2024
Lily A. Clough, Victoria Da Poian, Jonathan D. Major, Lauren M. Seyler, *Brett A. McKinney, *Bethany P. Theiling. “Interpretable Machine Learning Biosignature Detection from Ocean Worlds Analogue CO2 Isotopologue Data,” Preprint (2024) ESS Open Archive *Corresponding authors
Elizabeth Kresock, Bryan Dawkins, Henry Luttbeg, Jamie Li, Rayus Kuplicki, B. A. McKinney. “Centrality-based nearest-neighbor projected-distance regression (C-NPDR) feature selection for correlation predictors with application to resting-state fMRI of major depressive disorder,” Research Square Preprint (2024) https://doi.org/10.21203/rs.3.rs-4193488/v1
Yijie (Jamie) Li, Rayus Kuplicki, Bart N. Ford, Elizabeth Kresock, Leandra Figueroa-Hall, Jonathan Savitz, B. A. McKinney. “Gene Age Gap Estimate (GAGE) for major depressive disorder: a penalized biological age model using gene expression,” Preprint (2024) https://doi.org/10.1101/2024.09.03.610913
Kaiping Burrows, Leandra K. Figueroa-Hall, Jennifer L. Stewart, Ahlam M. Alarbi, Rayus Kuplicki, Bethany N. Hannafon, Chibing Tan, Victoria B. Risbrough, Brett A. McKinney, Rajagopal Ramesh, Teresa A. Victor, Robin Aupperle, Jonathan Savitz, T. Kent Teague, Sahib S. Khalsa & Martin P. Paulus. “Exploring the role of neuronal-enriched extracellular vesicle miR-93 and interoception in major depressive disorder,” Translational Psychiatry volume 14, Article number: 199 (2024). https://www.nature.com/articles/s41398-024-02907-x
Bryan A. Dawkins and B. A. McKinney. “Multivariate optimization of k for k-nearest-neighbor feature selection with dichotomous outcomes: complex associations, class imbalance, and application to RNA-Seq in Major Depressive Disorder,” BioRxiv (2022) https://www.biorxiv.org/content/10.1101/2022.05.19.492724v1.
Yijie (Jamie) Li, J. Zhang, B.A. McKinney, S. Karimi, SA Shirazi. “Linear Versus Non-Linear Machine Learning Feature Selection for Erosion Rate Prediction.” Proceedings of the ASME 2024 Fluids Engineering Division Summer Meeting, Volume 2: Computational Fluid Dynamics (CFDTC); Micro and Nano Fluid Dynamics (MNFDTC); Flow Visualization. Anaheim, California, USA. July 15–17, 2024. V002T05A005. ASME. https://doi.org/10.1115/FEDSM2024-130309 view abstract
H. Khaleghpour and B. A. McKinney, “Optimizing Neuro-Fuzzy and Colonial Competition Algorithms for Skin Cancer Diagnosis in Dermatoscopic Images,” 7th International Conference on Information and Computer Technologies (ICICT), Honolulu, HI, USA, 2024, pp. 166-172, doi:10.1109/ICICT62343.2024.00032. https://ieeexplore.ieee.org/document/10541825
Vu Nguyen, Minh Phan, Tiantian Wang, Salih Tutun, B.A. McKinney, Bahareh Rahmani. “PTSD Case Detection with Boosting,” Signals (MDPI) 2024, 5(3), 508-515; https://doi.org/10.3390/signals5030027
2023
Lanie G. McKinney and B. A. McKinney. “Conditions for Bound States of the Pseudopotential with Harmonic Confinement in Arbitrary Dimensions,” Physica Scripta (2023) 98 015404 https://iopscience.iop.org/article/10.1088/1402-4896/aca6b6.
