Model Revision from Temporal Logic Properties in Computational Systems Biology

International audienceSystems biologists build models of bio-molecular processes from knowledge acquired both at the gene and protein levels, and at the phenotype level through experiments done in wildlife and mutated organisms. In this chapter, we present qualitative and quantitative logic learning tools, and illustrate how they can be useful to the modeler. We focus on biochemical reaction models written in the Systems Biology Markup Language SBML, and interpreted in the Biochemical Abstract Machine BIOCHAM. We first present a model revision algorithm for inferring reaction rules from biological properties expressed in temporal logic. Then we discuss the representations of kinetic models with ordinary differential equations (ODEs) and with stochastic logic programs (SLPs), and describe a parameter search algorithm for finding parameter values satisfying quantitative temporal properties. These methods are illustrated by a simple model of the cell cycle control, and by an application to the modelling of the conditions of synchronization in period of the cell cycle by the circadian cycle

Fitting the integrated Spectral Energy Distributions of Galaxies

Fitting the spectral energy distributions (SEDs) of galaxies is an almost universally used technique that has matured significantly in the last decade. Model predictions and fitting procedures have improved significantly over this time, attempting to keep up with the vastly increased volume and quality of available data. We review here the field of SED fitting, describing the modelling of ultraviolet to infrared galaxy SEDs, the creation of multiwavelength data sets, and the methods used to fit model SEDs to observed galaxy data sets. We touch upon the achievements and challenges in the major ingredients of SED fitting, with a special emphasis on describing the interplay between the quality of the available data, the quality of the available models, and the best fitting technique to use in order to obtain a realistic measurement as well as realistic uncertainties. We conclude that SED fitting can be used effectively to derive a range of physical properties of galaxies, such as redshift, stellar masses, star formation rates, dust masses, and metallicities, with care taken not to over-interpret the available data. Yet there still exist many issues such as estimating the age of the oldest stars in a galaxy, finer details ofdust properties and dust-star geometry, and the influences of poorly understood, luminous stellar types and phases. The challenge for the coming years will be to improve both the models and the observational data sets to resolve these uncertainties. The present review will be made available on an interactive, moderated web page (sedfitting.org), where the community can access and change the text. The intention is to expand the text and keep it up to date over the coming years.Comment: 54 pages, 26 figures, Accepted for publication in Astrophysics & Space Scienc

The Theory of Brown Dwarfs and Extrasolar Giant Planets

Straddling the traditional realms of the planets and the stars, objects below the edge of the main sequence have such unique properties, and are being discovered in such quantities, that one can rightly claim that a new field at the interface of planetary science and and astronomy is being born. In this review, we explore the essential elements of the theory of brown dwarfs and giant planets, as well as of the new spectroscopic classes L and T. To this end, we describe their evolution, spectra, atmospheric compositions, chemistry, physics, and nuclear phases and explain the basic systematics of substellar-mass objects across three orders of magnitude in both mass and age and a factor of 30 in effective temperature. Moreover, we discuss the distinctive features of those extrasolar giant planets that are irradiated by a central primary, in particular their reflection spectra, albedos, and transits. Aspects of the latest theory of Jupiter and Saturn are also presented. Throughout, we highlight the effects of condensates, clouds, molecular abundances, and molecular/atomic opacities in brown dwarf and giant planet atmospheres and summarize the resulting spectral diagnostics. Where possible, the theory is put in its current observational context.Comment: 67 pages (including 36 figures), RMP RevTeX LaTeX, accepted for publication in the Reviews of Modern Physics. 30 figures are color. Most of the figures are in GIF format to reduce the overall size. The full version with figures can also be found at: http://jupiter.as.arizona.edu/~burrows/papers/rm

Observations of the High Redshift Universe

(Abridged) In these lectures aimed for non-specialists, I review progress in understanding how galaxies form and evolve. Both the star formation history and assembly of stellar mass can be empirically traced from redshifts z~6 to the present, but how the various distant populations inter-relate and how stellar assembly is regulated by feedback and environmental processes remains unclear. I also discuss how these studies are being extended to locate and characterize the earlier sources beyond z~6. Did early star-forming galaxies contribute significantly to the reionization process and over what period did this occur? Neither theory nor observations are well-developed in this frontier topic but the first results presented here provide important guidance on how we will use more powerful future facilities.Comment: To appear in `First Light in Universe', Saas-Fee Advanced Course 36, Swiss Soc. Astrophys. Astron. in press. 115 pages, 64 figures (see http://www.astro.caltech.edu/~rse/saas-fee.pdf for hi-res figs.) For lecture ppt files see http://obswww.unige.ch/saas-fee/preannouncement/course_pres/overview_f.htm

