scholarly journals Evolving complexity: how tinkering shapes cells, software and ecological networks

2020 ◽  
Vol 375 (1796) ◽  
pp. 20190325 ◽  
Author(s):  
Ricard Solé ◽  
Sergi Valverde
Keyword(s):  
Biological Networks ◽  
Network Models ◽  
Scale Free ◽  
Philosophical Foundations ◽  
Evolutionary Origins ◽  
Proper Formulation ◽  
Modular Architectures ◽  
The Individual ◽  
Insight Into ◽  
Selection Of

A common trait of complex systems is that they can be represented by means of a network of interacting parts. It is, in fact, the network organization (more than the parts) that largely conditions most higher-level properties, which are not reducible to the properties of the individual parts. Can the topological organization of these webs provide some insight into their evolutionary origins? Both biological and artificial networks share some common architectural traits. They are often heterogeneous and sparse, and most exhibit different types of correlations, such as nestedness, modularity or hierarchical patterns. These properties have often been attributed to the selection of functionally meaningful traits. However, a proper formulation of generative network models suggests a rather different picture. Against the standard selection–optimization argument, some networks reveal the inevitable generation of complex patterns resulting from reuse and can be modelled using duplication–rewiring rules lacking functionality. These give rise to the observed heterogeneous, scale-free and modular architectures. Here, we examine the evidence for tinkering in cellular, technological and ecological webs and its impact in shaping their architecture. Our analysis suggests a serious consideration of the role played by selection as the origin of network topology. Instead, we suggest that the amplification processes associated with reuse might shape these graphs at the topological level. In biological systems, selection forces would take advantage of emergent patterns. This article is part of the theme issue ‘Unifying the essential concepts of biological networks: biological insights and philosophical foundations’.

scholarly journals Quantification and selection of ictogenic zones in epilepsy surgery

2019 ◽  
Author(s):  
Petroula Laiou ◽  
Eleftherios Avramidis ◽  
Marinho A. Lopes ◽  
Eugenio Abela ◽  
Michael Müller ◽  
...  
Keyword(s):  
Computational Models ◽  
Brain Networks ◽  
Network Models ◽  
Combinatorial Problem ◽  
Valuable Insight ◽  
Potential Applicability ◽  
Healthy Functioning ◽  
The Brain ◽  
Insight Into ◽  
Selection Of

AbstractNetwork models of brain dynamics provide valuable insight into the healthy functioning of the brain and how this breaks down in disease. A pertinent example is the use of network models to understand seizure generation (ictogenesis) in epilepsy. Recently, computational models have emerged to aid our understanding of seizures and to predict the outcome of surgical perturbations to brain networks. Such approaches provide the opportunity to quantify the effect of removing regions of tissue from brain networks and thereby search for the optimal resection strategy.Here, we use computational models to elucidate how sets of nodes contribute to the ictogenicity of networks. In small networks we fully elucidate the ictogenicity of all possible sets of nodes and demonstrate that the distribution of ictogenicity across sets depends on network topology. However, the full elucidation is a combinatorial problem that becomes intractable for large networks. Therefore, we develop a global optimisation approach to search for minimal sets of nodes that contribute significantly to ictogenesis. We demonstrate the potential applicability of these methods in practice by identifying optimal sets of nodes to resect in networks derived from 20 individuals who underwent resective surgery for epilepsy.

scholarly journals Shifting levels of ecological network's analysis reveals different system properties

2020 ◽  
Vol 375 (1796) ◽  
pp. 20190326 ◽  
Author(s):  
Nathalie Niquil ◽  
Matilda Haraldsson ◽  
Télesphore Sime-Ngando ◽  
Philippe Huneman ◽  
Stuart R. Borrett
Keyword(s):  
Biological Networks ◽  
General Pattern ◽  
Network Models ◽  
Time Step ◽  
Philosophical Foundations ◽  
Network Analyses ◽  
Planktonic Food ◽  
Node Level ◽  
System Properties ◽  
Level Of Analysis

Network analyses applied to models of complex systems generally contain at least three levels of analyses. Whole-network metrics summarize general organizational features (properties or relationships) of the entire network, while node-level metrics summarize similar organization features but consider individual nodes. The network- and node-level metrics build upon the primary pairwise relationships in the model. As with many analyses, sometimes there are interesting differences at one level that disappear in the summary at another level of analysis. We illustrate this phenomenon with ecosystem network models, where nodes are trophic compartments and pairwise relationships are flows of organic carbon, such as when a predator eats a prey. For this demonstration, we analysed a time-series of 16 models of a lake planktonic food web that describes carbon exchanges within an autumn cyanobacteria bloom and compared the ecological conclusions drawn from the three levels of analysis based on inter-time-step comparisons. A general pattern in our analyses was that the closer the levels are in hierarchy (node versus network, or flow versus node level), the more they tend to align in their conclusions. Our analyses suggest that selecting the appropriate level of analysis, and above all regularly using multiple levels, may be a critical analytical decision. This article is part of the theme issue ‘Unifying the essential concepts of biological networks: biological insights and philosophical foundations'.

