Home › Publications › Peer-reviewed papers

Peer-reviewed papers

Peer-reviewed papers

  1. Ma S, Kemmeren P, Gresham D, Statnikov A. De-Novo Learning of Genome-Scale Regulatory Networks in S. Cerevisiae. PLoS ONE (in press), 2014.
  2. Galatzer-Levy IR, Karstoft KI, Statnikov A, Shalev AY. Quantitative Forecasting of PTSD from Early Trauma Responses: A Machine Learning Application. Journal of Psychiatric Research (in press), 2014.
  3. Aphinyanaphongs Y, Fu L, Li Z, Peskin E, Efstathiadis E, Aliferis CF, Statnikov A. A Comprehensive Empirical Comparison of Modern Supervised Classification and Feature Selection Methods for Text Categorization. Journal of the American Society for Information Science and Technology (JASIST) (in press), 2014.  
  4. Aphinyanaphongs Y, Ray B, Statnikov A, Krebs P. Text Classification for Automatic Detection of Alcohol Use-Related Tweets: A Feasibility Study. Proceedings of the 3rd International Workshop on Issues and Challenges in Social Computing (WICSOC), 2014.
  5. Ray B, Henaff M, Ma S, Efstathiadis E, Peskin E, Picone M, Poli T, Aliferis CF, Statnikov A. Information Content and Analysis Methods for Multi-Modal High-Throughput Biomedical Data. 2014; 4:4411.   
  6. Shmelkov E, Krachmarov C, Grigoryan A, Pinter A, Statnikov A, Cardozo T. Computational Prediction of Neutralization Epitopes Targeted by Human Anti-V3 HIV Monoclonal Antibodies. PLoS ONE, 2014, 9(2): e89987.   
  7. Guyon I, Battaglia D, Guyon A, Orlandi J, Saeed M, Fradera JS, Statnikov A, Stetter O. Design of the First Neural Connectomics Challenge: From Imaging to Connectivity. Proceedings of the 2014 International Joint Conference on Neural Networks, 2014.
  8. Statnikov A, Alekseyenko AV, Li Z, Henaff M, Perez-Perez GI, Blaser MJ, Aliferis CF. Microbiomic Signatures of Psoriasis: Feasibility and Methodology Comparison, Scientific Reports, 2013; 3:2620.  
  9. Statnikov A, Henaff M, Narendra V, Koganti K, Li Z, Yang L, Pei Z, Blaser MJ, Aliferis CF, Alekseyenko AV. A Comprehensive Evaluation of Multicategory Classification Methods for Microbiomic Data. Microbiome, 2013; 1:11.   
  10. Udyavar AR, Hoeksema MD, Clark JE, Zou Y, Tang Z, Li M, Chen H, Statnikov A, Li Z, Shyr Y, Liebler DC, Field J, Eisenberg R, Estrada L, Massion PP, Quaranta V. Co-Expression Network Analysis Identifies Spleen Tyrosine Kinase (SYK) as an Oncogenic Driver in Small-Cell Lung Cancer. BMC Systems Biology, 2013; 7(Suppl 5): S1.  
  11. Statnikov A, Lytkin NI, Lemeire J, Aliferis CF. Algorithms for Discovery of Multiple Markov Boundaries.Journal of Machine Learning Research, 2013; 14: 499-566.  
  12. Bai J, Alekseyenko AV, Statnikov A, Wang IM, Wong P. Strategic Application of Gene Expression: from Drug Discovery/Development to Bedside. The American Association of Pharmaceutical Scientists (AAPS) Journal, 2013; 15(2): 427-437.   
  13. Statnikov A, Henaff M, Lytkin NI, Aliferis CF. New Methods for Separating Causes from Effects in Genomics Data. BMC Genomics, 2012;13(Suppl 8): S22.   
  14. Feig JE, Vengrenyuk Y, Reiser V, Wu C, Statnikov A, Aliferis CF, Garabedian MJ, Fisher EA, Puig O.Regression of Atherosclerosis is Characterized by Broad Changes in the Plaque Macrophage Transcriptome. PLoS ONE, 2012; 7(6): e39790.   