Star clusters near and far; tracing star formation across cosmic time

© 2020 Springer-Verlag. The final publication is available at Springer via https://doi.org/10.1007/s11214-020-00690-x.Star clusters are fundamental units of stellar feedback and unique tracers of their host galactic properties. In this review, we will first focus on their constituents, i.e.\ detailed insight into their stellar populations and their surrounding ionised, warm, neutral, and molecular gas. We, then, move beyond the Local Group to review star cluster populations at various evolutionary stages, and in diverse galactic environmental conditions accessible in the local Universe. At high redshift, where conditions for cluster formation and evolution are more extreme, we are only able to observe the integrated light of a handful of objects that we believe will become globular clusters. We therefore discuss how numerical and analytical methods, informed by the observed properties of cluster populations in the local Universe, are used to develop sophisticated simulations potentially capable of disentangling the genetic map of galaxy formation and assembly that is carried by globular cluster populations.Peer reviewedFinal Accepted Versio

Physical Processes in Star Formation

© 2020 Springer-Verlag. The final publication is available at Springer via https://doi.org/10.1007/s11214-020-00693-8.Star formation is a complex multi-scale phenomenon that is of significant importance for astrophysics in general. Stars and star formation are key pillars in observational astronomy from local star forming regions in the Milky Way up to high-redshift galaxies. From a theoretical perspective, star formation and feedback processes (radiation, winds, and supernovae) play a pivotal role in advancing our understanding of the physical processes at work, both individually and of their interactions. In this review we will give an overview of the main processes that are important for the understanding of star formation. We start with an observationally motivated view on star formation from a global perspective and outline the general paradigm of the life-cycle of molecular clouds, in which star formation is the key process to close the cycle. After that we focus on the thermal and chemical aspects in star forming regions, discuss turbulence and magnetic fields as well as gravitational forces. Finally, we review the most important stellar feedback mechanisms.Peer reviewedFinal Accepted Versio

A MODEST review

We present an account of the state of the art in the fields explored by the research community invested in 'Modeling and Observing DEnse STellar systems'. For this purpose, we take as a basis the activities of the MODEST-17 conference, which was held at Charles University, Prague, in September 2017. Reviewed topics include recent advances in fundamental stellar dynamics, numerical methods for the solution of the gravitational N-body problem, formation and evolution of young and old star clusters and galactic nuclei, their elusive stellar populations, planetary systems, and exotic compact objects, with timely attention to black holes of different classes of mass and their role as sources of gravitational waves. Such a breadth of topics reflects the growing role played by collisional stellar dynamics in numerous areas of modern astrophysics. Indeed, in the next decade, many revolutionary instruments will enable the derivation of positions and velocities of individual stars in the Milky Way and its satellites and will detect signals from a range of astrophysical sources in different portions of the electromagnetic and gravitational spectrum, with an unprecedented sensitivity. On the one hand, this wealth of data will allow us to address a number of long-standing open questions in star cluster studies; on the other hand, many unexpected properties of these systems will come to light, stimulating further progress of our understanding of their formation and evolution.Comment: 42 pages; accepted for publication in 'Computational Astrophysics and Cosmology'. We are much grateful to the organisers of the MODEST-17 conference (Charles University, Prague, September 2017). We acknowledge the input provided by all MODEST-17 participants, and, more generally, by the members of the MODEST communit

Machine learning biochemical networks from temporal logic properties

Abstract. One central issue in systems biology is the definition of formal languages for describing complex biochemical systems and their behavior at different levels. The biochemical abstract machine BIOCHAM is based on two formal languages, one rule-based language used for modeling biochemical networks, at three abstraction levels corresponding to three semantics: boolean, concentration and population; and one temporal logic language used for formalizing the biological properties of the system. In this paper, we show how the temporal logic language can be turned into a specification language. We describe two algorithms for inferring reaction rules and kinetic parameter values from a temporal specification formalizing the biological data. Then, with an example of the cell cycle control, we illustrate how these machine learning techniques may be useful to the modeler.

In Silico Modelling and Analysis of Ribosome Kinetics and aa-tRNA Competition

We present a formal analysis of ribosome kinetics using probabilistic model checking and the tool Prism. We compute different parameters of the model, like probabilities of translation errors and average insertion times per codon. The model predicts strong correlation to the quotient of the concentrations of the so-called cognate and near-cognate tRNAs, in accord with experimental findings and other studies. Using piecewise analysis of the model, we are able to give an analytical explanation of this observation