1
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Mele M, Covino R, Potestio R. Information-theoretical measures identify accurate low-resolution representations of protein configurational space. SOFT MATTER 2022; 18:7064-7074. [PMID: 36070256 DOI: 10.1039/d2sm00636g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The steadily growing computational power employed to perform molecular dynamics simulations of biological macromolecules represents at the same time an immense opportunity and a formidable challenge. In fact, large amounts of data are produced, from which useful, synthetic, and intelligible information has to be extracted to make the crucial step from knowing to understanding. Here we tackled the problem of coarsening the conformational space sampled by proteins in the course of molecular dynamics simulations. We applied different schemes to cluster the frames of a dataset of protein simulations; we then employed an information-theoretical framework, based on the notion of resolution and relevance, to gauge how well the various clustering methods accomplish this simplification of the configurational space. Our approach allowed us to identify the level of resolution that optimally balances simplicity and informativeness; furthermore, we found that the most physically accurate clustering procedures are those that induce an ultrametric structure of the low-resolution space, consistently with the hypothesis that the protein conformational landscape has a self-similar organisation. The proposed strategy is general and its applicability extends beyond that of computational biophysics, making it a valuable tool to extract useful information from large datasets.
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Affiliation(s)
- Margherita Mele
- Physics Department, University of Trento, via Sommarive, 14 I-38123 Trento, Italy.
| | - Roberto Covino
- Frankfurt Institute for Advanced Studies, 60438 Frankfurt am Main, Germany
| | - Raffaello Potestio
- Physics Department, University of Trento, via Sommarive, 14 I-38123 Trento, Italy.
- INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, I-38123 Trento, Italy
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2
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Static and dynamic methods in social network analysis reveal the association patterns of desert-dwelling giraffe. Behav Ecol Sociobiol 2022. [DOI: 10.1007/s00265-022-03167-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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3
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Primate Infectious Disease Ecology: Insights and Future Directions at the Human-Macaque Interface. THE BEHAVIORAL ECOLOGY OF THE TIBETAN MACAQUE 2020. [PMCID: PMC7123869 DOI: 10.1007/978-3-030-27920-2_13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Global population expansion has increased interactions and conflicts between humans and nonhuman primates over shared ecological space and resources. Such ecological overlap, along with our shared evolutionary histories, makes human-nonhuman primate interfaces hot spots for the acquisition and transmission of parasites. In this chapter, we bring to light the importance of human-macaque interfaces in particular as hot spots for infectious disease ecological and epidemiological assessments. We first outline the significance and broader objectives behind research related to the subfield of primate infectious disease ecology and epidemiology. We then reveal how members of the genus Macaca, being among the most socioecologically flexible and invasive of all primate taxa, live under varying degrees of overlap with humans in anthropogenic landscapes. Thus, human-macaque interfaces may favor the bidirectional exchange of parasites. We then review studies that have isolated various types of parasites at human-macaque interfaces, using information from the Global Mammal Parasite Database (GMPD: http://www.mammalparasites.org/). Finally, we elaborate on avenues through which the implementation of both novel conceptual frameworks (e.g., Coupled Systems, One Health) and quantitative network-based approaches (e.g., social and bipartite networks, agent-based modeling) may potentially address some of the critical gaps in our current knowledge of infectious disease ecology at human-primate interfaces.
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4
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Guan J, Hsieh F, Koehl P. DCG++: A data-driven metric for geometric pattern recognition. PLoS One 2019; 14:e0217838. [PMID: 31170208 PMCID: PMC6553753 DOI: 10.1371/journal.pone.0217838] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2018] [Accepted: 05/20/2019] [Indexed: 11/19/2022] Open
Abstract
Clustering large and complex data sets whose partitions may adopt arbitrary shapes remains a difficult challenge. Part of this challenge comes from the difficulty in defining a similarity measure between the data points that captures the underlying geometry of those data points. In this paper, we propose an algorithm, DCG++ that generates such a similarity measure that is data-driven and ultrametric. DCG++ uses Markov Chain Random Walks to capture the intrinsic geometry of data, scans possible scales, and combines all this information using a simple procedure that is shown to generate an ultrametric. We validate the effectiveness of this similarity measure within the context of clustering on synthetic data with complex geometry, on a real-world data set containing segmented audio records of frog calls described by mel-frequency cepstral coefficients, as well as on an image segmentation problem. The experimental results show a significant improvement on performance with the DCG-based ultrametric compared to using an empirical distance measure.