  15. Marbach D, Costello JC, Küffner R, Vega N, Prill RJ, Camacho DM, Allison KR, the DREAM5 Consortium (including Statnikov A), Kellis M, Collins JJ, Stolovitzky G. Wisdom of Crowds for Robust Gene Network Inference. Nature Methods, 2012; 9(8): 796-804.   
  16. Lytkin NI, McVoy L, Weitkamp JH, Aliferis CF, Statnikov A. Expanding the Understanding of Biases in Development of Clinical-Grade Molecular Signatures: A Case Study in Acute Respiratory Viral Infections.PLoS ONE, 2011; 6(6): e20662.   
  17. Alekseyenko AV, Lytkin NI, Ai J, Ding B, Padyukov L, Aliferis CF, Statnikov A. Causal Graph-Based Analysis of Genome-Wide Association Data in Rheumatoid Arthritis. Biology Direct, 2011; 6(1): 25.  
  18. Shmelkov E, Tang Z, Aifantis I, Statnikov A. Assessing Quality and Completeness of Human Transcriptional Regulation Pathways on a Genome-Wide Scale. Biology Direct, 2011; 6(1): 15.  
  19. Narendra V, Lytkin NI, Aliferis CF, Statnikov A. A Comprehensive Assessment of Methods for De-Novo Reverse-Engineering of Genome-Scale Regulatory Networks. Genomics, 2011; 97(1): 7-18.  
  20. Aliferis CF, Alekseyenko AV, Aphinyanaphongs Y, Brown S, Fenyo D, Fu L, Shen S, Statnikov A, Wang J.Trends and Developments in Bioinformatics in 2010: Prospects and Perspectives. IMIA Yearbook of Medical Informatics, 2011; 6(1): 146-155.   
  21. Lemeire J, Meganck S, Cartella F, Liu T, Statnikov A. Inferring the Causal Decomposition under the Presence of Deterministic Relations. Proceedings of the 19th European Symposium on Artificial Neural Networks (ESANN), 2011. 
  22. Guyon I, Statnikov A, Aliferis CF. Time Series Analysis with the Causality Workbench. Journal of Machine Learning Research W&CP, 2011; 12: 115-139.  
  23. Statnikov A, Lytkin NI, McVoy L, Weitkamp JH, Aliferis CF. Using Gene Expression Profiles from Peripheral Blood to Identify Asymptomatic Responses to Acute Respiratory Viral Infections. BMC Research Notes, 2010; 3(1): 264.   
  24. Espinosa L, Cathelin S, D’Altri T, Trimarchi T, Statnikov A, Guiu J, Rodilla V, Ingles-Esteve J, Nomdedeu J, Bellosillo B, Besses C, Abdel-Wahab O, Kucine N, Sun SC, Song G, Mullighan CC, Levine RL, Rajewsky K, Aifantis I, Bigas A. The Notch/Hes1 Pathway Sustains NF-κB Activation through CYLD Repression in T Cell Leukemia. Cancer Cell, 2010; 18(3): 268-281.   
  25. Statnikov A, Aliferis CF. Analysis and Computational Dissection of Molecular Signature Multiplicity. (Cover Article) PLoS Computational Biology, 2010; 6(5): e1000790.   
  26. Statnikov A, McVoy L, Lytkin N, Aliferis CF. Improving Development of the Molecular Signature for Diagnosis of Acute Respiratory Viral Infections. Cell Host & Microbe, 2010; 7(2): 100-101.   
  27. Guyon I, Pellet JP, Statnikov A. Development of Projects for the Causality Workbench. Proceedings of the AAAI Artificial Intelligence and Development (AI-D) Spring Symposium, 2010.  
  28. 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. Journal of Machine Learning Research, 2010; 11: 171-234.  
  29. 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.Journal of Machine Learning Research, 2010; 11: 235-284.  