Victoria Da Poian, Bethany Theiling, Lily Clough, Brett McKinney, Jonathan Major, Jingyi Chen and Sarah Hörst. “Exploratory Data Analysis (EDA) Machine Learning Approaches for Ocean World Analog Mass Spectrometry,” Frontiers in Astronomy Space Science – Planetary Science Volume 10 (2023) https://doi.org/10.3389/fspas.2023.1134141.
Azhar Iqbal Kashif Butt, Muhammad Imran, Brett A. McKinney, Saira Batool and Hassan Aftab. “Mathematical and Stability Analysis of Dengue–Malaria Co-Infection with Disease Control Strategies,” Mathematics 2023, 11(22), 4600; https://doi.org/10.3390/math11224600
2022
Yijie (Jamie) Li, Elizabeth Kresock, Rayus Kuplicki, Jonathan Savitz, B. A.McKinney. “Differential expression of MDGA1 in major depressive disorder,” Brain, Behavior, & Immunity – Health (2022) https://doi.org/10.1016/j.bbih.2022.100534.
Laura D Wilson, Rachel A Hildebrand, Trang T. Le, B. A. McKinney. “Repetitive head impacts in a collegiate football season: Exposure and effects,” International Journal of Sports Science & Coaching 17(2): 285-297 (2022) https://doi.org/10.1177/17479541211027277.
A. Sedhain, S. S. Ragavan, B. McKinney and S. K. Kuttal, “Estimating Foraging Values and Costs in Stack Overflow,” 2022 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC) pp. 1-4, doi:10.1109/VL/HCC53370.2022.9833135.
Ian Riley, B.A. McKinney, R.F. Gamble. “Improving the Expected Performance of Self-Organization in a Collective Adaptive System of Drones using Stochastic Multiplayer Games,” Proceedings of the 55th Hawaii International Conference on System Sciences (2022) http://hdl.handle.net/10125/80260.
2021
Bryan A. Dawkins, Trang T. Le, B. A. McKinney. “Theoretical properties of distance distributions and novel metrics for nearest-neighbor feature selection,” PLoS ONE 16(2): e0246761. (2021) https://doi.org/10.1371/journal.pone.0246761.
Rayus Kuplicki, J. Touthang, O. A. Zoubi, A. Mayeli, M. Misaki, NeuroMAP-Investigators, R. L. Aupperle, T. K. Teague, B. A. McKinney, M. Paulus, J. Bodurka. “Common Data Elements, Scalable Data Management Infrastructure and Analytics Workflows for Large-scale Neuroimaging Studies,” Frontiers in Psychiatry, section Neuroimaging and Stimulation 17 June (2021) DOI: 10.3389/fpsyt.2021.682495. Open Access.
2020
Trang T. Le, Bryan A. Dawkins, B. A. McKinney. “Nearest-neighbor Projected-Distance Regression (NPDR) for detecting network interactions with adjustments for multiple tests and confounding,” Bioinformatics (2020) https://doi.org/10.1093/bioinformatics/btaa024 github version or biorxiv.
Saeid Parvandeh, Hung-Wen Yeh, M. P. Paulus, B. A. McKinney. “Consensus Features Nested Cross-Validation,” Bioinformatics (2020) https://doi.org/10.1093/bioinformatics/btaa046 preprint version.
Marziyeh Arabnejad, C. G. Montgomery, P. M. Gaffney, B. A. McKinney. “Nearest-Neighbor Projected Distance Regression for Epistasis Detection in GWAS With Population Structure Correction,” Frontiers in Genetics (2020) https://www.frontiersin.org/articles/10.3389/fgene.2020.00784/abstract.
Matt Moradi, H. Ekhtiari, R. Kuplicki, B. A. McKinney, J. L. Stewart, T. A. Victor, M. P. Paulus. “Evaluating the Resource Allocation Index as a Potential fMRI-based Biomarker for Substance Use Disorder,” Drug and Alcohol Dependence (2020) https://doi.org/10.1016/j.drugalcdep.2020.108211.