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Affiliation(s)
- Jiahui Guan
- Department of Statistics, University of California Davis, Davis, CA, United States of America
| | - Fushing Hsieh
- Department of Statistics, University of California Davis, Davis, CA, United States of America
| | - Patrice Koehl
- Department of Computer Science and Genome Center, University of California Davis, Davis, CA, United States of America
- * E-mail:
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5
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Unraveling the Regional Specificities of Malbec Wines from Mendoza, Argentina, and from Northern California. AGRONOMY-BASEL 2019. [DOI: 10.3390/agronomy9050234] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
This study explores the relationships between chemical and sensory characteristics of wines in connection with their regions of production. The objective is to identify whether such characteristics are significant enough to serve as signatures of a terroir for wines, thereby supporting the concept of regionality. We argue that the relationships between characteristics and regions of production for the set of wines under study are rendered complicated by possible non-linear relationships between the characteristics themselves. Consequently, we propose a new approach for performing the analysis of the wine data that relies on these relationships instead of trying to circumvent them. This new approach follows two steps: We first cluster the measurements for each characteristic (chemical, or sensory) independently. We then assign a distance between two features to be the mutual entropy of the clustering results they generate. The set of characteristics is then clustered using this distance measure. The result of this clustering is a set of sub-groups of characteristics, such that two characteristics in the same group carry similar, i.e., synergetic information with respect to the wines under study. Those wines are then analyzed separately on the different sub groups of features. We have used this method to analyze the similarities and differences between Malbec wines from Argentina and California, as well as the similarities and differences between sub-regions of those two main wine producing countries. We report detection of groups of features that characterize the origins of the different wines included in the study. We note stronger evidence of regionality for Argentinian Malbec wines than for Californian wines, at least for the sub regions of production included in this study.
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6
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Destoumieux-Garzón D, Mavingui P, Boetsch G, Boissier J, Darriet F, Duboz P, Fritsch C, Giraudoux P, Le Roux F, Morand S, Paillard C, Pontier D, Sueur C, Voituron Y. The One Health Concept: 10 Years Old and a Long Road Ahead. Front Vet Sci 2018; 5:14. [PMID: 29484301 PMCID: PMC5816263 DOI: 10.3389/fvets.2018.00014] [Citation(s) in RCA: 261] [Impact Index Per Article: 43.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2017] [Accepted: 01/22/2018] [Indexed: 02/05/2023] Open
Abstract
Over the past decade, a significant increase in the circulation of infectious agents was observed. With the spread and emergence of epizootics, zoonoses, and epidemics, the risks of pandemics became more and more critical. Human and animal health has also been threatened by antimicrobial resistance, environmental pollution, and the development of multifactorial and chronic diseases. This highlighted the increasing globalization of health risks and the importance of the human-animal-ecosystem interface in the evolution and emergence of pathogens. A better knowledge of causes and consequences of certain human activities, lifestyles, and behaviors in ecosystems is crucial for a rigorous interpretation of disease dynamics and to drive public policies. As a global good, health security must be understood on a global scale and from a global and crosscutting perspective, integrating human health, animal health, plant health, ecosystems health, and biodiversity. In this study, we discuss how crucial it is to consider ecological, evolutionary, and environmental sciences in understanding the emergence and re-emergence of infectious diseases and in facing the challenges of antimicrobial resistance. We also discuss the application of the "One Health" concept to non-communicable chronic diseases linked to exposure to multiple stresses, including toxic stress, and new lifestyles. Finally, we draw up a list of barriers that need removing and the ambitions that we must nurture for the effective application of the "One Health" concept. We conclude that the success of this One Health concept now requires breaking down the interdisciplinary barriers that still separate human and veterinary medicine from ecological, evolutionary, and environmental sciences. The development of integrative approaches should be promoted by linking the study of factors underlying stress responses to their consequences on ecosystem functioning and evolution. This knowledge is required for the development of novel control strategies inspired by environmental mechanisms leading to desired equilibrium and dynamics in healthy ecosystems and must provide in the near future a framework for more integrated operational initiatives.