Principles of Applied Clinical Pharmacokinetics and Pharmacodynamics in Antiretroviral Therapy

2019 ◽  
pp. 219-224
Author(s):  
Neha Sheth Pandit ◽  
Emily L. Heil
Keyword(s):  
Antiretroviral Therapy ◽  
Patient Treatment ◽  
Pharmacokinetics And Pharmacodynamics ◽  
Basic Principles ◽  
Clinical Pharmacokinetics ◽  
Treatment Regimens ◽  
The Individual ◽  
Insight Into ◽  
Therapeutic Responses ◽  
Selection Of

Upon completion of this chapter, the reader should be able to • Understand the basic principles of applied pharmacokinetics and pharmacodynamics of antiretroviral agents, and apply this knowledge to improve individual patient treatment regimens. Understanding the basic principles of applied clinical pharmacokinetics and pharmacodynamics can help the clinician gain insight into contemporary HIV pharmacotherapy and improve therapeutic responses. This information can be used to improve antiretroviral (ARV) treatment for the individual patient by gaining a fundamental working knowledge of concepts that contribute to the occurrence of drug–drug interactions (DDIs), adverse drug reactions, poor adherence, decreased efficacy, and the selection of viral resistance. These factors, alone or in combination, can lead to treatment failure of antiretroviral therapy (ART) and subsequent progression of HIV disease. This chapter discusses some of the applied clinical pharmacokinetic and pharmacodynamic principles that relate to the treatment of HIV....

Generalized Boolean Networks

2010 ◽  
pp. 429-449 ◽  
Author(s):  
Christian Darabos ◽  
Mario Giacobini ◽  
Marco Tomassini
Keyword(s):  
Biological Networks ◽  
Regulatory Networks ◽  
Dynamical Behavior ◽  
Real Life ◽  
Network Models ◽  
Cell Types ◽  
Boolean Networks ◽  
Genetic Regulatory Networks ◽  
Point Of View ◽  
Scale Free

Random Boolean Networks (RBN) have been introduced by Kauffman more than thirty years ago as a highly simplified model of genetic regulatory networks. This extremely simple and abstract model has been studied in detail and has been shown capable of extremely interesting dynamical behavior. First of all, as some parameters are varied such as the network’s connectivity, or the probability of expressing a gene, the RBN can go through a phase transition, going from an ordered regime to a chaotic one. Kauffman’s suggestion is that cell types correspond to attractors in the RBN phase space, and only those attractors that are short and stable under perturbations will be of biological interest. Thus, according to Kauffman, RBN lying at the edge between the ordered phase and the chaotic phase can be seen as abstract models of genetic regulatory networks. The original view of Kauffman, namely that these models may be useful for understanding real-life cell regulatory networks, is still valid, provided that the model is updated to take into account present knowledge about the topology of real gene regulatory networks, and the timing of events, without loosing its attractive simplicity. According to present data, many biological networks, including genetic regulatory networks, seem, in fact, to be of the scale-free type. From the point of view of the timing of events, standard RBN update their state synchronously. This assumption is open to discussion when dealing with biologically plausible networks. In particular, for genetic regulatory networks, this is certainly not the case: genes seem to be expressed in different parts of the network at different times, according to a strict sequence, which depends on the particular network under study. The expression of a gene depends on several transcription factors, the synthesis of which appear to be neither fully synchronous nor instantaneous. Therefore, we have recently proposed a new, more biologically plausible model. It assumes a scale-free topology of the networks and we define a suitable semi-synchronous dynamics that better captures the presence of an activation sequence of genes linked to the topological properties of the network. By simulating statistical ensembles of networks, we discuss the attractors of the dynamics, showing that they are compatible with theoretical biological network models. Moreover, the model demonstrates interesting scaling abilities as the size of the networks is increased.

scholarly journals Network explanations and explanatory directionality

2020 ◽  
Vol 375 (1796) ◽  
pp. 20190318 ◽  
Author(s):  
Lina Jansson
Keyword(s):  
Biological Networks ◽  
Scientific Explanation ◽  
Network Models ◽  
Causal Models ◽  
Topological Properties ◽  
Theme Issue ◽  
Causal Explanations ◽  
Philosophical Foundations ◽  
Direction Of Causation