B. Xu, Matt Moradi, R. T. Kuplicki, J. L. Stewart, B. A. McKinney, S. Sen, M. P. Paulus. “Machine Learning Analysis of Electronic Nose in a Transdiagnostic Community Sample with a Streamlined Data Collection Approach: No Links Between Volatile Organic Compounds and Psychiatric Symptoms,” Frontiers in Psychiatry, section Computational Psychiatry (2020) https://doi.org/10.3389/fpsyt.2020.503248.
2019
Trang T. Le, Zach Osman, D. K. Watson, Martin Dunn, B. A. McKinney. “Generalization of the Fermi Pseudopotential,” Physica Scripta (2019) 94(6) 065203. preprint. published.
Saeid Parvandeh and B. A. McKinney. “EpistasisRank and EpistasisKatz: interaction network centrality methods that integrate prior knowledge networks,” Bioinformatics. (2019) https://doi.org/10.1093/bioinformatics/bty965t.
Preprint Version.
Supplementary Material
Saied Parvandeh, G.A. Poland, R.B. Kennedy, B. A. McKinney. “Multi-level model to predict antibody response to influenza vaccine using gene expression interaction network feature selection,” Microorganisms: Vaccine Informatics (2019) 7(3), 79 doi:10.3390/microorganisms7030079. https://www.mdpi.com/2076-2607/7/3/79.
A. Pezeshki, I.A. Ovsyannikova, B.A. McKinney, G.A. Poland, R.B. Kennedy. “The role of systems biology approaches in determining molecular signatures for the development of more effective vaccines,” Expert Review of Vaccines (IERV) (2019) https://doi.org/10.1080/14760584.2019.1575208.
S. M. Santos, M. Icyuz, I. Pound, D. William, J. Guo, B. A. McKinney, M. Niederweis, J. W. Rodgers, J. L Hartman IV. “A humanized yeast phenomic model of deoxycytidine kinase to predict genetic buffering of nucleoside analog cytotoxicity,” Genes: Microbial Genetics and Genomics (2019) Sep 30;10(10). pii:E770. doi:10.3390/genes10100770. BioRxiv.
2018
Marziyeh Arabnejad, B. A. Dawkins, W.S. Bush, B.C. White, A.R. Harkness and B. A. McKinney. “Transition-transversion encoding and genetic relationship metric in ReliefF feature selection improves pathway enrichment in GWAS,” BMC BioData Mining. (2018) 11:23.
html: https://doi.org/10.1186/s13040-018-0186-4
Enhanced pdf: https://rdcu.be/baHpV
Trang T. Le, R. J. Urbanowicz, J. H. Moore, B. A McKinney. “STatistical Inference Relief (STIR) feature selection,” Bioinformatics. (2018) Sep 18 https://doi.org/10.1093/bioinformatics/bty788.
Trang T. Le, J. Savitz, H. Suzuki, M. Misaki, T. K. Teague, B. C. White, J. H. Marino, G. Wiley, P. M. Gaffney, W. C. Drevets, B. A. McKinney* and J. Bodurka*. “Identification and replication of RNA-Seq gene network modules associated with depression severity,” Translational Psychiatry (2018) 8:180 DOI 10.1038/s41398-018-0234-3. Open Access *Co-Senior authors
Peyman Zahedi, S. Parvandeh, A. Asgharpour, B. S. McLaury, S. A. Shirazi, B. A. McKinney. “Random Forest Regression Prediction of Solid Particle Erosion in Elbows,” Powder Technology, Volume 338, October 2018, Pages 983-992. ScienceDirect.
Trang T. Le*, R.T. Kuplicki*, B.A. McKinney, H. Yeh, W.K. Thompson and M.P. Paulus. “A nonlinear simulation framework supports adjusting for age when analyzing BrainAGE,” Methods, Front. Aging Neurosci. 24 October 2018. https://doi.org/10.3389/fnagi.2018.00317 *Co-First authors
B. Rahmani, K. W. Chung, P. Norouzzadeh, J. Bodurka, B. A. McKinney. “Dynamical Hurst analysis identifies EEG channel differences between PTSD and healthy controls,” PLoS One. 2018. https://doi.org/10.1371/journal.pone.0199144.
