Publications

2017
  • K Oksanen and T Hu (2017): Lexicase selection promotes effective search and behavioural diversity of solutions in linear genetic programming. Proceedings of the 2017 IEEE Congress on Evolutionary Computation (CEC), pp.169-176
  • T Hu and JH Moore (2017): A network-guided MDR approach to searching for high-order genetic interactions. Multifactor Dimensionality Reduction Book (Cambridge University Press), in press
  • T Hu and W Banzhaf (2017): Neutrality, robustness, and evolvability in genetic programming. Genetic Programming Theory and Practice XIV (Springer), in press
  • EvoApplications chairs (including T Hu as chair of EvoBio), editors (2017): Applications of Evolutionary Computation, Proceedings of the 20th European Conference on the Applications of Evolutionary Computation (EvoApplications), Lecture Notes in Computer Science, vol. 10199 & 10200
2016
  • T Hu and W Banzhaf (2016): Quantitative analysis of evolvability using vertex centralities in phenotype networks. Proceedings of the 25th Genetic and Evolutionary Computation Conference (GECCO), pp.733-740 (Nominated Best Paper Award)
  • S Ye, Y Chen, and T Hu (2016): Evolutionary algorithmic deployment of radio beacons for indoor positioning. Proceedings of the 2016 IEEE Congress on Evolutionary Computation (CEC), pp.2829-2835
  • T Hu, W Zhang, Z Fan, G Sun, S Likhodi, E Randell, and G Zhai (2016): Metabolomics differential correlation network analysis of Osteoarthritis. Proceedings of the Pacific Symposium on Biocomputing (PSB), 21:120-131
  • EvoApplications chairs (including T Hu as chair of EvoBio), editors (2016): Applications of Evolutionary Computation, Proceedings of the 19th European Conference on the Applications of Evolutionary Computation (EvoApplications), Lecture Notes in Computer Science, vol. 9597 & 9598
2015
  • T Hu, AS Andrew, MR Karagas, and JH Moore (2015): The functional dyadicity and heterophilicity of gene-gene interactions in statistical epistasis networks. BioData Mining, 8:43
  • R De, T Hu, D Gilbert-Diamond, and JH Moore (2015): Characterizing gene-gene interactions in a statistical epistasis network of twelve candidate genes for obesity. BioData Mining, 8:45
  • MJ White, F Eren, D Agirbasli, J Chen, T Hu, JH Moore, SM Williams, M Agirbasli (2015): A systems genetics approach to dyslipidemia in children and adolescents. OMICS: A Journal of Integrative Biology, 19(4):248-259
  • AS Andrew, J Gui, T Hu, A Wyszynski, CJ Marsit, KT Kelsey, AR Schned, SA Tanyos, EM Pendleton, RA Mason, Z Li, MS Zens, M Borsuk, JH Moore, and MR Karagas (2015): Genetic polymorphisms modify bladder cancer recurrence and survival in a U.S. population-based prognostic study. British Journal of Urology International (BJUI), 115(2):238-247
  • T Hu, C Darabos, ME Cricco, E Kong, and JH Moore (2015): Genome-wide genetic interaction analysis of glaucoma using expert knowledge derived from human phenotype networks. Proceedings of the Pacific Symposium on Biocomputing (PSB), 20:207-218
  • JH Moore and T Hu (2015): Epistasis analysis using information theory. Epistasis, Methods in Molecular Biology (Springer Press) vol. 1253, chapter 13, pages 257-268
2014
  • T Hu, W Banzhaf, and JH Moore (2014): The effects of recombination on phenotypic exploration and robustness in evolution. Artificial Life, 20(4):457-470
  • T Hu, Q Pan, AS Andrew, JM Langer, MD Cole, CR Tomlinson, MR Karagas, and JH Moore (2014): Functional genomics annotation of a statistical epistasis network associated with bladder cancer susceptibility. BioData Mining, 7(1):5
  • Q Pan, T Hu, JD Malley, AS Andrew, MR Karagas, and JH Moore (2014): A system-level pathway-phenotype association analysis using synthetic feature random forest. Genetic Epidemiology, 38(3):209-219
  • MJ White, A Tacconelli, JS Chen, C Wejse, PC Hill, VF Gomes, DR Velez, LJ Ostergaard, T Hu, JH Moore, G Novelli, WK Scott, SM Williams, and G Sirugo (2014): Epiregulin (EREG) and human V-ATPase (TCIRG1): genetic variation, ethnicity and pulmonary tuberculosis susceptibility in Guinea-Bissau and The Gambia. Genes and Immunity, 15:370-377
  • AL Zieselman, JM Fisher, T Hu, PC Andrews, CS Greene, L Shen, AJ Saykin, JH Moore and ADNI (2014): Computational genetics analysis of grey matter density in Alzheimer's disease. BioData Mining, 7:17