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Affiliation(s)
- Delphine Destoumieux-Garzón
- CNRS, Interactions Hôtes-Pathogènes-Environnements (IHPE), UMR5244, Université de Perpignan Via Domitia, Université de Montpellier, Ifremer, Montpellier, France
| | - Patrick Mavingui
- Université de La Reunion, UMR PIMIT (Processus Infectieux en Milieu Insulaire Tropical), INSERM 1187, CNRS 9192, IRD 249, Sainte-Clotilde, La Réunion, France
- UMR Ecologie Microbienne, CNRS, INRA, VetAgro Sup, Claude Bernard University Lyon 1, Université de Lyon, Villeurbanne, France
| | - Gilles Boetsch
- UMI 3189 “Environnement, Santé, Sociétés”, Faculty of Medicine, Cheikh Anta Diop University, Dakar-Fann, Senegal
- Téssékéré International Human-Environment Observatory Labex DRIIM, CNRS and Cheikh Anta Diop University, Dakar, Senegal
| | - Jérôme Boissier
- Université de Perpignan Via Domitia, Interactions Hôtes-Pathogènes-Environnements (IHPE), UMR5244, CNRS, Ifremer, Université de Montpellier, Perpignan, France
| | - Frédéric Darriet
- Institut de Recherche pour le Développement, Maladies Infectieuses et Vecteurs, Ecologie, Génétique, Evolution et Contrôle (MIVEGEC), IRD, CNRS, Université de Montpellier, Montpellier, France
| | - Priscilla Duboz
- UMI 3189 “Environnement, Santé, Sociétés”, Faculty of Medicine, Cheikh Anta Diop University, Dakar-Fann, Senegal
- Téssékéré International Human-Environment Observatory Labex DRIIM, CNRS and Cheikh Anta Diop University, Dakar, Senegal
| | - Clémentine Fritsch
- Laboratoire Chrono-Environnement, UMR 6249 CNRS/Université Bourgogne Franche-Comté Usc, INRA, Besançon, France
| | - Patrick Giraudoux
- Laboratoire Chrono-Environnement, UMR 6249 CNRS/Université Bourgogne Franche-Comté Usc, INRA, Besançon, France
- Institut Universitaire de France, Paris, France
| | - Frédérique Le Roux
- Ifremer, Unité Physiologie Fonctionnelle des Organismes Marins, Plouzané, France
| | - Serge Morand
- Institut des Sciences de l’Évolution (ISEM), UMR 5554, CNRS, Université de Montpellier, CIRAD, IRD, EPHE, Montpellier, France
- UPR ASTRE, CIRAD, Montpellier, France
| | - Christine Paillard
- Laboratoire des Sciences de l’Environnement Marin (LEMAR), Institut Universitaire Européen de la Mer, Université de Bretagne Occidentale, UMR 6539, CNRS, UBO, IRD, Ifremer, Plouzané, France
| | - Dominique Pontier
- Laboratoire de Biométrie et Biologie Evolutive UMR5558, CNRS, Université de Lyon, Université Claude Bernard Lyon 1, Villeurbanne, France
- LabEx Ecofect, Eco-Evolutionary Dynamics of Infectious Diseases, University of Lyon, Lyon, France
| | - Cédric Sueur
- Université de Strasbourg, CNRS, IPHC, UMR 7178, Strasbourg, France
| | - Yann Voituron
- Laboratoire d’Ecologie des Hydrosystèmes Naturels et Anthropisés, UMR 5023, CNRS, Université Claude Bernard Lyon1, Université de Lyon, Villeurbanne, France
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7
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Balasubramaniam K, Beisner B, Guan J, Vandeleest J, Fushing H, Atwill E, McCowan B. Social network community structure and the contact-mediated sharing of commensal E. coli among captive rhesus macaques ( Macaca mulatta). PeerJ 2018; 6:e4271. [PMID: 29372120 PMCID: PMC5775753 DOI: 10.7717/peerj.4271] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2017] [Accepted: 12/27/2017] [Indexed: 01/17/2023] Open
Abstract
In group-living animals, heterogeneity in individuals' social connections may mediate the sharing of microbial infectious agents. In this regard, the genetic relatedness of individuals' commensal gut bacterium Escherichia coli may be ideal to assess the potential for pathogen transmission through animal social networks. Here we use microbial phylogenetics and population genetics approaches, as well as host social network reconstruction, to assess evidence for the contact-mediated sharing of E. coli among three groups of captively housed rhesus macaques (Macaca mulatta), at multiple organizational scales. For each group, behavioral data on grooming, huddling, and aggressive interactions collected for a six-week period were used to reconstruct social network communities via the Data Cloud Geometry (DCG) clustering algorithm. Further, an E. coli isolate was biochemically confirmed and genotypically fingerprinted from fecal swabs collected from each macaque. Population genetics approaches revealed that Group Membership, in comparison to intrinsic attributes like age, sex, and/or matriline membership of individuals, accounted for the highest proportion of variance in E. coli genotypic similarity. Social network approaches revealed that such sharing was evident at the community-level rather than the dyadic level. Specifically, although we found no links between dyadic E. coli similarity and social contact frequencies, similarity was significantly greater among macaques within the same social network communities compared to those across different communities. Moreover, tests for one of our study-groups confirmed that E. coli isolated from macaque rectal swabs were more genotypically similar to each other than they were to isolates from environmentally deposited feces. In summary, our results suggest that among frequently interacting, spatially constrained macaques with complex social relationships, microbial sharing via fecal-oral, social contact-mediated routes may depend on both individuals' direct connections and on secondary network pathways that define community structure. They lend support to the hypothesis that social network communities may act as bottlenecks to contain the spread of infectious agents, thereby encouraging disease control strategies to focus on multiple organizational scales. Future directions includeincreasing microbial sampling effort per individual to better-detect dyadic transmission events, and assessments of the co-evolutionary links between sociality, infectious agent risk, and host immune function.
