Alexander Statnikov
Ph.D. in Biomedical Informatics
Main Curriculum Vitae Publications Presentations Software Personal
Books
  • Guyon I, Aliferis CF, Cooper GF, Elisseeff A, Pellet JP, Spirtes P, Statnikov A. Challenges in Causality. Volume 1: Causation and Prediction Challenge. (In press) Brookline, Massachusetts: Microtome Publishing, 2009.
Book Chapters
  • Guyon I, Aliferis CF, Cooper GF, Elisseeff A, Pellet JP, Spirtes P, Statnikov A. Causality Workbench. In Causality in the Sciences. Edited by Illari PM, Russo F and Williamson J. (In press) Oxford University Press, 2010.
  • Statnikov A, Tsamardinos I, Brown LE, Aliferis CF. Causal Explorer: A Matlab Library of Algorithms for Causal Discovery and Variable Selection for Classification. In Challenges in Causality. Volume 1: Causation and Prediction Challenge. Edited by Guyon I, Aliferis CF, Cooper GF, Elisseeff A, Pellet JP, Spirtes P and Statnikov A. (In press) Brookline, Massachusetts: Microtome Publishing, 2009.
Journal Papers
  • Aliferis CF, Statnikov A, Tsamardinos I, Schildcrout JS, Shepherd BE, Harrell FE. Factors Influencing the Statistical Power of Complex Data Analysis Protocols for Molecular Signature Development from Microarray Data. PLoS ONE, 2009; 4(3): e4922.
  • Fananapazir N, Statnikov A, Aliferis CF. The FAST-AIMS Clinical Mass Spectrometry Analysis System. Advances in Bioinformatics, 2009.
  • Aliferis CF, Statnikov A, Tsamardinos I, Mani S, Koutsoukos X. Local Causal and Markov Blanket Induction Algorithms for Causal Discovery and Feature Selection for Classification. Part I: Algorithms and Empirical Evaluation. Accepted to the Journal of Machine Learning Research, 2009.
  • Aliferis CF, Statnikov A, Tsamardinos I, Mani S, Koutsoukos X. Local Causal and Markov Blanket Induction Algorithms for Causal Discovery and Feature Selection for Classification. Part II: Analysis and Extensions. Accepted to the Journal of Machine Learning Research, 2009.
  • Statnikov A, Wang L, Aliferis CF. A Comprehensive Comparison of Random Forests and Support Vector Machines for Microarray-Based Cancer Classification. BMC Bioinformatics, 2008; 9:319.
  • Statnikov A, Li C, Aliferis CF. A Statistical Reappraisal of the Findings of an Esophageal Cancer Genome-Wide Association Study. Cancer Research, 2008; 68: 3074-3075.
  • Statnikov A, Li C, Aliferis CF. Effects of Environment, Genetics and Data Analysis Pitfalls in an Esophageal Cancer Genome-Wide Association Study. PLoS ONE, 2007; 2(9): e958.
  • Aliferis CF, Statnikov A, Tsamardinos I. Challenges in the Analysis of Mass-Throughput Data: A Technical Commentary from the Perspective of Statistical Machine Learning. Cancer Informatics. 2006; 2: 133-162.
  • Aphinyanaphongs Y, Statnikov A, Aliferis CF. A Comparison of Citation Metrics to Machine Learning Filters for the Identification of High Quality MEDLINE Documents. Journal of the American Medical Informatics Association. 2006 Jul-Aug; 13: 446-455.
  • Levy S, Statnikov A, Aliferis CF. Biomarker Selection from High-Dimensionality Data. Pharmaceutical Discovery. 2005 Microarray Supplement, 2005 Sep; 37-44.
  • Statnikov A, Tsamardinos I, Dosbayev Y, Aliferis CF. GEMS: A System for Automated Cancer Diagnosis and Biomarker Discovery from Microarray Gene Expression Data. International Journal of Medical Informatics. 2005 Aug; 74(7-8): 493-501.
  • Statnikov A, Aliferis CF, Tsamardinos I, Hardin D, Levy S. A Comprehensive Evaluation of Multicategory Classification Methods for Microarray Gene Expression Cancer Diagnosis. Bioinformatics. 2005 Mar; 21(5): 631-43.
  • Aphinyanaphongs Y, Tsamardinos I, Statnikov A, Hardin D, Aliferis CF. Text Categorization Models for High-Quality Article Retrieval in Internal Medicine. Journal of the American Medical Informatics Association. 2005 Mar-Apr; 12(2): 207-16.