2017
Trang T. Le, W. K. Simmons, M. Misaki, B.C. White, J. Savitz, J. Bodurka, and B. A. McKinney. “Differential privacy-based evaporative cooling feature selection and classification with Relief-F and Random Forests,” Bioinformatics, Volume 33, Issue 18, 15 September 2017, Pages 2906–2913. Open Access.
Suzuki H, Savitz J, Teague K, Gandhapudi SK, Tan C, Misaki M, McKinney BA, Irwin MR, Drevets WC, Bodurka J. “Altered populations of natural killer cells, cytotoxic T lymphocytes, and regulatory T cells in major depressive disorder: Association with sleep disturbance,” Brain, Behavior and Immunity. 2017 Jun 20. pii: S0889-1591(17)30200-3. doi:10.1016/j.bbi.2017.06.011. PubMed.
2016
B. Rahmani, M. Zimmermann, D. Grill, R. Kennedy, A Oberg, B. C. White, G. A. Poland, B. A. McKinney, “Recursive Indirect-Paths Modularity (RIP-M) for Detecting Community Structure in RNA-Seq Co-Expression Networks,” Frontiers in Genetics, 7:80. doi: 10.3389/fgene.2016.00080. 2016.
C. A. Lareau, B.C. White, A.L. Oberg, R.B. Kennedy, G.A. Poland, B.A. McKinney, “An interaction quantitative trait loci (iQTL) tool implicates epistatic functional variants in an apoptosis pathway in smallpox vaccine eQTL data,” Genes and Immunity (Nature Publishing). 17:244–250; doi:10.1038/gene.2016.15. 2016.
B. A. McKinney, C. A. Lareau, A. L. Oberg, R. B. Kennedy, I. G. Ovsyannikova, G. A. Poland, “The Integration of epistasis network and functional interactions in a GWAS implicates RXR pathway genes in the immune response to smallpox vaccine,” PLoS ONE. 11(8): e0158016. doi:10.1371/journal.pone.0158016. 2016.
2015
C. A. Lareau, B. C. White, Courtney G. Montgomery and B. A. McKinney, “dcVar: A Method for Identifying Common Variants that Modulate Differential Correlation Structures in Gene Expression Data,” Frontiers in Genetics. 6:312. doi: 10.3389/fgene.2015.00312. 2015.
C. Lareau, B.C. White, A.L. Oberg, B.A. McKinney, “Differential co-expression network centrality and machine learning feature selection for identifying susceptibility hubs in networks with scale-free structure,” BMC Biodata Mining 8:5. 2015. biodatamining.
C. Lareau, B.A. McKinney, “Network Theory for Data-Driven Epistasis Networks,” in Epistasis: Method and Protocols, Methods in Molecular Biology, Volume: 1253, 285-300, 2015. Springer.
A.L. Oberg, B.A. McKinney, D.J. Schaid, V.S. Pankratz, R.B. Kennedy, G.A. Poland “Lessons learned in the analysis of high-dimensional data in vaccinomics,” Vaccine. Volume 33, Issue 40, Pages 5262-5270. Science Direct.
2014
B. Briney, J. Willis, J. Finn, B.A. McKinney, J.E. Crowe, Jr. “Tissue-specific expressed antibody variable gene repertoires,” PLoS ONE 9(6):e100839. doi:10.1371/journal.pone.0100839. 2014.
2013
B.A. McKinney, B.C. White, D.E. Grill, P.W. Li, R.B. Kennedy, G.A. Poland, A.L. Oberg. “ReliefSeq: A gene-wise adaptive-k nearest-neighbor feature selection tool for finding gene-gene interactions and main effects in mRNA-Seq gene expression data,” PLoS ONE 8(12):e81527. 2013. doi:10.1371/journal.pone.0081527.