Network explanations raise foundational questions about the nature of scientific explanation. The challenge discussed in this article comes from the fact that network explanations are often thought to be non-causal, i.e. they do not describe the dynamical or mechanistic interactions responsible for some behaviour, instead they appeal to topological properties of network models describing the system. These non-causal features are often thought to be valuable precisely because they do not invoke mechanistic or dynamical interactions and provide insights that are not available through causal explanations. Here, I address a central difficulty facing attempts to move away from causal models of explanation; namely, how to recover the directionality of explanation. Within causal models, the directionality of explanation is identified with the direction of causation. This solution is no longer available once we move to non-causal accounts of explanation. I will suggest a solution to this problem that emphasizes the role of conditions of application. In doing so, I will challenge the idea that sui generis mathematical dependencies are the key to understand non-causal explanations. The upshot is a conceptual account of explanation that accommodates the possibility of non-causal network explanations. It also provides guidance for how to evaluate such explanations. This article is part of the theme issue ‘Unifying the essential concepts of biological networks: biological insights and philosophical foundations’.

How missed temporal deadlines influence consumption behavior

2014 ◽  
Vol 31 (5) ◽  
pp. 360-370 ◽  
Author(s):  
Beth Vallen ◽  
Lauren G. Block ◽  
Eric Eisenstein
Keyword(s):  
Affect Regulation ◽  
Consumer Choice ◽  
Behavior Changes ◽  
Start Time ◽  
Content Type ◽  
Consumption Behavior ◽  
Time Usage ◽  
The Individual ◽  
Insight Into ◽  
Selection Of

Purpose – The purpose of this research is to explore how and why consumption behavior changes across time in reference to a temporal deadline, such as a meeting start time or scheduled appointment. Design/methodology/approach – The authors present findings from two experiments that manipulate distance to/from a deadline and assess behavioral intentions and consumer choice, both before a deadline is reached (i.e. the individual is early) and after a deadline has passed (i.e. the individual is late). Findings – Results demonstrate that, while individuals are more likely to refrain from consumption in favor of being on time as a deadline approaches, they are more likely to engage in consumption activities once they have already missed their deadline. Support is shown for an underlying process of affect regulation; when they are late (vs on time), consumers are likely to regulate affect via the selection of more indulgent options. Practical implications – These studies provide insight into the both the beneficial and detrimental nature of deadlines. Further, they provide insight as to how deadlines impact consumer behavior by demonstrating differential patterns of consumption based on whether an individual is early vs late. Originality/value – Documenting the effect of meeting and missing deadlines on consumption contributes to the literature on time usage and offers insights into individuals’ efforts to prioritize multiple activities that conflict due to time constraints.

scholarly journals Polymolybdates and Peroxomolybdates: Candidates for Catalysts in Industry

2014 ◽  
Vol 70 (a1) ◽  
pp. C589-C589
Author(s):  
Wieslaw Lasocha ◽  
Anna Szymanska ◽  
Marcin Oszajca ◽  
Graham Appleby ◽  
Katarzyna Pamin ◽  
...  
Keyword(s):  
Polycrystalline Materials ◽  
Full Understanding ◽  
Variable Size ◽  
Cyclic Hydrocarbons ◽  
Oxidation Of Hydrocarbons ◽  
The Family ◽  
The Individual ◽  
Insight Into ◽  
Selection Of

Progress in catalysis depends on a full understanding of the role of the individual components of catalytic materials. Crystallographic studies offer insight into crystal structure, which enables the rational selection of reagents and better planning of the syntheses of novel materials and catalysts. In this paper we have studied the process of the oxidation of hydrocarbons and terpenes with oxygen from the air. Processes of this type are important in so-called "Green Chemistry." Their application can reduce the amount of environmentally harmful pollutants formed through conventional oxidation based on nitric acid. While investigating the catalytic activity of peroxo- and polymolybdates(VI) in the oxidation of cycloalkanes, we found a number of intriguing relationships. To explain them, we designed, synthesized and solved the crystal structures of the family of new peroxomolybdates, tri-, octa- and pentamolybdates of amines. Both single crystal and polycrystalline materials were investigated using laboratory as well as synchrotron radiation. Next, we used these compounds as catalysts in certain interesting for industry processes (e.g. oxidation of cyclic hydrocarbons). We have concluded that: – The activity of peroxocompounds is enhanced by the coordination of N-oxide groups to Mo atoms. – The activity of anionic polymeric trimolybdates decreases when `surface of polymeric fiber' is blocked by cations. – The anionic layers of pentamolybdates are separated by cations of variable size. The distance between layers plays a role similar to that of the size of channels in zeolites. Summary: Peroxomolybdates and polyoxomolybdates show great prospects for new industrial uses (besides cracking and desulfurization).

