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Data from: Fundamental activity constraints lead to specific interpretations of the connectome
负责人:
关键词:
cortex;Neurons;Neural networks;Network analysis;System instability;connectome;macaque;Single neuron function;Membrane potential;Simulation and modeling;mean-field theory
DOI:
doi:10.5061/dryad.vn342
摘要:
network models of spiking neurons are necessarily underconstrained even if experimental data on brain connectivity are incorporated to the best of our knowledge
Data from: System-level insights into the cellular interactome of a non-model organism: inferring, modelling and analysing functional gene network
负责人:
关键词:
Glycine max
DOI:
doi:10.5061/dryad.0rv1m
摘要:
and defects, and covering different slices of biological information. Functional gene network (FGN), a consolidated interaction network that models fuzzy
network
负责人:
关键词:
Block Choleski decomposition;Block system;Helmert-blocking;Insertion of new observations;Large geodetic networks
DOI:
doi:10.5061/dryad.t23n3
摘要:
The Helmert-blocking technique is a common approach to adjust large geodetic networks like Europeans and Brazilians. The technique is based upon
Data from: Predicting species occurrences with habitat network models
负责人:
关键词:
connectivity;cost surface;habitat network;Hyla arborea;network topology;cost surface;species occurrence;Holocene;habitat suitability
DOI:
doi:10.5061/dryad.sc818d5
摘要:
), and the position of the patch in the habitat network topology (nt) all influence occurrence-state. Existing models are data demanding or consider only local
Data from: What can interaction webs tell us about species roles?
负责人:
关键词:
food web;Mytilus californianus;Mussel Bed;rocky intertidal;Modern
DOI:
doi:10.5061/dryad.39jv1
摘要:
The group model is a useful tool to understand broad-scale patterns of interaction in a network, but it has previously been limited in use
Data from: Neural modularity helps organisms evolve to learn new skills without forgetting old
负责人:
关键词:
catastrophic forgetting evolutionary algorithm artificial neural network neural modularity
DOI:
doi:10.5061/dryad.s38n5
摘要:
by evolving modular neural networks. Modularity intuitively should reduce learning interference between tasks by separating functionality into physically
Data from: Experimentally verified parameter sets for modelling heterogeneous neocortical pyramidal-cell populations
负责人:
关键词:
Wistar rat;pyramidal neurons;dynamic IV method;Neocortex;single neuron modelling;reduced neuron models
DOI:
doi:10.5061/dryad.d30k7
摘要:
Models of neocortical networks are increasingly including the diversity of excitatory and inhibitory neuronal classes. Significant variability
Data from: The evolution of generalized reciprocity on social interaction networks
负责人:
van Doorn, G. Sander
关键词:
Behavior Sociality Social networks Population Structure Cooperation Models/Simulations
DOI:
doi:10.5061/dryad.tr588488
摘要:
reover, the evolutionary stability of cooperation is enhanced by a modular network structure. Communities of reciprocal altruists are protected ag
Data from: Scale-dependent genetic structure of the Idaho giant salamander (Dicamptodon aterrimus) in stream networks
负责人:
关键词:
scale dependence;stream networks;Genetic structure;Dispersal;Dicamptodon aterrimus;Amphibians;Population Genetics - Empirical
DOI:
doi:10.5061/dryad.1187
摘要:
. This consistent architecture also makes stream networks useful for testing general models of population genetic structure and the scaling of gene flow. We examine
Data from: Context-dependency and anthropogenic effects on individual plant-frugivore networks
负责人:
Miguel, Maria Florencia
关键词:
ecological networks intrapopulation heterogeneity land uses
DOI:
doi:10.5061/dryad.1n755
摘要:
of individuals within populations. Exponential random graph models (ERGMs) examine the global structure of networks by allowing the inclusion of specific node

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