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Affiliation(s)
- Krishna Balasubramaniam
- Department of Population Health & Reproduction, School of Veterinary Medicine, University of California, Davis, CA, United States of America
| | - Brianne Beisner
- Department of Population Health & Reproduction, School of Veterinary Medicine, University of California, Davis, CA, United States of America
- Brain, Mind & Behavior, California National Primate Research Center, University of California, Davis, CA, United States of America
| | - Jiahui Guan
- Department of Statistics, University of California, Davis, CA, United States of America
| | - Jessica Vandeleest
- Department of Population Health & Reproduction, School of Veterinary Medicine, University of California, Davis, CA, United States of America
- Brain, Mind & Behavior, California National Primate Research Center, University of California, Davis, CA, United States of America
| | - Hsieh Fushing
- Department of Statistics, University of California, Davis, CA, United States of America
| | - Edward Atwill
- Department of Population Health & Reproduction, School of Veterinary Medicine, University of California, Davis, CA, United States of America
| | - Brenda McCowan
- Department of Population Health & Reproduction, School of Veterinary Medicine, University of California, Davis, CA, United States of America
- Brain, Mind & Behavior, California National Primate Research Center, University of California, Davis, CA, United States of America
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8
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Bennitt E, Bonyongo MC, Harris S. Cape buffalo (Syncerus caffer caffer) social dynamics in a flood-pulsed environment. Behav Ecol 2017. [DOI: 10.1093/beheco/arx138] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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9
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Hsieh F, Hsueh CH, Heitkamp C, Matthews M. Integrative Inferences on Pattern Geometries of Grapes Grown under Water Stress and Their Resulting Wines. PLoS One 2016; 11:e0160621. [PMID: 27508416 PMCID: PMC4980011 DOI: 10.1371/journal.pone.0160621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2014] [Accepted: 07/22/2016] [Indexed: 11/18/2022] Open
Abstract
Multiple datasets of two consecutive vintages of replicated grape and wines from six different deficit irrigation regimes are characterized and compared. The process consists of four temporal-ordered signature phases: harvest field data, juice composition, wine composition before bottling and bottled wine. A new computing paradigm and an integrative inferential platform are developed for discovering phase-to-phase pattern geometries for such characterization and comparison purposes. Each phase is manifested by a distinct set of features, which are measurable upon phase-specific entities subject to the common set of irrigation regimes. Throughout the four phases, this compilation of data from irrigation regimes with subsamples is termed a space of media-nodes, on which measurements of phase-specific features were recoded. All of these collectively constitute a bipartite network of data, which is then normalized and binary coded. For these serial bipartite networks, we first quantify patterns that characterize individual phases by means of a new computing paradigm called "Data Mechanics". This computational technique extracts a coupling geometry which captures and reveals interacting dependence among and between media-nodes and feature-nodes in forms of hierarchical block sub-matrices. As one of the principal discoveries, the holistic year-factor persistently surfaces as the most inferential factor in classifying all media-nodes throughout all phases. This could be deemed either surprising in its over-arching dominance or obvious based on popular belief. We formulate and test pattern-based hypotheses that confirm such fundamental patterns. We also attempt to elucidate the driving force underlying the phase-evolution in winemaking via a newly developed partial coupling geometry, which is designed to integrate two coupling geometries. Such partial coupling geometries are confirmed to bear causal and predictive implications. All pattern inferences are performed with respect to a profile of energy distributions sampled from network bootstrapping ensembles conforming to block-structures specified by corresponding hypotheses.
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Affiliation(s)
- Fushing Hsieh
- Department of Statistics, University of California at Davis, Davis, CA, United States of America
- * E-mail:
| | - Chih-Hsin Hsueh
- Department of Statistics, University of California at Davis, Davis, CA, United States of America
| | - Constantin Heitkamp
- Department of Viticulture and Enology, University of California at Davis, Davis, CA, United States of America
| | - Mark Matthews
- Department of Viticulture and Enology, University of California at Davis, Davis, CA, United States of America
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10
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Fushing H, Hsueh CH, Heitkamp C, Matthews MA, Koehl P. Unravelling the geometry of data matrices: effects of water stress regimes on winemaking. J R Soc Interface 2016; 12:20150753. [PMID: 26468072 DOI: 10.1098/rsif.2015.0753] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
A new method is proposed for unravelling the patterns between a set of experiments and the features that characterize those experiments. The aims are to extract these patterns in the form of a coupling between the rows and columns of the corresponding data matrix and to use this geometry as a support for model testing. These aims are reached through two key steps, namely application of an iterative geometric approach to couple the metric spaces associated with the rows and columns, and use of statistical physics to generate matrices that mimic the original data while maintaining their inherent structure, thereby providing the basis for hypothesis testing and statistical inference. The power of this new method is illustrated on the study of the impact of water stress conditions on the attributes of 'Cabernet Sauvignon' Grapes, Juice, Wine and Bottled Wine from two vintages. The first step, named data mechanics, de-convolutes the intrinsic effects of grape berries and wine attributes due to the experimental irrigation conditions from the extrinsic effects of the environment. The second step provides an analysis of the associations of some attributes of the bottled wine with characteristics of either the matured grape berries or the resulting juice, thereby identifying statistically significant associations between the juice pH, yeast assimilable nitrogen, and sugar content and the bottled wine alcohol level.
