null models
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2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Yuliya Shapovalova ◽  
Tom Heskes ◽  
Tjeerd Dijkstra

Abstract Background Understanding the synergetic and antagonistic effects of combinations of drugs and toxins is vital for many applications, including treatment of multifactorial diseases and ecotoxicological monitoring. Synergy is usually assessed by comparing the response of drug combinations to a predicted non-interactive response from reference (null) models. Possible choices of null models are Loewe additivity, Bliss independence and the recently rediscovered Hand model. A different approach is taken by the MuSyC model, which directly fits a generalization of the Hill model to the data. All of these models, however, fit the dose–response relationship with a parametric model. Results We propose the Hand-GP model, a non-parametric model based on the combination of the Hand model with Gaussian processes. We introduce a new logarithmic squared exponential kernel for the Gaussian process which captures the logarithmic dependence of response on dose. From the monotherapeutic response and the Hand principle, we construct a null reference response and synergy is assessed from the difference between this null reference and the Gaussian process fitted response. Statistical significance of the difference is assessed from the confidence intervals of the Gaussian process fits. We evaluate performance of our model on a simulated data set from Greco, two simulated data sets of our own design and two benchmark data sets from Chou and Talalay. We compare the Hand-GP model to standard synergy models and show that our model performs better on these data sets. We also compare our model to the MuSyC model as an example of a recent method on these five data sets and on two-drug combination screens: Mott et al. anti-malarial screen and O’Neil et al. anti-cancer screen. We identify cases in which the HandGP model is preferred and cases in which the MuSyC model is preferred. Conclusion The Hand-GP model is a flexible model to capture synergy. Its non-parametric and probabilistic nature allows it to model a wide variety of response patterns.


2022 ◽  
Vol 82 ◽  
Author(s):  
K. Solis-Lufí ◽  
M. J. Suazo ◽  
M. E. Avila-Salem ◽  
C. Maldonado-Murúa ◽  
H. Aponte ◽  
...  

Abstract One of the biological indicators most used to determine the health of a fluvial ecosystem are the benthic macroinvertebrates. The presence of recurrent species in a wide gradient of latitudes, dominates the biogeographic pattern of the benthic macroinvertebrates in Chilean fresh waters, nevertheless the knowledge on the communitarian ecology of these in the Chilean rivers continues to be scarce. Null models became a powerful statistical tool for describing the ecological mechanisms that drive the structure of an ecological community and the underlying patterns of diversity. The objective of this study was to determine the community structure of benthic invertebrates in the Allipén River by describing their composition, richness and abundance of species through richness models and null models based on presence/absence. The results reveal a high family richness and low diversity, three phyla, five classes, 11 orders and 28 families were identified in the study area during the four seasons of the year. The Arthropoda phylum was the most representative in abundance and richness. Regarding to richness, Trichoptera (7 families) and Diptera (6 families) followed by Ephemeroptera (3 families) were the orders that showed the greatest diversity of families, however, a low diversity with a H’≤ 1.5 nit was registered in the study area. We demonstrated through the null models, the randomization in the species associations corresponding to the three analyzed sites. The information provided here contributes to the understanding of the ecological patterns of the invertebrate communities in the Allipén River, establishing the basis for more complex ecological studies.


2022 ◽  
Vol 12 (1) ◽  
Author(s):  
David N. Koons ◽  
Thomas V. Riecke ◽  
G. Scott Boomer ◽  
Benjamin S. Sedinger ◽  
James S. Sedinger ◽  
...  

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7585
Author(s):  
Cornelia Meckbach ◽  
Sabrina Elsholz ◽  
Caroline Siede ◽  
Imke Traulsen

Sensor technologies, such as the Global Navigation Satellite System (GNSS), produce huge amounts of data by tracking animal locations with high temporal resolution. Due to this high resolution, all animals show at least some co-occurrences, and the pure presence or absence of co-occurrences is not satisfactory for social network construction. Further, tracked animal contacts contain noise due to measurement errors or random co-occurrences. To identify significant associations, null models are commonly used, but the determination of an appropriate null model for GNSS data by maintaining the autocorrelation of tracks is challenging, and the construction is time and memory consuming. Bioinformaticians encounter phylogenetic background and random noise on sequencing data. They estimate this noise directly on the data by using the average product correction procedure, a method applied to information-theoretic measures. Using Global Positioning System (GPS) data of heifers in a pasture, we performed a proof of concept that this approach can be transferred to animal science for social network construction. The approach outputs stable results for up to 30% missing data points, and the predicted associations were in line with those of the null models. The effect of different distance thresholds for contact definition was marginal, but animal activity strongly affected the network structure.