  • T Hu, W Banzhaf, and JH Moore (2014): Population exploration on genotype networks in genetic programming. Proceedings of the 13th International Conference on Parallel Problem Solving from Nature (PPSN), Lecture Notes in Computer Science, 8672:424-433
2013
  • T Hu, Y Chen, JW Kiralis, and JH Moore (2013): ViSEN: methodology and software for visualization of statistical epistasis networks. Genetic Epidemiology, 37(3):283-285
  • T Hu, Y Chen, JW Kiralis, RL Collins, C Wejse, G Sirugo, SM Williams, and JH Moore (2013): An information-gain approach to detecting three-way epistatic interactions in genetic association studies. Journal of the American Medical Informatics Association (JAMIA), 20:630-636
  • RL Collins, T Hu, C Wejse, G Sirugo, SM Williams, and JH Moore (2013): Multifactor dimensionality reduction reveals a three-locus epistatic interaction associated with susceptibility to pulmonary tuberculosis. BioData Mining, 6(1):4
  • T Hu, AS Andrew, MR Karagas, and JH Moore (2013): Statistical epistasis networks reduce the computational complexity of searching three-locus genetic models. Proceedings of the Pacific Symposium on Biocomputing (PSB), 18:397-408
  • T Hu, W Banzhaf, and JH Moore (2013): Robustness and evolvability of recombination in linear genetic programming. Proceedings of the 16th European Conference on Genetic Programming (EuroGP), Lecture Notes in Computer Science, 7831:97-108
  • Q Pan, T Hu, JD Malley, AS Andrew, MR Karagas, and JH Moore (2013): Supervising random forests using attribute interaction networks. Proceedings of the 11th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics (EvoBio), Lecture Notes in Computer Science, 7833:104-116
  • Q Pan, T Hu, AS Andrew, MR Karagas, and JH Moore (2013): Bladder cancer specific pathway interaction networks. Proceedings of the 12th European Conference on Artificial Life (ECAL), pp.94-101
  • Q Pan, T Hu, L Shen, AJ Saykin, and JH Moore (2013): Topological analysis of statistical epistasis networks reveals pathways associated with Alzheimer's disease. Proceedings of the 3rd Translational Bioinformatics Conference (TBC) (Best Paper Award)
  • C Darabos, BE Graham, T Hu, and JH Moore (2013): Bipartite networks show the genotype-to-phenotype relationship in biological systems models: a study of the robustness, evolvability, and accessibility in linear cellular automata. Proceedings of the 12th European Conference on Artificial Life (ECAL), pp.348-355
  • T Hu and JH Moore (2013): Network modeling of statistical epistasis. Biological Knowledge Discovery Handbook: Preprocessing, Mining and Post-processing of Biological Data (Wiley Press), chapter 8, pages 175-189
  • Q Pan, T Hu, and JH Moore (2013): Epistasis, complexity, and multifactor dimensionality reduction. Genome-Wide Association Studies and Genomic Prediction, Methods in Molecular Biology (Humana Press), 1019:465-477
  • C Darabos, M Giacobini, T Hu, and JH Moore (2013): A new mutation paradigm for genetic programming. Genetic Programming Theory and Practice X (Springer Press), 45-58
  • K Krawiec, A Moraglio, T Hu, AS Etaner-Uyar, and B Hu, editors (2013): Proceedings of the 16th European Conference on Genetic Programming (EuroGP), Lecture Notes in Computer Science, vol. 7831
2012
  • AS Andrew, T Hu, J Gu, J Gui, Y Ye, CJ Marsit, KT Kelsey, AR Schned, SA Tanyos, EM Pendleton, RA Mason, EV Morlock, MS Zens, Z Li, JH Moore, and MR Karagas (2012): HSD3B and gene-gene interactions in a pathway-based analysis of genetic susceptibility to bladder cancer. PLoS One, 7(12): e51301
  • T Hu, JL Payne, W Banzhaf, and JH Moore (2012): Evolutionary dynamics on multiple scales: A quantitive analysis of the interplay between genotype, phenotype, and fitness. Genetic Programming and Evolvable Machines, 13(3):305-337
  • NA Lavender, EN Rogers, S Yeyeodu, J Rudd, T Hu, J Zhang, GN Brock, KS Kimbro, JH Moore, DW Hein and LR Kidd (2012): Interaction among apoptosis-associated sequence variants and joint effects on aggressive prostate cancer: a case control study. BMC Medical Genomics, 5(1):11
