V. Anne Smith - researchr alias

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Viewing Publication 1 - 14 from 14

2022

Bayesian networks as a novel tool to enhance interpretability and predictive power of ecological modelsEdwin Hui, Richard Stafford, Iain M. Matthews, V. Anne Smith. ecoi, 68:101539, 2022. [doi]

Practical application of a Bayesian network approach to poultry epigenetics and stressEmiliano A. Videla Rodriguez, Fábio Pértille, Carlos Guerrero-Bosagna, John B. O. Mitchell, Per Jensen, V. Anne Smith. bmcbi, 23(1):261, 2022. [doi]

2019

BayesPiles: Visualisation Support for Bayesian Network Structure LearningAthanasios Vogogias, Jessie Kennedy, Daniel W. Archambault, Benjamin Bach, V. Anne Smith, Hannah Currant. tist, 10(1), 2019. [doi]

2016

MLCut: Exploring Multi-Level Cuts in Dendrograms for Biological DataAthanasios Vogogias, Jessie Kennedy, Daniel W. Archambault, V. Anne Smith, Hannah Currant. tpcg 2016: 1-8 [doi]

2014

Inference of Circadian Regulatory NetworksMarco Grzegorczyk, Andrej Aderhold, V. Anne Smith, Dirk Husmeier. iwbbio 2014: 1001-1014 [doi]

2013

Reconstructing ecological networks with hierarchical Bayesian regression and Mondrian processesAndrej Aderhold, Dirk Husmeier, V. Anne Smith. aistats 2013: 75-84 [doi]

2012

Hierarchical Bayesian models in ecology: Reconstructing species interaction networks from non-homogeneous species abundance dataAndrej Aderhold, Dirk Husmeier, Jack J. Lennon, Colin M. Beale, V. Anne Smith. ecoi, 11:55-64, 2012. [doi]

2010

Causal pattern recovery from neural spike train data using the Snap Shot ScoreChristoph Echtermeyer, Tom V. Smulders, V. Anne Smith. jcns, 29(1-2):231-252, 2010. [doi]

Revealing Structure of Complex Biological Systems Using Bayesian NetworksV. Anne Smith. In Ernesto Estrada, Maria Fox, Desmond J. Higham, Gian-Luca Oppo, editors, Network Science - Complexity in Nature and Technology. pages 185-204, Springer, 2010. [doi]

2008

Evolving an Agent-Based Model to Probe Behavioral Rules in Flocks of CowbirdsV. Anne Smith. alife 2010: 561-568 [doi]

2006

Computational Inference of Neural Information Flow NetworksV. Anne Smith, Jing Yu, Tom V. Smulders, Alexander J. Hartemink, Erich D. Jarvis. ploscb, 2(11), 2006. [doi]

2004

Advances to Bayesian network inference for generating causal networks from observational biological dataJing Yu, V. Anne Smith, Paul P. Wang, Alexander J. Hartemink, Erich D. Jarvis. bioinformatics, 20(18):3594-3603, 2004. [doi]

2003

Influence of Network Topology and Data Collection on Network InferenceV. Anne Smith, Erich D. Jarvis, Alexander J. Hartemink. psb 2003: 164-175 [doi]

2002

Evaluating functional network inference using simulations of complex biological systemsV. Anne Smith, Erich D. Jarvis, Alexander J. Hartemink. ismb 2002: 216-224

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