scholarly journals Ecological networks: Pursuing the shortest path, however narrow and crooked

2018 ◽  
Author(s):  
Andrea Costa ◽  
Ana M. Martín González ◽  
Katell Guizien ◽  
Andrea M. Doglioli ◽  
José María Gómez ◽  
...  
Keyword(s):  
Best Practices ◽  
Evolutionary Biology ◽  
Shortest Paths ◽  
Ecological Networks ◽  
Interaction Networks ◽  
Centrality Measures ◽  
Compact Representation ◽  
Sufficient Information ◽  
Ecological Data ◽  
Important Nodes

Representing data as networks cuts across all sub-disciplines in ecology and evolutionary biology. Besides providing a compact representation of the interconnections between agents, network analysis allows the identification of especially important nodes, according to various metrics that often rely on the calculation of the shortest paths connecting any two nodes. While the interpretation of a shortest paths is straightforward in binary, unweighted networks, whenever weights are reported, the calculation could yield unexpected results. We analyzed 129 studies of ecological networks published in the last decade and making use of shortest paths, and discovered a methodological inaccuracy related to the edge weights used to calculate shortest paths (and related centrality measures), particularly in interaction networks. Specifically, 49% of the studies do not report sufficient information on the calculation to allow their replication, and 61% of the studies on weighted networks may contain errors in how shortest paths are calculated. Using toy models and empirical ecological data, we show how to transform the data prior to calculation and illustrate the pitfalls that need to be avoided. We conclude by proposing a five-point check-list to foster best-practices in the calculation and reporting of centrality measures in ecology and evolution studies.

scholarly journals Ecological networks: Pursuing the shortest path, however narrow and crooked

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Andrea Costa ◽  
Ana M. Martín González ◽  
Katell Guizien ◽  
Andrea M. Doglioli ◽  
José María Gómez ◽  
...  
Keyword(s):  
Best Practices ◽  
Evolutionary Biology ◽  
Shortest Paths ◽  
Ecological Networks ◽  
Interaction Networks ◽  
Centrality Measures ◽  
Compact Representation ◽  
Sufficient Information ◽  
Ecological Data ◽  
Important Nodes

AbstractRepresenting data as networks cuts across all sub-disciplines in ecology and evolutionary biology. Besides providing a compact representation of the interconnections between agents, network analysis allows the identification of especially important nodes, according to various metrics that often rely on the calculation of the shortest paths connecting any two nodes. While the interpretation of a shortest paths is straightforward in binary, unweighted networks, whenever weights are reported, the calculation could yield unexpected results. We analyzed 129 studies of ecological networks published in the last decade that use shortest paths, and discovered a methodological inaccuracy related to the edge weights used to calculate shortest paths (and related centrality measures), particularly in interaction networks. Specifically, 49% of the studies do not report sufficient information on the calculation to allow their replication, and 61% of the studies on weighted networks may contain errors in how shortest paths are calculated. Using toy models and empirical ecological data, we show how to transform the data prior to calculation and illustrate the pitfalls that need to be avoided. We conclude by proposing a five-point check-list to foster best-practices in the calculation and reporting of centrality measures in ecology and evolution studies.

scholarly journals Phylogenetic paleoecology: macroecology within an evolutionary framework

Paleobiology ◽  
2021 ◽  
Vol 47 (2) ◽  
pp. 171-177
Author(s):  
James C. Lamsdell ◽  
Curtis R. Congreve
Keyword(s):  
Species Diversity ◽  
Spatial Variation ◽  
Geographic Distribution ◽  
Evolutionary Biology ◽  
Phylogenetic Signal ◽  
Evolutionary Rates ◽  
The Other ◽  
Ecological Data ◽  
Temporal And Spatial Variation ◽  
Temporal And Spatial

The burgeoning field of phylogenetic paleoecology (Lamsdell et al. 2017) represents a synthesis of the related but differently focused fields of macroecology (Brown 1995) and macroevolution (Stanley 1975). Through a combination of the data and methods of both disciplines, phylogenetic paleoecology leverages phylogenetic theory and quantitative paleoecology to explain the temporal and spatial variation in species diversity, distribution, and disparity. Phylogenetic paleoecology is ideally situated to elucidate many fundamental issues in evolutionary biology, including the generation of new phenotypes and occupation of previously unexploited environments; the nature of relationships among character change, ecology, and evolutionary rates; determinants of the geographic distribution of species and clades; and the underlying phylogenetic signal of ecological selectivity in extinctions and radiations. This is because phylogenetic paleoecology explicitly recognizes and incorporates the quasi-independent nature of evolutionary and ecological data as expressed in the dual biological hierarchies (Eldredge and Salthe 1984; Congreve et al. 2018; Fig. 1), incorporating both as covarying factors rather than focusing on one and treating the other as error within the dataset.

