is interesting here is that both "Toy Models" and "Quantifying Mosaic Development" show a long tail with respect to age, while the review article shows very little in terms of a distributional tail. While there are differences in topical literatures (the VR and associated perceptual literature is not that old, after all) that influence the result, it seems that the recurrent academic Terminators utilize the literature in a way somewhat differently than most contemporary research papers. While the respect for history is somewhat author and topically dependent, it does seem to add a extra dimension to the research.

NOTES:
[1] the Toy Models paper was part of a Biosystems special issue called "Patterns in Evolution".

[2] This is a Terminator metaverse reference, in which the Terminator comes back every ten years to cause, effect, and/or stop Judgement Day.

[3] Gittleman, J.L. and Luh, H. (1992). On Comparing Comparative Methods. Annual Review of Ecology and Systematics, 23, 383-404.

[4] Alicea, B., Portegys, T.E., and Gordon, R. (2016). Information Isometry Technique Reveals Organizational Features in Developmental Cell Lineages. bioRxiv, doi:10.1101/062539

[5] Alicea, B. and Gordon, R. (2016). Quantifying Mosaic Development: Towards an Evo-Devo Postmodern Synthesis of the Evolution of Development Via Differentiation Trees of Embryos. Biology, 5(3), 33.

[6] Pan, R.K., Petersen, A.M., Pammolli, F., and Fortunato, S. (2016). The Memory of Science: Inflation, Myopia, and the Knowledge Network. arXiv, 1607.05606.