Alexander Statnikov

University of North Carolina at Chapel Hill — United States

Biochemistry, Genetics and Molecular Biology · Life Sciences

36h-index6.8kcitations102works0.02yr avg
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Research Topics

Gene expression and cancer classification(26), Bioinformatics and Genomic Networks(21), Bayesian Modeling and Causal Inference(19), Machine Learning and Data Classification(11), Machine Learning and Algorithms(8)

Publications102 total

Low-Grade Inflammation in Symptomatic Knee Osteoarthritis: Prognostic Value of Inflammatory Plasma Lipids and Peripheral Blood Leukocyte Biomarkers: COX AND IL MEDIATORS PREDICT RADIOGRAPHIC PROGRESSION IN OA
UNC Libraries·2020Open Access
Analysis of the AutoML Challenge Series 2015–2018
˜The œSpringer series on challenges in machine learning·2019· 125 citedOpen Access
Results of the Cause-Effect Pair Challenge
˜The œSpringer series on challenges in machine learning·2019· 2 cited
Analysis of the AutoML Challenge Series 2015–2018
Greater South Information System·2019· 8 citedOpen Access
Utilization of machine learning for prediction of post-traumatic stress: a re-examination of cortisol in the prediction and pathways to non-remitting PTSD
Translational Psychiatry·2017· 137 citedOpen Access
Methods for computational causal discovery in biomedicine
Behaviormetrika·2017· 16 cited
An Automated System for Data Attribute Anomaly Detection
Knowledge Discovery and Data Mining·2017· 2 cited
First Connectomics Challenge: From Imaging to Connectivity
˜The œSpringer series on challenges in machine learning·2017· 10 cited
Anomaly Detection in Finance: Editors’ Introduction
Knowledge Discovery and Data Mining·2017· 29 cited
A Complex Systems Approach to Causal Discovery in Psychiatry
PLoS ONE·2016· 33 citedOpen Access
Evaluation and Ensembling of Methods for Reverse Engineering of Brain Connectivity from Imaging Data
arXiv (Cornell University)·2016Open Access
An Evaluation of Active Learning Causal Discovery Methods for Reverse-Engineering Local Causal Pathways of Gene Regulation
Scientific Reports·2016· 10 citedOpen Access
A brief Review of the ChaLearn AutoML Challenge: Any-time Any-dataset Learning without Human Intervention
SPIRE - Sciences Po Institutional REpository·2016· 59 cited
Plasma levels of interleukin-1 receptor antagonist (IL1Ra) predict radiographic progression of symptomatic knee osteoarthritis
Osteoarthritis and Cartilage·2015· 77 citedOpen Access
Low‐Grade Inflammation in Symptomatic Knee Osteoarthritis: Prognostic Value of Inflammatory Plasma Lipids and Peripheral Blood Leukocyte Biomarkers
Arthritis & Rheumatology·2015· 116 citedOpen Access
Design of the 2015 ChaLearn AutoML challenge
2015· 122 cited
Early identification of posttraumatic stress following military deployment: Application of machine learning methods to a prospective study of Danish soldiers
Journal of Affective Disorders·2015· 72 cited
Elevated peripheral blood leukocyte inflammatory gene expression in radiographic progressors with symptomatic knee osteoarthritis: NYU and OAI cohorts
Osteoarthritis and Cartilage·2015· 1 citedOpen Access
Bridging a translational gap: using machine learning to improve the prediction of PTSD
BMC Psychiatry·2015· 150 citedOpen Access
Molecular Characterization of the Peripheral Airway Field of Cancerization in Lung Adenocarcinoma
PLoS ONE·2015· 28 citedOpen Access
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Frequent Co-authors

Constantin Aliferis(32), Ioannis Tsamardinos(13), Mikael Henaff(5), Alexander V. Alekseyenko(5), Bisakha Ray(5), Isaac R. Galatzer‐Levy(4), Sisi Ma(4), Isabelle Guyon(4), Nikita I. Lytkin(4), Karen‐Inge Karstoft(3), Arieh Y. Shalev(3), Hugo Jair Escalante(3), Sérgio Escalera(3), Evelyne Viegas(3), Yindalon Aphinyanaphongs(3), E. Peskin(3), E. Efstathiadis(3), Douglas P. Hardin(2), Subramani Mani(2), Xenofon Koutsoukos(2)