N.A. Davis, C.A. Lareau, B.C. White, A. Pandey, G. Wiley, C.G. Montgomery, P.M. Gaffney, B.A. McKinney. “Encore: Genetic association interaction network centrality pipeline and application to SLE exome data,” Genetic Epidemiology. doi: 10.1002/gepi.21739. 2013. PMID: 23740754. (text online)
G. Poland, R. Kennedy, B.A. McKinney, I. Ovsyannikova, N. Lambert, R. Jacobson, A. Oberg. “Vaccinomics, Adversomics, and the Immune Response Network Theory: Individualized Vaccinology in the 21st Century,” Seminars in Immunology. 2013. http://dx.doi.org/10.1016/j.smim.2013.04.007
C. Carley, L. Sells, B.A. McKinney, Zhao, Chao, H. Neeman. “Using a shared, remote cluster for teaching HPC,” Cluster Computing (CLUSTER), 2013 IEEE International Conference 1(6):23-27. 2013.
2012
B.A. McKinney and N.M. Pajewski. “Six degrees of epistasis: Statistical network models of GWAS,” Frontiers in Statistical Genetics and Methodology. 2 (109). doi: 10.3389/fgene.2011.00109; January 2012. (open access)
A. Pandey, N. A. Davis, B. C. White, N. M. Pajewski, J. Savitz, W. C. Drevets, B. A. McKinney. “Epistasis network centrality analysis yields pathway replication across two GWAS cohorts for bipolar disorder,” Translational Psychiatry. 2, e154; doi:10.1038/tp.2012.80 2012. (open access)
Savitz J, Frank MB, Victor T, Bebak M, Marino JH, Bellgowan PS, McKinney BA, Bodurka J, Kent Teague T, Drevets WC. “Inflammation and neurological disease-related genes are differentially expressed in depressed patients with mood disorders and correlate with morphometric and functional imaging abnormalities,” Brain Behav Immun. 2012 Oct 12. doi:pii: S0889-1591(12)00469-2. 10.1016/j.bbi.2012.10.007; Oct 12, 2012. PMID: 23064081
P. Crooke, J. Hotchkiss, Y. Lenbury, and B. A. McKinney. “Mathematical Modeling of Patient Care,” Computational and Mathematical Methods in Medicine. Article ID 563287, 2 pages doi:10.1155/2012/563287; 2012 (open access)
N. M. Pajewski, S. Shrestha, C.P. Quinn, S.D. Parker, H. Weiner, B. Aissani, B.A. McKinney, G.A. Poland, J.C. Edberg, R.P. Kimberly, J. Tang, and R.A. Kaslow. “A Genome-wide Association Study of Host Genetic Determinants of the Antibody Response to Anthrax Vaccine Adsorbed,” Vaccine. 30(32):4778-84; 2012. (open access)
B. S. Briney, Willis J. R., McKinney B. A., Crowe J. E. Jr. “High-throughput antibody sequencing reveals genetic evidence of global regulation of the naïve and memory repertoires that extends across individuals,” Genes and Immunity (Nature Publishing). doi:10.1038/gene.2012.20; 2012. ( abstract )
Louie RJ, Guo J, Rodgers JW, White R, Shah N, Pagant S, Kim P, Livstone M, Dolinski K, McKinney BA, Hong J, Sorscher EJ, Bryan J, Miller EA, Hartman JL 4th. “A yeast phenomic model for the gene interaction network modulating CFTR-DeltaF508 protein biogenesis,” Genome Med. 2012 Dec 27;4(12):103.