Events and festivals in Asia and the Middle East/North Africa (MENA) region

2012 ◽  
Vol 3 (1) ◽  
pp. 4-8 ◽  
Author(s):  
Karin Weber ◽  
Jane Ali‐Knight
Keyword(s):  
Mena Region ◽  
Content Type ◽  
Qualitative Approaches ◽  
Recent Developments ◽  
Individual Contributions ◽  
Key Issues ◽  
The Subject ◽  
The Individual ◽  
Insight Into ◽  
Selection Of

PurposeThis editorial aims to provide a brief overview of recent developments in the events industry in general, and in Asia and the MENA region in particular. The discussion forms a prelude for the individual contributions of this special issue.Design/methodology/approachThe papers cover a variety of different research methods and methodologies including both quantitative and qualitative approaches.FindingsSetting the stage for the selection of papers is a thought‐provoking introduction, followed by six papers that aim to provide insights into key issues by examining pertinent literature, addressing relevant research questions, and providing applied and theoretical outcomes relevant to both academics and practitioners in the event and festival fields. These papers cover the variety, scope and diversity of events in Asia and MENA region, with a mixture of papers that examine event‐specific aspects and those that approach the subject from a broader destination/policy perspective.Originality/valueThe selection of papers are unique as they provide a thorough and extensive insight into the opportunities and challenges facing emergent festival and event destinations in Asia and the MENA region.

scholarly journals Exploring modularity in biological networks

2020 ◽  
Vol 375 (1796) ◽  
pp. 20190316 ◽  
Author(s):  
Maria Serban
Keyword(s):  
Biological Networks ◽  
Network Models ◽  
Exploratory Research ◽  
Systematic Analysis ◽  
Philosophical Foundations ◽  
Theoretical Approaches ◽  
New Directions ◽  
Biology I ◽  
Complementary Set

Network theoretical approaches have shaped our understanding of many different kinds of biological modularity. This essay makes the case that to capture these contributions, it is useful to think about the role of network models in exploratory research. The overall point is that it is possible to provide a systematic analysis of the exploratory functions of network models in bioscientific research. Using two examples from molecular and developmental biology, I argue that often the same modelling approach can perform one or more exploratory functions, such as introducing new directions of research, offering a complementary set of concepts, methods and algorithms for individuating important features of natural phenomena, generating proofs of principle demonstrations and potential explanations for phenomena of interest and enlarging the scope of certain research agendas. This article is part of the theme issue ‘Unifying the essential concepts of biological networks: biological insights and philosophical foundations’.

scholarly journals Personalizing psychological care for chronic cancer-related fatigue: A case study on symptom dynamics.

2021 ◽  
Vol 7 (1) ◽  
pp. 1-13
Author(s):  
Melanie P. J. Schellekens ◽  
Tom I. Bootsma ◽  
Rosalie A. M. Van Woezik ◽  
Marije L. Van der Lee
Keyword(s):  
Mental Healthcare ◽  
Network Models ◽  
Evidence Based ◽  
Psychological Care ◽  
The Past ◽  
Cancer Related Fatigue ◽  
The Moment ◽  
The Individual ◽  
Insight Into

Approximately 25% of cancer patients suffer from chronic cancer-related fatigue (CCRF), which is a complex, multifactorial condition. While there are evidence-based interventions, it remains unclear what treatment works best for the individual patient. Psychological network models can offer a schematic representation of interrelations among fatigue and protective and perpetuating factors for the individual patient. We explored whether feedback based on these individual fatigue networks can help personalize psychological care for CCRF. A 34-year old woman with CCRF was referred to our mental healthcare institute for psycho-oncology. During the waitlist period, she filled out an experience sampling app for 101 days, including five daily assessments of fatigue, pain, mood, activity and fatigue coping. The interplay between items was visualized in network graphs at the moment-level and day-level, which were discussed with the patient. For example, acceptance of fatigue in the past three hours was associated with less hopelessness and less fatigue in the following moment. At the day-level, acceptance was also being associated with less fatigue, less hopelessness, a better mood, and more motivation to do things. The patient recognized these patterns and explained how unexpected waves of fatigue can make her feel hopeless. This started a dialogue on how cultivating acceptance could potentially help her handle the fatigue. The patient would discuss this with her therapist. Feedback based on individual fatigue networks can provide direct insight into how one copes with CCRF and subsequently offer directions for treatment. Further research is needed in order to implement this in clinical practice.

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