scholarly journals mangal - making ecological network analysis simple

2014 ◽  
Author(s):  
Timothée E Poisot ◽  
Benjamin Baiser ◽  
Jennifer A Dunne ◽  
Sonia Kéfi ◽  
Francois Massol ◽  
...  
Keyword(s):  
Network Analysis ◽  
R Package ◽  
Ecological Networks ◽  
Ecological Interactions ◽  
Ecological Network ◽  
Ecological Data ◽  
Meta Data ◽  
Ecological Network Analysis ◽  
Analysis Process ◽  
Access Data

The study of ecological networks is severely limited by (i) the difficulty to access data, (ii) the lack of a standardized way to link meta-data with interactions, and (iii) the disparity of formats in which ecological networks themselves are represented. To overcome these limitations, we conceived a data specification for ecological networks. We implemented a database respecting this standard, and released a R package ( `rmangal`) allowing users to programmatically access, curate, and deposit data on ecological interactions. In this article, we show how these tools, in conjunctions with other frameworks for the programmatic manipulation of open ecological data, streamlines the analysis process, and improves eplicability and reproducibility of ecological networks studies.

scholarly journals MODELING OF EMERGENCY EVACUATION IN BUILDING FIRE

2020 ◽  
Vol XLIII-B4-2020 ◽  
pp. 321-327 ◽  
Author(s):  
H. Bayat ◽  
M. R. Delavar ◽  
W. Barghi ◽  
S. A. EslamiNezhad ◽  
P. Hanachi ◽  
...  
Keyword(s):  
Indoor Environment ◽  
Shortest Paths ◽  
Fire Risk ◽  
Emergency Evacuation ◽  
Information Modeling ◽  
Sufficient Information ◽  
Dijkstra Algorithm ◽  
Rescue Workers ◽  
Building Information ◽  
Emergency Exit

Abstract. One of the main problems of rescue workers in confrontation of fired complex buildings is the lack of sufficient information about the building indoor environment and their emergency exit ways. Building information modeling (BIM) is a database for building a 3D model of building information to create a 3D building geometry network model. This paper has implemented some GIS and BIM integration analyses to determine the shortest and safest paths to people under fire risk and simulate their movement in the building. Plasco building was a multi-story shop in Tehran which has been fired in 2017 and destroyed. This paper attempts to simulate the firefighting and rescue operations in Plasco Building using an integration of BIM and GIS. There is no detailed information about the building and the fire incident, therefore the developed BIM and corresponding geometric network might differ slightly. The shortest and safest paths to the exit door or windows where the fire ladders are located are computed and analyzed. As a result of 15 scenarios developed in this paper, it was found that at 87% of the cases, the safest paths for the emergency exit of the people at risk were longer than the shortest paths. This study has evaluated different scenarios for the shortest and safest paths using Dijkstra algorithm considering different origins and destination points in the 3D indoor environment to assist the rescue operations.

scholarly journals Multiple perspective centrality measures based on facility location problem under inter-group competitive environment

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Takayasu Fushimi ◽  
Seiya Okubo ◽  
Kazumi Saito
Keyword(s):  
Facility Location ◽  
Location Problem ◽  
Facility Location Problem ◽  
Closeness Centrality ◽  
Centrality Measures ◽  
Spatial Network ◽  
Multiple Perspectives ◽  
Cooperative Relationships ◽  
Important Nodes ◽  
New Facility

Abstract In this study, we propose novel centrality measures considering multiple perspectives of nodes or node groups based on the facility location problem on a spatial network. The conventional centrality exclusively quantifies the global properties of each node in a network such as closeness and betweenness, and extracts nodes with high scores as important nodes. In the context of facility placement on a network, it is desirable to place facilities at nodes with high accessibility from residents, that is, nodes with a high score in closeness centrality. It is natural to think that such a property of a node changes when the situation changes. For example, in a situation where there are no existing facilities, it is expected that the demand of residents will be satisfied by opening a new facility at the node with the highest accessibility, however, in a situation where there exist some facilities, it is necessary to open a new facility some distance from the existing facilities. Furthermore, it is natural to consider that the concept of closeness differs depending on the relationship with existing facilities, cooperative relationships and competitive relationships. Therefore, we extend a concept of centrality so as to considers the situation where one or more nodes have already been selected belonging to one of some groups. In this study, we propose two measures based on closeness centrality and betweenness centrality as behavior models of people on a spatial network. From our experimental evaluations using actual urban street network data, we confirm that the proposed method, which introduces the viewpoints of each group, shows that there is a difference in the important nodes of each group viewpoint, and that the new store location can be predicted more accurately.

scholarly journals Fitness, Extrinsic Complexity and Informing Science

10.28945/3668 ◽  
2017 ◽  
Vol 20 ◽  
pp. 037-061
Author(s):  
Grandon Gill ◽  
Matthew Mullarkey
Keyword(s):  
Best Practices ◽  
Evolutionary Biology ◽  
Resistance To Change ◽  
Academic Research ◽  
Future Research ◽  
Science Field ◽  
Rigorous Approach ◽  
Individual Effects ◽  
Research Stream ◽  
Definition Of