2011
N. A. Davis, Ahwan Pandey, and B. A. McKinney. “Real-world comparison of CPU and GPU implementations of SNPrank: a network analysis tool for genome-wide association studies,” Bioinformatics. 27 (2): 284-285; 2011 (pdf)
N. M. Pajewski, S.. D. Parker, G. A. Poland, I. G. Ovsyannikova, W. Song, K. Zhang, B. A. McKinney, V. S. Pankratz, J. C. Edberg, R. P. Kimberly, R. M. Jacobson, J. Tang, and R. A. Kaslow, “The Role of HLA DR-DQ Haplotypes in Variable Antibody Response to Anthrax Vaccine Adsorbed,” Genes and Immunity (Nature Publishing). (3 March 2011) | doi:10.1038/gene.2011.15; 2011.
M. T. Rock, B. A. McKinney, S. M. Yoder, C. E. Prudom, D. W. Wright, J. E. Crowe, Jr. “Identification of potential human respiratory syncytial virus and metapneumovirus T cell epitopes using computational prediction and MHC binding assays,” Journal of Immunological Methods; 2011. (Pubmed).
2010
N. A. Davis, J. E. Crowe, Jr, N. M. Pajewski, B. A. McKinney, “Surfing a genetic association interaction network to identify modulators of antibody response to smallpox vaccine,” Genes and Immunity (Nature Publishing). doi: 10.1038/gene.2010.3; 2010. (open access)
J. Guo, D. Tian, B.A. McKinney, and J.L. Hartman, “Recursive expectation-maximization clustering (REMc): A method for identifying buffering mechanisms composed of phenomic modules,” Chaos: An Interdisciplinary Journal of Nonlinear Science. 5(2):026103;2010. (abstract). Selected for July 1, 2010 issue of Virtual Journal of Biological Physics Research
2009
B.A. McKinney, J.E. Crowe, Jr., J. Guo, and D. Tian, “Capturing the spectrum of interaction effects in genetic association studies by simulated evaporative cooling network analysis,” PLoS Genetics. 5(3): e1000432. doi:10.1371/journal.pgen.1000432; 2009. (open access)
B.A. McKinney, “New Informatics approaches for identifying biologic relationships in time series data,” Wiley Interdisciplinary Reviews: Nanomedicine and Nanobiotechnology. 1:60-68;2009. (online)(pdf)
D. M. Reif, A.A. Motsinger, B. A. McKinney, J. E. Crowe, Jr., J.H. Moore, “Integrated analysis of genetic and proteomic data identifies biomarkers associated with adverse events following smallpox vaccination,” Genes and Immunity. 10:112-119; 2009. (abstract)
Peter F. Wright, Anna P. Durbin, Stephen S. Whitehead, Mine R. Ikizler, Susan Henderson, Joseph E. Blaney, Bhavin Thumar, Sharon Ankrah, Sapna Mehta, Michael T. Rock, Sandra M. Yoder, B. A. McKinney, Brian R. Murphy, and Alexander C. Schmidt, “The dengue virus type 4 vaccine candidate rDEN430-4995 is highly attenuated, safe, and immunogenic in healthy adult volunteers,” Am. J. Trop. Med. Hyg. doi:10.4269/ajtmh.2009.09-0131; 2009.
