Beyond Biobricks: Synthesizing Synergistic Biochemical Systems from the Bottom-up

Engineers who attempt to discover and optimize the behavior of complex biochemical systems face a dauntingly difficult task. This is especially true if the systems are governed by multiple qualitative and quantitative variables that have non-linear response functions and that interact synergistically. The synthetic biology community has responded to this difficulty by promoting the use of standard biological parts called BioBricks , which are supposed to make biology into traditional engineering and enable engineers to program living organisms in the same way a computer scientists can program a computer . But the BioBricks research program faces daunting hurdles, because the nonlinearity and synergy found throughout biochemical systems generates lots of unpredictable emergent properties. This talk describes an alternative vision of how to engineer complex biochemical systems, according to which we would refashion engineering to fit biology (rather than the other way around). The resulting method (termed Predictive Design Technology or PDT) is a robot- and computer-driven automatic and autonomous implementation of traditional Edisonian science. The PDT method is described and illustrated in application to a number of practical biochemical design tasks, including (2) optimizing combination drug therapies, (2) optimizing cargo capacity of liposomes that self-assemble from complex amphiphile mixtures, (3) optimizing the liposomal formulation of insoluble drugs, and (4) optimizing in vitro protein expression.https://pdxscholar.library.pdx.edu/systems_science_seminar_series/1040/thumbnail.jp

Dropping diversity of products of large US firms: Models and measures

It is widely assumed that in our lifetimes the products available in the global economy have become more diverse. This assumption is difficult to investigate directly, however, because it is difficult to collect the necessary data about every product in an economy each year. We solve this problem by mining publicly available textual descriptions of the products of every large US firms each year from 1997 to 2017. Although many aspects of economic productivity have been steadily rising during this period, our text-based measurements show that the diversity of the products of at least large US firms has steadily declined. This downward trend is visible using a variety of product diversity metrics, including some that depend on a measurement of the similarity of the products of every single pair of firms. The current state of the art in comprehensive and detailed firm-similarity measurements is a Boolean word vector model due to Hoberg and Phillips. We measure diversity using firm-similarities from this Boolean model and two more sophisticated variants, and we consistently observe a significant dropping trend in product diversity. These results make it possible to frame and start to test specific hypotheses for explaining the dropping product diversity trend

Open problems in artificial life

This article lists fourteen open problems in artificial life, each of which is a grand challenge requiring a major advance on a fundamental issue for its solution. Each problem is briefly explained, and, where deemed helpful, some promising paths to its solution are indicated

Topology and Evolution of Technology Innovation Networks

The web of relations linking technological innovation can be fairly described in terms of patent citations. The resulting patent citation network provides a picture of the large-scale organization of innovations and its time evolution. Here we study the patterns of change of patents registered by the US Patent and Trademark Office (USPTO). We show that the scaling behavior exhibited by this network is consistent with a preferential attachment mechanism together with a Weibull-shaped aging term. Such attachment kernel is shared by scientific citation networks, thus indicating an universal type of mechanism linking ideas and designs and their evolution. The implications for evolutionary theory of innovation are discussed.Comment: 6 pages, 5 figures, submitted to Physical Review

Social and ethical checkpoints for bottom-up synthetic biology, or protocells

An alternative to creating novel organisms through the traditional “top-down” approach to synthetic biology involves creating them from the “bottom up” by assembling them from non-living components; the products of this approach are called “protocells.” In this paper we describe how bottom-up and top-down synthetic biology differ, review the current state of protocell research and development, and examine the unique ethical, social, and regulatory issues raised by bottom-up synthetic biology. Protocells have not yet been developed, but many expect this to happen within the next five to ten years. Accordingly, we identify six key checkpoints in protocell development at which particular attention should be given to specific ethical, social and regulatory issues concerning bottom-up synthetic biology, and make ten recommendations for responsible protocell science that are tied to the achievement of these checkpoints

Downward Causation and the Autonomy of Weak Emergence

Weak emergence has been offered as an explicatzon of the ubiquztous notum of emergence used m complexity science After outinung the problem of emergence and comparmg weak emergence with the two other nuun objecuvist approaches to emergence, the paper explams a vetsion of weak emergence and illustrcues at with cellular automata Then it explcans the sart of downward causattan and explanatory auumomy mvolved m weak ernergence