Cell fate reprogramming by control of intracellular network dynamics

Identifying control strategies for biological networks is paramount for practical applications that involve reprogramming a cell's fate, such as disease therapeutics and stem cell reprogramming. Here we develop a novel network control framework that integrates the structural and functional information available for intracellular networks to predict control targets. Formulated in a logical dynamic scheme, our approach drives any initial state to the target state with 100% effectiveness and needs to be applied only transiently for the network to reach and stay in the desired state. We illustrate our method's potential to find intervention targets for cancer treatment and cell differentiation by applying it to a leukemia signaling network and to the network controlling the differentiation of helper T cells. We find that the predicted control targets are effective in a broad dynamic framework. Moreover, several of the predicted interventions are supported by experiments.Comment: 61 pages (main text, 15 pages; supporting information, 46 pages) and 12 figures (main text, 6 figures; supporting information, 6 figures). In revie

Emergence of scaling in random networks

Systems as diverse as genetic networks or the world wide web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution. This feature is found to be a consequence of the two generic mechanisms that networks expand continuously by the addition of new vertices, and new vertices attach preferentially to already well connected sites. A model based on these two ingredients reproduces the observed stationary scale-free distributions, indicating that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.Comment: 11 pages, 2 figure

Mathematics Is Physics

In this essay, I argue that mathematics is a natural science---just like physics, chemistry, or biology---and that this can explain the alleged "unreasonable" effectiveness of mathematics in the physical sciences. The main challenge for this view is to explain how mathematical theories can become increasingly abstract and develop their own internal structure, whilst still maintaining an appropriate empirical tether that can explain their later use in physics. In order to address this, I offer a theory of mathematical theory-building based on the idea that human knowledge has the structure of a scale-free network and that abstract mathematical theories arise from a repeated process of replacing strong analogies with new hubs in this network. This allows mathematics to be seen as the study of regularities, within regularities, within ..., within regularities of the natural world. Since mathematical theories are derived from the natural world, albeit at a much higher level of abstraction than most other scientific theories, it should come as no surprise that they so often show up in physics. This version of the essay contains an addendum responding to Slyvia Wenmackers' essay and comments that were made on the FQXi website.Comment: 15 pages, LaTeX. Second prize winner in 2015 FQXi Essay Contest (see http://fqxi.org/community/forum/topic/2364

Preformed defense responses in a powdery mildew-resistant Hungarian cherry pepper cultivar

A Hungarian cherry pepper (Capsicum annuum var. cerasiformé) cultivar ('Szentesi') displays resistance to pepper powdery mildew caused by Leveillula taurica. Resistance also develops in susceptible sweet pepper (C. annuum) when grafted on resistant cherry pepper cv. Szentesi rootstocks. Powdery mildew (PM) resistance is correlated with high levels of the defense regulator reactive oxygen species superoxide (O2 ') even in healthy plants. In order to further elucidate the mechanisms of preformed defense responses in cherry pepper cv. Szentesi we have monitored levels of salicylic acid (SA), a key molecule of plant defense signaling and expression of so-called pathogenesis/defense related (PR) genes in healthy pepper plants. Assays of free and bound (glycosylated) SA by high performance liquid chromatography (HPLC) revealed that in leaves of PM-resistant pepper levels of free SA are ca. twice as high compared to that of PM-sensitive plants. No difference occurred in levels of bound (glycosylated) SA. Expression of the CaPR-1 gene was several times higher in leaves of PM-resistant pepper than in sensitive plants as assayed by real time reverse transcription quantitative polymerase chain reaction (real time RT-qPCR). On the other hand, high expression levels of the CaPR-2 (glucanase) gene did not entirely correlate with PM-resistance, being detectable only in PM-resistant cv. Szentesi plants but neither in PM-resistant sweet pepper cv. Totál grafted on cv. Szentesi rootstocks nor in susceptible controls (cv. Totál). It seems that graft-transmissible PMresistance of the cherry pepper cv. Szentesi is correlated not only with high levels of superoxide but also with elevated levels of free salicylic acid and enhanced expression of the defense-related CaPR-1 gene

The urban economy as a scale-free network

We present empirical evidence that land values are scale-free and introduce a network model that reproduces the observations. The network approach to urban modelling is based on the assumption that the market dynamics that generates land values can be represented as a growing scale-free network. Our results suggest that the network properties of trade between specialized activities causes land values, and likely also other observables such as population, to be power law distributed. In addition to being an attractive avenue for further analytical inquiry, the network representation is also applicable to empirical data and is thereby attractive for predictive modelling.Comment: Submitted to Phys. Rev. E. 7 pages, 3 figures. (Minor typos and details fixed

Topology of evolving networks: local events and universality

Networks grow and evolve by local events, such as the addition of new nodes and links, or rewiring of links from one node to another. We show that depending on the frequency of these processes two topologically different networks can emerge, the connectivity distribution following either a generalized power-law or an exponential. We propose a continuum theory that predicts these two regimes as well as the scaling function and the exponents, in good agreement with the numerical results. Finally, we use the obtained predictions to fit the connectivity distribution of the network describing the professional links between movie actors.Comment: 13 pages, 3 figure