Aim/Purpose We establish a conceptually rigorous definition for the widely used but loosely defined term “fitness”. We then tie this definition to complexity, highlighting a number of important implications for the informing science transdiscipline. Background As informing science increasingly incorporates concepts of fitness and complexity in its research stream, rigorous discussion and definition of both terms is essential to effective communication. Methodology Our analysis consists principally of a synthesis of past work in the informing science field that incorporates concepts from evolutionary biology, economics and management. Contribution We provide a rigorous approach to defining fitness and introduce the construct “extrinsic complexity”, as a measure of the amount of information required to predict fitness, to more fully differentiate this form of complexity from other complexity constructs. We draw a number of conclusions regarding how behaviors under low and high extrinsic complexity will differ. Findings High extrinsic complexity environments are likely to produce behaviors that include resistance to change, imitation, turbulence and inequality. Recommendations for Practitioners As extrinsic complexity grows, effective search for problem solutions will increasingly dominate employing recommended solutions of “best practices”. Recommendation for Researchers As extrinsic complexity grows, research tools that rely on decomposing individual effects and hypothesis testing become increasingly unreliable. Impact on Society We raise concerns about society’s continuing investment in academic research that discounts the extrinsic complexity of the domains under study. Future Research We highlight a need for research to operationalize the concepts of fitness and complexity in practice.

Measures and metrics

2018 ◽  
Author(s):  
Mark Newman
Keyword(s):  
Network Structure ◽  
Similarity Measures ◽  
Clustering Coefficient ◽  
Centrality Measures ◽  
Degree Centrality ◽  
Eigenvector Centrality ◽  
Structural Balance ◽  
Important Nodes

This chapter describes the measures and metrics that are used to quantify network structure. The chapter starts with a discussion of centrality measures, which are used to identify central or important nodes in networks. Measures discussed include degree centrality, eigenvector centrality, PageRank, closeness, and betweenness. This is followed by a discussion of groupings of nodes like cliques and components, transitivity measures including the clustering coefficient, structural balance in networks, similarity measures, and assortative mixing.

scholarly journals An integrative methodology based on protein-protein interaction networks for identification and functional annotation of disease-relevant genes applied to channelopathies

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Milagros Marín ◽  
Francisco J. Esteban ◽  
Hilario Ramírez-Rodrigo ◽  
Eduardo Ros ◽  
María José Sáez-Lara
Keyword(s):  
Protein Interaction ◽  
Clinical Manifestations ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Centrality Measures ◽  
Protein Protein Interaction ◽  
Network Analyses ◽  
Complex Group ◽  
Heterogeneous Datasets ◽  
Protein Protein Interaction Networks

Abstract Background Biologically data-driven networks have become powerful analytical tools that handle massive, heterogeneous datasets generated from biomedical fields. Protein-protein interaction networks can identify the most relevant structures directly tied to biological functions. Functional enrichments can then be performed based on these structural aspects of gene relationships for the study of channelopathies. Channelopathies refer to a complex group of disorders resulting from dysfunctional ion channels with distinct polygenic manifestations. This study presents a semi-automatic workflow using protein-protein interaction networks that can identify the most relevant genes and their biological processes and pathways in channelopathies to better understand their etiopathogenesis. In addition, the clinical manifestations that are strongly associated with these genes are also identified as the most characteristic in this complex group of diseases. Results In particular, a set of nine representative disease-related genes was detected, these being the most significant genes in relation to their roles in channelopathies. In this way we attested the implication of some voltage-gated sodium (SCN1A, SCN2A, SCN4A, SCN4B, SCN5A, SCN9A) and potassium (KCNQ2, KCNH2) channels in cardiovascular diseases, epilepsies, febrile seizures, headache disorders, neuromuscular, neurodegenerative diseases or neurobehavioral manifestations. We also revealed the role of Ankyrin-G (ANK3) in the neurodegenerative and neurobehavioral disorders as well as the implication of these genes in other systems, such as the immunological or endocrine systems. Conclusions This research provides a systems biology approach to extract information from interaction networks of gene expression. We show how large-scale computational integration of heterogeneous datasets, PPI network analyses, functional databases and published literature may support the detection and assessment of possible potential therapeutic targets in the disease. Applying our workflow makes it feasible to spot the most relevant genes and unknown relationships in channelopathies and shows its potential as a first-step approach to identify both genes and functional interactions in clinical-knowledge scenarios of target diseases. Methods An initial gene pool is previously defined by searching general databases under a specific semantic framework. From the resulting interaction network, a subset of genes are identified as the most relevant through the workflow that includes centrality measures and other filtering and enrichment databases.

scholarly journals Two betweenness centrality measures based on Randomized Shortest Paths

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Ilkka Kivimäki ◽  
Bertrand Lebichot ◽  
Jari Saramäki ◽  
Marco Saerens
Keyword(s):  
Betweenness Centrality ◽  
Shortest Paths ◽  
Centrality Measures
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