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Affiliation(s)
- Hsieh Fushing
- Department of Statistics, University of California, Davis, CA 95616, USA
| | - Chih-Hsin Hsueh
- Department of Statistics, University of California, Davis, CA 95616, USA
| | - Constantin Heitkamp
- Department of Viticulture and Enology, University of California, Davis, CA 95616, USA
| | - Mark A Matthews
- Department of Viticulture and Enology, University of California, Davis, CA 95616, USA
| | - Patrice Koehl
- Department of Computer Science and Genome Center, University of California, Davis, CA 95616, USA
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11
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Borgeaud C, Sosa S, Bshary R, Sueur C, van de Waal E. Intergroup Variation of Social Relationships in Wild Vervet Monkeys: A Dynamic Network Approach. Front Psychol 2016; 7:915. [PMID: 27445890 PMCID: PMC4914564 DOI: 10.3389/fpsyg.2016.00915] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2015] [Accepted: 06/02/2016] [Indexed: 11/30/2022] Open
Abstract
Social network analysis is a powerful tool that enables us to describe and quantify relationships between individuals. So far most of the studies rely on the analyses of various network snapshots, but do not capture changes over time. Here we use a stochastic actor-oriented model (SAOM) to test both the structure and the dynamics of relationships of three groups of wild vervet monkeys. We found that triadic closure (i.e., the friend of a friend is a friend) was significant in all three groups while degree popularity (i.e., the willingness to associate with individuals with high degree of connections) was significant in only two groups (AK, BD). The structure and dynamics of relationships according to the attributes of sex, matrilineand age differed significantly among groups. With respect to the structure, when analyzing the likelihood of bonds according to the different attributes, we found that individuals associate themselves preferably to individuals of the same sex only in two groups (AK, NH), while significant results for attachment to individuals of the same matriline were found also in two groups (BD, NH). With respect to the dynamics, i.e., how quickly relationships are modified, we found in two groups (AK, BD) that females' relationships were more prone to variation than males.' In the BD group, relationships within high-ranking matrilines were less stable than low-ranking ones while in the NH group, juveniles' relationships were also less stable than adults' ones. The intergroup variation indicates that establishing species-specific or even population specific characteristics of social networks for later between-species comparisons will be challenging. Although, such variation could also indicate some methodological issue, we are quite confident that data was collected similarly within the different groups. Our study therefore provides a potential new method to quantify social complexity according to natural demographic variation.
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Affiliation(s)
- Christèle Borgeaud
- Laboratory of Eco-Ethology, Institute of Biology, University of NeuchâtelNeuchâtel, Switzerland; Inkawu Vervet Project, Mawana Game ReserveKwaZulu Natal, South Africa
| | - Sebastian Sosa
- Adaptive Behavior and Interaction Research Group, University of Barcelona Barcelona, Spain
| | - Redouan Bshary
- Laboratory of Eco-Ethology, Institute of Biology, University of NeuchâtelNeuchâtel, Switzerland; Inkawu Vervet Project, Mawana Game ReserveKwaZulu Natal, South Africa
| | - Cédric Sueur
- Département Ecologie, Physiologie et Ethologie, Centre National de la Recherche ScientifiqueStrasbourg, France; Institut Pluridisciplinaire Hubert Curien, Université de StrasbourgStrasbourg, France
| | - Erica van de Waal
- Inkawu Vervet Project, Mawana Game ReserveKwaZulu Natal, South Africa; Anthropological Institute and Museum, University of ZurichZurich, Switzerland
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12
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McCowan B, Beisner B, Bliss-Moreau E, Vandeleest J, Jin J, Hannibal D, Hsieh F. Connections Matter: Social Networks and Lifespan Health in Primate Translational Models. Front Psychol 2016; 7:433. [PMID: 27148103 PMCID: PMC4841009 DOI: 10.3389/fpsyg.2016.00433] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2015] [Accepted: 03/11/2016] [Indexed: 12/25/2022] Open
Abstract
Humans live in societies full of rich and complex relationships that influence health. The ability to improve human health requires a detailed understanding of the complex interplay of biological systems that contribute to disease processes, including the mechanisms underlying the influence of social contexts on these biological systems. A longitudinal computational systems science approach provides methods uniquely suited to elucidate the mechanisms by which social systems influence health and well-being by investigating how they modulate the interplay among biological systems across the lifespan. In the present report, we argue that nonhuman primate social systems are sufficiently complex to serve as model systems allowing for the development and refinement of both analytical and theoretical frameworks linking social life to health. Ultimately, developing systems science frameworks in nonhuman primate models will speed discovery of the mechanisms that subserve the relationship between social life and human health.