  • G He, N Xiong, LT Yang, T Kim, CH Hsu, Y Li, and T Hu (2012): Evolvable hardware design based on a novel simulated annealing in an embedded system. Concurrency and Computation: Practice and Experience, 24(4):354-370
  • C Darabos, M Giacobini, T Hu, and JH Moore (2012): Levy-flight GP: towards a new mutation paradigm. Proceedings of the 10th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics (EvoBio), Lecture Notes in Computer Science, 7246:38-49
2011
  • T Hu, NA Sinnott-Armstrong, JW Kiralis, AS Andrew, MR Karagas, and JH Moore (2011): Characterizing genetic interactions in human disease association studies using statistical epistasis networks. BMC Bioinformatics, 12(1):36
  • T Hu, JL Payne, W Banzhaf, and JH Moore (2011): Robustness, evolvability, and accessibility in linear genetic programming. Proceedings of the 14th European Conference on Genetic Programming (EuroGP), Lecture Notes in Computer Science, 6621:13-24 (Nominated Best Paper Award)
2010
  • T Hu and W Banzhaf (2010): Evolvability and speed of evolutionary algorithms in the light of recent developments in biology. Journal of Artificial Evolution and Applications, Article ID:568375
  • T Hu, S Harding, and W Banzhaf (2010): Variable population size and evolution acceleration: a case study with a parallel evolutionary algorithm. Genetic Programming and Evolvable Machines, 11(2):205-225
  • T Hu, Y Chen, and W Banzhaf (2010): WiMAX network planning using adaptive-population-size genetic algorithm. Proceedings of the 7th European Event on the Application of Nature-inspired Techniques for Telecommunication Networks and other Parallel and Distributed Systems (EvoCOMNET), Lecture Notes in Computer Science, 6025:31-40
2009
  • T Hu and W Banzhaf (2009): Neutrality and variability: two sides of evolvability in linear genetic programming. Proceedings of the 18th Genetic and Evolutionary Computation Conference (GECCO), pp.963-980
  • T Hu, Y Chen, W Banzhaf, and R Benkoczi (2009): An evolutionary approach to planning IEEE 802.16 networks. Proceedings of the 18th Genetic and Evolutionary Computation Conference (GECCO), pp.1929-1930
  • G He, Y Li, Z Shi, and T Hu (2009): Intrinsic evolution of digital circuits using evolutionary algorithms. Proceedings of the World Summit on Genetic and Evolutionary Computation (GEC Summit '09 ), pp. 201-208 (Nominated Best Paper Award)
  • T Hu and W Banzhaf (2009): The role of population size in rate of evolution in genetic programming. Proceedings of the 12th European Conference on Genetic Programming (EuroGP), Lecture Notes in Computer Science, 5481:85-96 (Nominated Best Paper Award)
2008
  • T Hu, Y Chen, and W Banzhaf (2008): A genetic algorithmic approach to planning IEEE 802.16 networks. Proceedings of the 18th Newfoundland Electrical and Computer Engineering Conference (NECEC).
  • T Hu and W Banzhaf (2008): Nonsynonymous to synonymous substitution ratio ka/ks: measurement for rate of evolution in evolutionary computation. Proceedings of the 10th International Conference on Parallel Problem Solving from Nature (PPSN), Lecture Notes in Computer Science, 5199:448-457
  • T Hu and W Banzhaf (2008): Measuring rate of evolution in genetic programming using amino acid to synonymous substitution ratio ka/ksProceedings of the 17th Genetic and Evolutionary Computation Conference (GECCO), pp.1337-1338
2007
  • B Zheng and T Hu (2007): A novel multi-objective evolutionary algorithm. Proceedings of the 7th International Conference on Computational Science (ICCS), Lecture Notes in Computer Science, 4490:1029-1036
2006
  • B Zheng, Y Li, and T Hu (2006): Vector prediction approach to handling dynamical optimization problems. Proceedings of the 6th International Conference on Simulated Evolution and Learning (SEAL), Lecture Notes in Computer Science, 4247:353-360
2005
  • W Ding, T Hu, and H Zhang (2005): Multi-objective optimization by a new dynamical evolutionary algorithm based on the information entropy. Proceedings of the 2nd International Conference on Neural Networks and Brain (ICNN&B), vol.1, pp.50-53
  • T Hu, Y Li, and W Ding (2005): A new dynamical evolutionary algorithm based on the principle of minimal free energy. Proceedings of the 1st International Symposium on Intelligence Computation and Applications (ISICA), pp.749-754