2021 ◽  
Author(s):  
◽  
Danilo Coelho de Almeida

<p>The present study is divided into two parts: Firstly, null models where used to test whether plant communities in a New Zealand forest were assembled deterministically or stochastically. Secondly, a relationship between a plant trait; Leaf Mass per Area (LMA) and environmental conditions was investigated in a New Zealand forest. For the first study abundance of adult species was recorded in thirty 30m x 30m plots at Otari Wilton's Bush. In a subsample of six plots, the abundance of seedling species was also recorded. Null models for species co-occurrence, species richness, species abundance and niche overlap were used in order to establish how plant communities assemble at Otari Wilton's Bush. There was evidence of both determinist and stochasticity in some aspects of the plant community, it appears that seedlings are mainly randomly assembled whereas, determinism appears to be the main driver of community composition for mature trees. Results therefore suggest a pluralistic approach should be used in order to explain plant community patterns at Otari Wilton's Bush. For the second study, of all species observed in the first study only those species found in five or more of the plots were examined. For those species, the height of the two highest individuals was measured. From each individual, six fully exposed leaves were collected and measured. Measurements of environmental conditions were also collected for all plots. Principal component analysis and multiple regression was used to analyse the data. Height related (vertical) trends were observed for three surveyed species such that LMA significantly increased with plant height. Horizontal patterns were observed for two species, and for three species it was not possible to distinguish the association of tree height (vertical) and position along the forest (horizontal) with LMA. Potentially, by including more species in future studies a clearer pattern will be observed. It could also be that different species display different strategies regarding LMA and if so, a study more focused on individual species in isolation may be able to provide more informative explanations.</p>


2021 ◽  
Author(s):  
◽  
Danilo Coelho de Almeida

<p>The present study is divided into two parts: Firstly, null models where used to test whether plant communities in a New Zealand forest were assembled deterministically or stochastically. Secondly, a relationship between a plant trait; Leaf Mass per Area (LMA) and environmental conditions was investigated in a New Zealand forest. For the first study abundance of adult species was recorded in thirty 30m x 30m plots at Otari Wilton's Bush. In a subsample of six plots, the abundance of seedling species was also recorded. Null models for species co-occurrence, species richness, species abundance and niche overlap were used in order to establish how plant communities assemble at Otari Wilton's Bush. There was evidence of both determinist and stochasticity in some aspects of the plant community, it appears that seedlings are mainly randomly assembled whereas, determinism appears to be the main driver of community composition for mature trees. Results therefore suggest a pluralistic approach should be used in order to explain plant community patterns at Otari Wilton's Bush. For the second study, of all species observed in the first study only those species found in five or more of the plots were examined. For those species, the height of the two highest individuals was measured. From each individual, six fully exposed leaves were collected and measured. Measurements of environmental conditions were also collected for all plots. Principal component analysis and multiple regression was used to analyse the data. Height related (vertical) trends were observed for three surveyed species such that LMA significantly increased with plant height. Horizontal patterns were observed for two species, and for three species it was not possible to distinguish the association of tree height (vertical) and position along the forest (horizontal) with LMA. Potentially, by including more species in future studies a clearer pattern will be observed. It could also be that different species display different strategies regarding LMA and if so, a study more focused on individual species in isolation may be able to provide more informative explanations.</p>


NeuroImage ◽  
2021 ◽  
Vol 243 ◽  
pp. 118518
Author(s):  
Raphaël Liégeois ◽  
B.T. Thomas Yeo ◽  
Dimitri Van De Ville

2021 ◽  
pp. 103071
Author(s):  
Shannon P. McPherron ◽  
Will Archer ◽  
Erik R. Otárola-Castillo ◽  
Melissa G. Torquato ◽  
Trevor L. Keevil

2021 ◽  
Author(s):  
Nitin Williams ◽  
Benedetta Toselli ◽  
Felix Siebenhuhner ◽  
Satu Palva ◽  
Gabriele Arnulfo ◽  
...  

Magnetoencephalography (MEG) is used extensively to study functional connectivity (FC) networks of phase-synchronization, but the relationship of these networks to their biophysical substrates is poorly understood. Biophysical Network Models (BNMs) have been used to produce networks corresponding to MEG-derived networks of phase-synchronization, but the roles of inter-regional conduction delays, the structural connectome and dynamics of model of individual brain regions, in obtaining this correspondence remain unknown. In this study, we investigated the roles of conduction delays, the structural connectome, and dynamics of models of individual regions, in obtaining a correspondence between model-generated and MEG-derived networks between left-hemispheric regions. To do this, we compared three BNMs, respectively comprising Wilson-Cowan oscillators interacting with diffusion Magnetic Resonance Imaging (MRI)-based patterns of structural connections through zero delays, constant delays and distance-dependent delays respectively. For the BNM whose networks corresponded most closely to the MEG-derived network, we used comparisons against null models to identify specific features of each model component, e.g. the pattern of connections in the structure connectome, that contributed to the observed correspondence. The Wilson-Cowan zero delays model produced networks with a closer correspondence to the MEG-derived network than those produced by the constant delays model, and the same as those produced by the distance-dependent delays model. Hence, there is no evidence that including conduction delays improves the correspondence between model-generated and MEG-derived networks. Given this, we chose the Wilson-Cowan zero delays model for further investigation. Comparing the Wilson-Cowan zero delays model against null models revealed that both the pattern of structural connections and Wilson-Cowan oscillatory dynamics contribute to the correspondence between model-generated and MEG-derived networks. Our investigations yield insight into the roles of conduction delays, the structural connectome and dynamics of models of individual brain regions, in obtaining a correspondence between model-generated and MEG-derived networks. These findings result in a parsimonious BNM that produces networks corresponding closely to MEG-derived networks of phase-synchronization.


NeuroImage ◽  
2021 ◽  
Vol 236 ◽  
pp. 118052
Author(s):  
Ross D. Markello ◽  
Bratislav Misic
Keyword(s):  

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