Papers in Conference Proceedings
  • Guyon I, Aliferis CF, Cooper GF, Elisseeff A, Pellet JP, Spirtes P, Statnikov A. Design and Analysis of the Causation and Prediction Challenge. Accepted to the Journal of Machine Learning Research Workshop and Conference Proceeding, Volume 3: Causation ad Prediction Challenge (WCCI 2008), 2008.
  • Statnikov A, Aliferis CF. Are Random Forests Better than Support Vector Machines for Microarray-Based Cancer Classification? AMIA Annual Symposium, 2007.
  • Statnikov A, Hardin D, Aliferis CF. Using SVM Weight-Based Methods to Identify Causally Relevant and Non-Causally Relevant Variables. Neural Information Processing Systems (NIPS) 2006 Workshop on Causality and Feature Selection, 2006.
  • Tsamardinos I, Statnikov A, Brown LE, Aliferis CF. Generating Realistic Large Bayesian Networks by Tiling. 19th International Florida Artificial Intelligence Research Society (FLAIRS) Conference, 2006.
  • Duda S, Aliferis CF, Miller R, Statnikov A, Johnson K. Extracting Drug-Drug Interaction Articles from MEDLINE to Improve the Content of Drug Databases. AMIA Annual Symposium, 2005.
  • Statnikov A, Aliferis CF, Tsamardinos I. Methods for Multi-Category Cancer Diagnosis from Gene Expression Data: A Comprehensive Evaluation to Inform Decision Support System Development. Medinfo, 2004. (Gold Medal in the Student Paper Competition)
  • Aliferis CF, Tsamardinos I, Statnikov A. HITON: A Novel Markov Blanket Algorithm for Optimal Variable Selection. AMIA Annual Symposium, 2003.
  • Tsamardinos I, Aliferis CF, Statnikov A. Time and Sample Efficient Discovery of Markov Blankets and Direct Causal Relations. 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2003.
  • Aliferis CF, Tsamardinos I, Massion P, Statnikov A, Fananapazir N, Hardin D. Machine Learning Models for Classification of Lung Cancer and Selection of Genomic Markers Using Array Gene Expression Data. 16th International Florida Artificial Intelligence Research Society (FLAIRS) Conference, 2003.
  • Tsamardinos I, Aliferis CF, Statnikov A. Algorithms for Large Scale Markov Blanket Discovery. 16th International Florida Artificial Intelligence Research Society (FLAIRS) Conference, 2003.
  • Frey L, Fisher D, Tsamardinos I, Aliferis CF, Statnikov A. Identifying Markov Blankets with Decision Tree Induction. Third IEEE International Conference on Data Mining (ICDM), 2003.
  • Aliferis CF, Tsamardinos I, Statnikov A., Brown LE. Causal Explorer: A Probabilistic Network Learning Toolkit for Biomedical Discovery. International Conference on Mathematics and Engineering Techniques in Medicine and Biological Sciences (METMBS), 2003.
  • Aliferis CF, Tsamardinos I, Massion P, Statnikov A, Hardin D. Why Classification Models Using Array Gene Expression Data Perform So Well: A Preliminary Investigation of Explanatory Factors. International Conference on Mathematics and Engineering Techniques in Medicine and Biological Sciences (METMBS), 2003.
Posters and Abstracts in Conference Proceedings
  • Zimmerman LJ, Coleman JA, Hardin DP, Statnikov A, Aliferis CF, Liebler DC. Development of Metrics for Assessment of Plasma Quality. 57th ASMS Conference on Mass Spectrometry and Allied Topics, 2009.
  • Kokkotou E, Lois A, Triggs C, Conboy L, McDougall L, Statnikov A, Aliferis CF, Pothoulakis C, Kaptchuk T, Lembo A. Serum Biomarker Analysis of Placebo Responses in Patients with Irritable Bowel Syndrome. Neurogastroenterology and Motility Joint International Meeting, 2008.
  • Aliferis CF, Statnikov A, Tsamardinos I, Kokkotou E, Massion PP. Application and Comparative Evaluation of Causal and Non-Causal Feature Selection Algorithms for Biomarker Discovery in High-Throughput Biomedical Datasets. Neural Information Processing Systems (NIPS) 2006 Workshop on Causality and Feature Selection, 2006.
  • Aliferis CF, Statnikov A, Massion PP. Pathway Induction and High-Fidelity Simulation for Molecular Signature and Biomarker Discovery in Lung Cancer Using Microarray Gene Expression Data. APS Conference: Physiological Genomics and Proteomics of Lung Disease, 2006.