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Affiliation(s)
- Brenda McCowan
- Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, DavisDavis, CA, USA; California National Primate Research Center, University of California, DavisDavis, CA, USA
| | - Brianne Beisner
- Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, DavisDavis, CA, USA; California National Primate Research Center, University of California, DavisDavis, CA, USA
| | - Eliza Bliss-Moreau
- Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, DavisDavis, CA, USA; California National Primate Research Center, University of California, DavisDavis, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, DavisDavis, CA, USA
| | - Jessica Vandeleest
- Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, DavisDavis, CA, USA; California National Primate Research Center, University of California, DavisDavis, CA, USA
| | - Jian Jin
- California National Primate Research Center, University of California, Davis Davis, CA, USA
| | - Darcy Hannibal
- Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, DavisDavis, CA, USA; California National Primate Research Center, University of California, DavisDavis, CA, USA
| | - Fushing Hsieh
- Department of Statistics, University of California, Davis Davis, CA, USA
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13
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VanderWaal KL, Obanda V, Omondi GP, McCowan B, Wang H, Fushing H, Isbell LA. The “strength of weak ties” and helminth parasitism in giraffe social networks. Behav Ecol 2016. [DOI: 10.1093/beheco/arw035] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023] Open
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14
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Computing and Learning Year-Round Daily Patterns of Hourly Wind Speed and Direction and Their Global Associations with Meteorological Factors. ENTROPY 2015. [DOI: 10.3390/e17085784] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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15
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An Adaptive Spectral Clustering Algorithm Based on the Importance of Shared Nearest Neighbors. ALGORITHMS 2015. [DOI: 10.3390/a8020177] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Pasquaretta C, Levé M, Claidière N, van de Waal E, Whiten A, MacIntosh AJJ, Pelé M, Bergstrom ML, Borgeaud C, Brosnan SF, Crofoot MC, Fedigan LM, Fichtel C, Hopper LM, Mareno MC, Petit O, Schnoell AV, di Sorrentino EP, Thierry B, Tiddi B, Sueur C. Social networks in primates: smart and tolerant species have more efficient networks. Sci Rep 2014; 4:7600. [PMID: 25534964 PMCID: PMC4274513 DOI: 10.1038/srep07600] [Citation(s) in RCA: 65] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2014] [Accepted: 12/03/2014] [Indexed: 11/13/2022] Open
Abstract
Network optimality has been described in genes, proteins and human communicative networks. In the latter, optimality leads to the efficient transmission of information with a minimum number of connections. Whilst studies show that differences in centrality exist in animal networks with central individuals having higher fitness, network efficiency has never been studied in animal groups. Here we studied 78 groups of primates (24 species). We found that group size and neocortex ratio were correlated with network efficiency. Centralisation (whether several individuals are central in the group) and modularity (how a group is clustered) had opposing effects on network efficiency, showing that tolerant species have more efficient networks. Such network properties affecting individual fitness could be shaped by natural selection. Our results are in accordance with the social brain and cultural intelligence hypotheses, which suggest that the importance of network efficiency and information flow through social learning relates to cognitive abilities.
