Nikita A. Sakhanenko

According to our database, Nikita A. Sakhanenko authored at least 28 papers between 2003 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

<i>ApoE</i> Modifier Alleles for Alzheimer's Disease Discovered by Information Theory Dependency Measures: MIST Software Package.

Andrew Banman, Nikita A. Sakhanenko, James Kunert-Graf, David J. Galas

J. Comput. Biol., March, 2023

2021

Toward an Information Theory of Quantitative Genetics.

David J. Galas, James Kunert-Graf, Lisa Uechi, Nikita A. Sakhanenko

J. Comput. Biol., 2021

Optimized permutation testing for information theoretic measures of multi-gene interactions.

James M. Kunert-Graf, Nikita A. Sakhanenko, David J. Galas

BMC Bioinform., 2021

2020

Partial Information Decomposition and the Information Delta: A Geometric Unification Disentangling Non-Pairwise Information.

James Kunert-Graf, Nikita A. Sakhanenko, David J. Galas

Entropy, 2020

2019

Multivariate Analysis of Data Sets with Missing Values: An Information Theory-Based Reliability Function.

Lisa Uechi, David J. Galas, Nikita A. Sakhanenko

J. Comput. Biol., 2019

Symmetries among Multivariate Information Measures Explored Using Möbius Operators.

David J. Galas, Nikita A. Sakhanenko

Entropy, 2019

2017

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis.

Nikita A. Sakhanenko, James Kunert-Graf, David J. Galas

J. Comput. Biol., 2017

Complexity and Vulnerability Analysis of the <i>C. Elegans</i> Gap Junction Connectome.

James Kunert-Graf, Nikita A. Sakhanenko, David J. Galas

Entropy, 2017

Expansion of the Kullback-Leibler Divergence, and a New Class of Information Metrics.

David J. Galas, T. Gregory Dewey, James Kunert-Graf, Nikita A. Sakhanenko

Axioms, 2017

2016

Unifying formalism for multivariate information-related measures: Möbius operators on subset lattices.

David J. Galas, Nikita A. Sakhanenko

CoRR, 2016

2015

Biological Data Analysis as an Information Theory Problem: Multivariable Dependence Measures and the Shadows Algorithm.

Nikita A. Sakhanenko, David J. Galas

J. Comput. Biol., 2015

2014

Describing the Complexity of Systems: Multivariable "Set Complexity" and the Information Basis of Systems Biology.

David J. Galas, Nikita A. Sakhanenko, Alexander Skupin, Tomasz M. Ignac

J. Comput. Biol., 2014

2013

Describing the complexity of systems: Multi-variable "set complexity" and hypergraphs

David J. Galas, Nikita A. Sakhanenko, Alexander Skupin, Tomasz M. Ignac

CoRR, 2013

On Lattices and the Dualities of Information Measures.

David J. Galas, Nikita A. Sakhanenko, Benjamin Keller

CoRR, 2013

2012

Probabilistic Logic Methods and Some Applications to Biology and Medicine.

Nikita A. Sakhanenko, David J. Galas

J. Comput. Biol., 2012

Relations between the set-complexity and the structure of graphs and their sub-graphs.

Tomasz M. Ignac, Nikita A. Sakhanenko, David J. Galas

EURASIP J. Bioinform. Syst. Biol., 2012

Complexity of networks II: The set complexity of edge-colored graphs.

Tomasz M. Ignac, Nikita A. Sakhanenko, David J. Galas

Complex., 2012

2011

Complexity of networks I: The set-complexity of binary graphs.

Nikita A. Sakhanenko, David J. Galas

Complex., 2011

2010

Model Failure and Context Switching Using Logic-Based Stochastic Models.

Nikita A. Sakhanenko, George F. Luger

J. Comput. Sci. Technol., 2010

Markov Logic Networks in the Analysis of Genetic Data.

Nikita A. Sakhanenko, David J. Galas

J. Comput. Biol., 2010

2009

Predictions and Diagnostics in Experimental Data Using Support Vector Regression.

Nikita A. Sakhanenko, George F. Luger, Hanna E. Makaruk, David B. Holtkamp

Int. J. Artif. Intell. Tools, 2009

2008

A New Approach to Model-Based Diagnosis Using Probabilistic Logic.

Nikita A. Sakhanenko, Roshan Rammohan, George F. Luger, Carl R. Stern

Proceedings of the Twenty-First International Florida Artificial Intelligence Research Society Conference, 2008

2007

A Context-Partitioned Stochastic Modeling System with Causally Informed Context Management and Model Induction.

Nikita A. Sakhanenko, Roshan Rammohan, George F. Luger, Carl R. Stern

Proceedings of the 3rd Indian International Conference on Artificial Intelligence, 2007

Managing Dynamic Contexts Using Failure-Driven Stochastic Models.

Nikita A. Sakhanenko, George F. Luger, Carl R. Stern

Proceedings of the Twentieth International Florida Artificial Intelligence Research Society Conference, 2007

2006

Application of Support Vector Regression to Interpolation of Sparse Shock Physics Data Sets

Nikita A. Sakhanenko, George F. Luger, Hanna E. Makaruk, David B. Holtkamp

CoRR, 2006

2005

Understanding physics from interconnected data

Nikita A. Sakhanenko, Hanna E. Makaruk

CoRR, 2005

Systematic Method for Path-Complete White Box Testing

Hanna E. Makaruk, Robert Owczarek, Nikita A. Sakhanenko

CoRR, 2005

2003

Automatic Generation of Generalization Lemmas for Proving Properties of Tail-Recursive Definitions.

Deepak Kapur, Nikita A. Sakhanenko

Proceedings of the Theorem Proving in Higher Order Logics, 16th International Conference, 2003