2008
B.A. McKinney and D. Tian, “Grammatical Immune System Evolution for Reverse Engineering Nonlinear Dynamic Bayesian Models,” Cancer Informatics. 6:433-447; 2008. (open access)
D.M. Reif, B.A. McKinney, A.A. Motsinger, S.J. Chanock, K.M. Edwards, M.T. Rock, J.H. Moore, and J.E. Crowe, Jr., “Genetic Basis for Adverse Events Following Smallpox Vaccination,” Journal of Infectious Diseases. 198:16-22; 2008. (pdf)
F. Bibollet-Ruche, B.A. McKinney, F.H. Wagner, A. Duverger, A.A. Ansari, O. Kutsch “Antibody-mediated activation of chimpanzee T cells via the TCR/CD3 pathway is a function of the anti-CD3 antibody isotype,” Journal of Virology, 82:10271-10278; 2008. (abstract)
S. Faley, K. Seale, J. Hughey, D. Schaffer, B. A. McKinney, F. Baudenbacher, and J. P. Wikswo, “Microfluidic platform for real-time signaling analysis of multiple single T cells in parallel.” Lab Chip. 8:1700-1712; 2008. (abstract)
N. Kallewaard, B.A. McKinney, Y. Gu, A. Chen, B. V. V. Prasad, and J.E. Crowe, Jr., “Functional maturation of the human antibody response to rotavirus,” The Journal of Immunology. 180:3980-3989; 2008. (pdf)
J. Xie, P.S. Crooke, B.A. McKinney, J. Soltman, and S.J. Brandt, “A computational model of quantitative chromatin immunoprecipitation (ChIP) analysis,” Cancer Informatics. 4:137-145; 2008. (pdf)
W.S. Bush, T.L. Edwards, S.M. Dudek, B.A. McKinney, and M.D. Ritchie, “Alternative Contingency Table Measures Improve the Power and Detection of Multifactor Dimensionality Reduction,” BMC Bioinformatics. 9:238; 2008. (open access)
2007
B.A. McKinney, D. M. Reif, B. C. White, J. E. Crowe Jr., J. H. Moore. “Evaporative cooling feature selection for genotypic data involving interactions,” Bioinformatics. 23:2113-2120; 2007. (pdf)
B.A. McKinney, N. Kallewaard, J.E. Crowe, Jr., and J. Meiler, “Using the natural evolution of a rotavirus-specific human monoclonal antibody to predict the complex topography of a viral antigenic site,” Immunome Research. 3:8; 2007. (Pubmed)
2006
B.A. McKinney, J.E. Crowe, H.U. Voss, P.S. Crooke, N.L. Barney, and J.H. Moore, “Hybrid Grammar-based Approach to Nonlinear Dynamical System Identification from Biological Time Series,” Physical Review E, Statistical, Nonlinear, and Soft Matter Physics 73, 021912; 2006. (pubmed)
B.A. McKinney, D.M. Reif, M.T. Rock, K. M. Edwards, S. F. Kingsmore, J.H. Moore, and J.E. Crowe, “Cytokine expression patterns associated with systemic adverse events following smallpox immunization,” Journal of Infectious Diseases. 194(4): 36092; 2006. (free pubmed central)
B.A. McKinney, D.M. Reif, M.D. Ritchie and J.H. Moore, “Machine learning for detecting gene-gene interactions,” Applied Bioinformatics, 5(2):77-88; 2006. (pdf) (free pubmed central)
D. M. Reif, A. A. Motsinger, B.A. McKinney, and J. H. Moore, “Feature selection using a random forest classifier for the integrated analysis of multiple data types,” Proceedings of the IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology. pp. 171-178; 2006. (pdf)
2004-1999 (Ph.D. related publications)
B.A. McKinney, M. Dunn, D.K. Watson, and J. G. Loeser, “N identical particles under quantum confinement: a many-body dimensional perturbation theory approach,” Annals of Physics 310, 56; 2004.
B. A. McKinney, M. Dunn, and D.K. Watson, “Beyond-mean-field results for atomic Bose- Einstein condensates at interaction strengths near Feshbach resonances: A many-body dimensional perturbation theory calculation,” Phys. Rev. A 69, 053611; 2004. (link)
B.A. McKinney and D.K. Watson, “Bose-Einstein condensation in variable dimensionality,” Phys. Rev. A 65, 33604; 2002.
B.A. McKinney, D.K. Watson, “Semiclassical dimensional perturbation theory for two electrons in a D-dimensional quantum dot,” Phys. Rev. B 61, 4958; 2000.
D.K. Watson and B.A. McKinney, “An improved large-N limit for Bose-Einstein condensates from perturbation theory,” Phys. Rev. A 59, 4091; 1999