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Affiliation(s)
- Cristian Pasquaretta
- 1] Université de Strasbourg, Institut Pluridisciplinaire Hubert Curien, Strasbourg, France [2] Centre National de la Recherche Scientifique, Département Ecologie, Physiologie et Ethologie, Strasbourg, France
| | - Marine Levé
- 1] Université de Strasbourg, Institut Pluridisciplinaire Hubert Curien, Strasbourg, France [2] Centre National de la Recherche Scientifique, Département Ecologie, Physiologie et Ethologie, Strasbourg, France [3] Ecole Normale Supérieure, Paris, France
| | - Nicolas Claidière
- University of St Andrews, Centre for Social Learning and Cognitive Evolution, School of Psychology &Neuroscience, St Andrews, United Kingdom
| | - Erica van de Waal
- 1] University of St Andrews, Centre for Social Learning and Cognitive Evolution, School of Psychology &Neuroscience, St Andrews, United Kingdom [2] Inkawu Vervet Project, Mawana Game Reserve, Swart Mfolozi, KwaZulu Natal, South Africa
| | - Andrew Whiten
- 1] University of St Andrews, Centre for Social Learning and Cognitive Evolution, School of Psychology &Neuroscience, St Andrews, United Kingdom [2] Inkawu Vervet Project, Mawana Game Reserve, Swart Mfolozi, KwaZulu Natal, South Africa
| | - Andrew J J MacIntosh
- 1] Kyoto University, Primate Research Institute, Center for International Collaboration and Advanced Studies in Primatology Kanrin 41-2, Inuyama, Aichi, Japan 484-8506 [2] Kyoto University Wildlife Research Center, 2-24 Tanaka-Sekiden-cho, Sakyo, Kyoto, Japan 606-8203
| | - Marie Pelé
- Ethobiosciences, Research and Consultancy Agency in Animal Wellbeing and Behaviour, Strasbourg, France
| | | | - Christèle Borgeaud
- 1] Inkawu Vervet Project, Mawana Game Reserve, Swart Mfolozi, KwaZulu Natal, South Africa [2] University of Neuchâtel, Institute of Biology, Neuchâtel, Switzerland
| | - Sarah F Brosnan
- Department of Psychology &Language Research Center, Georgia State University, Atlanta, GA, 30302, USA
| | - Margaret C Crofoot
- 1] Department of Anthropology, University of California, Davis, 1 Shields Ave., Davis, CA 95616, U.S.A. [2] Smithsonian Tropical Research Institute, Ancon, Panama City, Panama
| | | | - Claudia Fichtel
- 1] Behavioral Ecology and Sociobiology Unit, German Primate Center, Göttingen, Germany [2] Courant Research Centre "Evolution of Social Behaviour", University of Göttingen, Germany
| | - Lydia M Hopper
- 1] Department of Psychology &Language Research Center, Georgia State University, Atlanta, GA, 30302, USA [2] Lester E. Fisher Center for the Study and Conservation of Apes, Lincoln Park Zoo, Chicago, IL, 60614, USA [3] Michale E. Keeling Center for Comparative Medicine and Research, UT MD Anderson Cancer Center, Bastrop, TX, 78602, USA
| | - Mary Catherine Mareno
- Michale E. Keeling Center for Comparative Medicine and Research, UT MD Anderson Cancer Center, Bastrop, TX, 78602, USA
| | - Odile Petit
- 1] Université de Strasbourg, Institut Pluridisciplinaire Hubert Curien, Strasbourg, France [2] Centre National de la Recherche Scientifique, Département Ecologie, Physiologie et Ethologie, Strasbourg, France [3] Unit of Social Ecology, CP231, Université libre de Bruxelles, Campus Plaine, Bd du triomphe, 1050 Brussels, Belgium
| | - Anna Viktoria Schnoell
- Courant Research Centre "Evolution of Social Behaviour", University of Göttingen, Germany
| | | | - Bernard Thierry
- 1] Université de Strasbourg, Institut Pluridisciplinaire Hubert Curien, Strasbourg, France [2] Centre National de la Recherche Scientifique, Département Ecologie, Physiologie et Ethologie, Strasbourg, France
| | - Barbara Tiddi
- 1] Cognitive Ethology Laboratory, German Primate Center, Goettingen, Germany [2] Courant Research Centre "Evolution of Social Behaviour", University of Göttingen, Germany
| | - Cédric Sueur
- 1] Université de Strasbourg, Institut Pluridisciplinaire Hubert Curien, Strasbourg, France [2] Centre National de la Recherche Scientifique, Département Ecologie, Physiologie et Ethologie, Strasbourg, France [3] Unit of Social Ecology, CP231, Université libre de Bruxelles, Campus Plaine, Bd du triomphe, 1050 Brussels, Belgium
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Fushing H, Chen C, Liu SY, Koehl P. Bootstrapping on undirected binary networks via statistical mechanics. JOURNAL OF STATISTICAL PHYSICS 2014; 156:823-842. [PMID: 25071295 PMCID: PMC4111278 DOI: 10.1007/s10955-014-1043-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
We propose a new method inspired from statistical mechanics for extracting geometric information from undirected binary networks and generating random networks that conform to this geometry. In this method an undirected binary network is perceived as a thermodynamic system with a collection of permuted adjacency matrices as its states. The task of extracting information from the network is then reformulated as a discrete combinatorial optimization problem of searching for its ground state. To solve this problem, we apply multiple ensembles of temperature regulated Markov chains to establish an ultrametric geometry on the network. This geometry is equipped with a tree hierarchy that captures the multiscale community structure of the network. We translate this geometry into a Parisi adjacency matrix, which has a relative low energy level and is in the vicinity of the ground state. The Parisi adjacency matrix is then further optimized by making block permutations subject to the ultrametric geometry. The optimal matrix corresponds to the macrostate of the original network. An ensemble of random networks is then generated such that each of these networks conforms to this macrostate; the corresponding algorithm also provides an estimate of the size of this ensemble. By repeating this procedure at different scales of the ultrametric geometry of the network, it is possible to compute its evolution entropy, i.e. to estimate the evolution of its complexity as we move from a coarse to a ne description of its geometric structure. We demonstrate the performance of this method on simulated as well as real data networks.