  • Statnikov A, Tsamardinos I, Aliferis CF. Using GEMS for Cancer Diagnosis and Biomarker Discovery from Microarray Gene Expression Data. 13th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB), 2005. (Best Poster Award)
Software Demonstrations in Conference Proceedings
  • Statnikov A, Tsamardinos I, Aliferis CF. Using the GEMS System for Supervised Analysis of Cancer Microarray Gene Expression Data. AMIA Annual Symposium, 2005.
  • Statnikov A, Tsamardinos I, Aliferis CF. Using the GEMS System for Cancer Diagnosis and Biomarker Discovery from Microarray Gene Expression Data. 12th National Conference on Artificial Intelligence (AAAI), 2005.
  • Statnikov A, Tsamardinos I, Aliferis CF. Using GEMS for Cancer Diagnosis and Biomarker Discovery from Microarray Gene Expression Data. 13th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB), 2005.
Papers in Preparation or under Review
  • Statnikov A, Aliferis CF. Algorithms for Identification of Multiple Non-Redundant Markov Blankets. In preparation, 2009.
  • Statnikov A, Aliferis CF. Analysis and Computational Dissection of Molecular Signature Multiplicity. In preparation, 2009.
  • Statnikov A, Aliferis CF. TIED: An Artificially Simulated Dataset with Multiple Markov Boundaries. Submitted, 2009.
  • Mani S, Aliferis CF, Statnikov A. Bayesian Algorithms for Causal Data Mining. Submitted, 2009.
  • Mani S, Cooper GF, Statnikov A. Discovering Causal Relationships in the Presence of Hidden Variables. Submitted, 2009.
Technical Reports
  • Statnikov A, Kasparova E, Aliferis CF. Applying Decision Support Models in the Presence of Incomplete Evidence. Technical Report DSL TR-06-02, Department of Biomedical Informatics, Vanderbilt University, 2006.
  • Statnikov A, Tsamardinos I, Aliferis CF. New Efficient and Correct Algorithms for Identification of Direct Causal Relationships and Markov Blankets from Data. Technical Report DSL TR-06-01, Department of Biomedical Informatics, Vanderbilt University, 2006.
  • Tsamardinos I, Aliferis CF, Statnikov A, Brown LE. Scaling-Up Bayesian Network Learning to Thousands of Variables Using Local Learning Technique. Technical Report DSL TR-03-02, Department of Biomedical Informatics, Vanderbilt University, 2003.
  • Statnikov A, Tsamardinos I, Aliferis CF. An Algorithm for Generation of Large Bayesian Networks. Technical Report DSL TR-03-01, Department of Biomedical Informatics, Vanderbilt University, 2003.
  • Aliferis CF, Tsamardinos I, Statnikov A. Large-Scale Feature Selection Using Markov Blanket Induction for the Prediction of Protein-Drug Binding. Technical Report DSL TR-02-06, Department of Biomedical Informatics, Vanderbilt University, 2002.
Theses
  • Statnikov A. Algorithms for Discovery of Multiple Markov Boundaries: Application to the Molecular Signature Multiplicity Problem. Ph.D. Thesis. Department of Biomedical Informatics, Vanderbilt University, Advisor: Dr. Constantin F. Aliferis, Committee Members: Dr. Gregory F. Cooper, Dr. Douglas P. Hardin, Dr. Daniel R. Masys, Dr. Ioannis Tsamardinos, December 2008.
  • Statnikov A. Automatic Cancer Diagnostic Decision Support System for Gene Expression Domain. Master’s Thesis. Department of Biomedical Informatics, Vanderbilt University, Advisors: Dr. Constantin F. Aliferis and Dr. Ioannis Tsamardinos, August 2005.
  • Statnikov A. Numerical Methods for Image Reconstruction for the Calibration of the NASA-Glenn Icing Research Wind Tunnel: A Computer-Based Approach. Master’s Thesis. Department of Mathematics, Case Western Reserve University, Advisor: Dr. Steven H. Izen, August 2002.
Patents
  • Statnikov A, Aliferis CF. A Method for Determining All Markov Boundaries and Its Application for Discovering Multiple Optimally Predictive and Non-Redundant Molecular Signatures. United States Provisional Patent Application, 2008.
  • Statnikov A, Aliferis CF, Tsamardinos I, Fananapazir N. Method and System for Automated Supervised Data Analysis. United States Patent Application #20070122347, 2006.
(The list of publications in Multicriteria Analysis is available upon request)