  30. Statnikov A, Aliferis CF. TIED: An Artificially Simulated Dataset with Multiple Markov Boundaries. Journal of Machine Learning Research W&CP, 2010, 6: 249-256.  
  31. Mani S, Aliferis CF, Statnikov A. Bayesian Algorithms for Causal Data Mining. Journal of Machine Learning Research W&CP, 2010, 6: 121-136.  
  32. 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.   
  33. Fananapazir N, Statnikov A, Aliferis CF. The FAST-AIMS Clinical Mass Spectrometry Analysis System.Advances in Bioinformatics, 2009; 2009: 598241.   
  34. 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.   
  35. Statnikov A, Li C, Aliferis CF. A Statistical Reappraisal of the Findings of an Esophageal Cancer GenomeWide Association Study. Cancer Research, 2008; 68: 3074-3075.   
  36. Guyon I, Aliferis CF, Cooper GF, Elisseeff A, Pellet JP, Spirtes P, Statnikov A. Design and Analysis of the Causation and Prediction Challenge. Journal of Machine Learning Research W&CP, 2008, 3: 1-33.  
  37. 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.   
  38. Statnikov A, Aliferis CF. Are Random Forests Better than Support Vector Machines for Microarray-Based Cancer Classification?. Proceedings of the AMIA Annual Symposium, 2007.   
  39. 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, 2007; 2: 133-162.   
  40. 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; 13: 446-455.   
  41. Statnikov A, Hardin D, Aliferis CF. Using SVM Weight-Based Methods to Identify Causally Relevant and Non-Causally Relevant Variables. Proceedings of the Neural Information Processing Systems (NIPS) 2006 Workshop on Causality and Feature Selection, 2006. 
  42. Tsamardinos I, Statnikov A, Brown LE, Aliferis CF. Generating Realistic Large Bayesian Networks by Tiling.Proceedings of the 19th International Florida Artificial Intelligence Research Society (FLAIRS) Conference, 2006  
  43. Levy S, Statnikov A, Aliferis CF. Biomarker Selection from High-Dimensionality Data. Pharmaceutical Discovery, 2005; 2005 Microarray Supplement: 37-44. 
  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; 74(7-8): 493-501.   
  45. 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; 21(5): 631-643.   
  46. 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; 12(2): 207-216.   
  47. Duda S, Aliferis CF, Miller R, Statnikov A, Johnson K. Extracting Drug-Drug Interaction Articles from MEDLINE to Improve the Content of Drug Databases. Proceedings of the AMIA Annual Symposium, 2005.  
  48. 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. Studies in Health Technology and Informatics. 2004; 107(Pt 2): 813-817.   
  49. Aliferis CF, Tsamardinos I, Statnikov A. HITON: A Novel Markov Blanket Algorithm for Optimal Variable Selection. Proceedings of the AMIA Annual Symposium, 2003.   
  50. Tsamardinos I, Aliferis CF, Statnikov A. Time and Sample Efficient Discovery of Markov Blankets and Direct Causal Relations. Proceedings of the 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2003.  
  51. 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.Proceedings of the 16th International Florida Artificial Intelligence Research Society (FLAIRS) Conference, 2003.  
  52. Tsamardinos I, Aliferis CF, Statnikov A. Algorithms for Large Scale Markov Blanket Discovery. Proceedings of the 16th International Florida Artificial Intelligence Research Society (FLAIRS) Conference, 2003.  
  53. Frey L, Fisher D, Tsamardinos I, Aliferis CF, Statnikov A. Identifying Markov Blankets with Decision Tree Induction. Proceedings of the third IEEE International Conference on Data Mining (ICDM), 2003.  
  54. Aliferis CF, Tsamardinos I, Statnikov A, Brown LE. Causal Explorer: A Probabilistic Network Learning Toolkit for Biomedical Discovery. Proceedings of the International Conference on Mathematics and Engineering Techniques in Medicine and Biological Sciences (METMBS), 2003. 
  55. 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. Proceedings of the International Conference on Mathematics and Engineering Techniques in Medicine and Biological Sciences (METMBS), 2003.