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Affiliation(s)
- Hsieh Fushing
- Department of Statistics, University of California, Davis, 1 Shields Ave, Davis, CA 95616
| | - Chen Chen
- Department of Statistics, University of California, Davis, 1 Shields Ave, Davis, CA 95616
| | - Shan-Yu Liu
- Department of Statistics, University of California, Davis, 1 Shields Ave, Davis, CA 95616
| | - Patrice Koehl
- Department of Computer Science, University of California, Davis, 1 Shields Ave, Davis, CA 95616
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Fushing H, Chen C. Data mechanics and coupling geometry on binary bipartite networks. PLoS One 2014; 9:e106154. [PMID: 25170903 PMCID: PMC4149528 DOI: 10.1371/journal.pone.0106154] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2014] [Accepted: 08/01/2014] [Indexed: 11/18/2022] Open
Abstract
We quantify the notion of pattern and formalize the process of pattern discovery under the framework of binary bipartite networks. Patterns of particular focus are interrelated global interactions between clusters on its row and column axes. A binary bipartite network is built into a thermodynamic system embracing all up-and-down spin configurations defined by product-permutations on rows and columns. This system is equipped with its ferromagnetic energy ground state under Ising model potential. Such a ground state, also called a macrostate, is postulated to congregate all patterns of interest embedded within the network data in a multiscale fashion. A new computing paradigm for indirect searching for such a macrostate, called Data Mechanics, is devised by iteratively building a surrogate geometric system with a pair of nearly optimal marginal ultrametrics on row and column spaces. The coupling measure minimizing the Gromov-Wasserstein distance of these two marginal geometries is also seen to be in the vicinity of the macrostate. This resultant coupling geometry reveals multiscale block pattern information that characterizes multiple layers of interacting relationships between clusters on row and on column axes. It is the nonparametric information content of a binary bipartite network. This coupling geometry is then demonstrated to shed new light and bring resolution to interaction issues in community ecology and in gene-content-based phylogenetics. Its implied global inferences are expected to have high potential in many scientific areas.
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Affiliation(s)
- Hsieh Fushing
- Department of Statistics, University of California Davis, Davis, California, United States of America
- * E-mail:
| | - Chen Chen
- Department of Statistics, University of California Davis, Davis, California, United States of America
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Chen CP, Fushing H, Atwill R, Koehl P. biDCG: a new method for discovering global features of DNA microarray data via an iterative re-clustering procedure. PLoS One 2014; 9:e102445. [PMID: 25047553 PMCID: PMC4105625 DOI: 10.1371/journal.pone.0102445] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2013] [Accepted: 06/19/2014] [Indexed: 02/02/2023] Open
Abstract
Biclustering techniques have become very popular in cancer genetics studies, as they are tools that are expected to connect phenotypes to genotypes, i.e. to identify subgroups of cancer patients based on the fact that they share similar gene expression patterns as well as to identify subgroups of genes that are specific to these subtypes of cancer and therefore could serve as biomarkers. In this paper we propose a new approach for identifying such relationships or biclusters between patients and gene expression profiles. This method, named biDCG, rests on two key concepts. First, it uses a new clustering technique, DCG-tree [Fushing et al, PLos One, 8, e56259 (2013)] that generates ultrametric topological spaces that capture the geometries of both the patient data set and the gene data set. Second, it optimizes the definitions of bicluster membership through an iterative two-way reclustering procedure in which patients and genes are reclustered in turn, based respectively on subsets of genes and patients defined in the previous round. We have validated biDCG on simulated and real data. Based on the simulated data we have shown that biDCG compares favorably to other biclustering techniques applied to cancer genomics data. The results on the real data sets have shown that biDCG is able to retrieve relevant biological information.
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Affiliation(s)
- Chia-Pei Chen
- Department of Statistics, University of California Davis, Davis, California, United States of America
| | - Hsieh Fushing
- Department of Statistics, University of California Davis, Davis, California, United States of America
| | - Rob Atwill
- Department of Population, Health and Reproduction/Vet Med Extension, University of California Davis, Davis, California, United States of America
| | - Patrice Koehl
- Department of Computer Science and Genome Center, University of California Davis, Davis, California, United States of America
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