bold: it's me
*: corresponding author

[44] Cory Gardner, Junhao Chen, Christina Hadfield, Zhaolian Lu, David Debruin, Yu Zhan, Maureen Donlin, Tae-Hyuk Ahn*, Zhenguo Lin*, "Chromosome-level subgenome-aware de novo assembly of Saccharomyces bayanus provides insight into genome divergence after hybridization", Genome Research, 2024.

[43] Tong Si, Yunge Wang, Lingling Zhang, Evan Richmond, Tae-Hyuk Ahn, Haijun Gong, "Multivariate Time Series Change-Point Detection with a Novel Pearson-like Scaled Bregman Divergence", Stats, 7, 2, 462-480, 2024.

[42] Kwok Sun Cheng, Pei-Chi Huang, Tae-Hyuk Ahn, Myoungkyu Song, "Tool Support for Improving Software Quality in Machine Learning Programs", Information, 14, 1, 53, 2023.

[41] Piyush Basia, Tae-Hyuk Ahn, Myoungkyu Song, "An IDE Support for Validating Machine Learning Applications in Bioengineering Text Corpora", 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2022.

[40] Kwok Sun Cheng, Tae-Hyuk Ahn, and Myoungkyu Song, "Debugging support for machine learning applications in bioengineering text corpora", 2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC), 2022.

[39] Yassin Mreyoud, Myoungkyu Song, Jihun Lim, and Tae-Hyuk Ahn*, "MegaD: deep learning for rapid and accurate disease status prediction of metagenomic samples", Life, 12, 5, 669, 2022.

[38] Zhaolian Lu, Keenan Berry, Zhenbin Hu, Yu Zhan, Tae-Hyuk Ahn*, and Zhenguo Lin*, "TSSr: an R package for comprehensive analyses of TSS sequencing data", NAR Genomics and Bioinformatics, 3, 4, 2021.

[37] Yongil Yang, Cory Gardner, Pallavi Gupta, Yanhui Peng, Cristiano Piasecki, Reginald J. Millwood, Tae-Hyuk Ahn, and C. N. Stewart Jr., "Novel Candidate Genes Differentially Expressed in Glyphosate-Treated Horseweed (Conyza canadensis)", Genes, 12, 10, 2021.

[36] Scott Lewis, Andrea Nash, Qinghong Li, and Tae-Hyuk Ahn*, "Comparison of 16S and whole genome dog microbiomes using machine learning", BioData Mining, 14, 41, 2021.

[35] A Rajeh, K Wolf, C Schiebout, N Sait, T Kosfeld, RJ DiPaolo* and TH Ahn*, "iCAT: diagnostic assessment tool of immunological history using high-throughput T-cell receptor sequencing", F1000Research, 2021.

[34] Eliza Dhungel, Yassin Mreyoud, Ho-Jin Gwak, Ahmad Rajeh, Mina Rho, and Tae-Hyuk Ahn*, "MegaR: an interactive R package for rapid sample classification and phenotype prediction using metagenome profiles and machine learning", BMC Bioinformatics 22, 25 (IF=3.242), 2021.

[33] Mariah Hassert, Kyle J. Wolf, Ahmad Rajeh, Courtney Shiebout, Stella G. Hoft, Tae-Hyuk Ahn, Richard J. DiPaolo, James D. Brien, Amelia K. Pinto, "Diagnostic differentiation of Zika and dengue virus exposure by analyzing T cell receptor sequences from peripheral blood of infected HLA-A2 transgenic mice", PLOS Neglected Tropical Diseases (IF=4.487), 2020.

[32] Y. Mreyoudand and T.-H. Ahn*, "Deep Neural Network Modeling for Phenotypic Prediction of Metagenomic Samples", in Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (BCB '20), September 21--24, 2020, Virtual Event, USA 2020.

[31] Tim Kosfeld, Jonathan McMillan, Richard J. DiPaolo, Jie Hou*, and Tae-Hyuk Ahn*, "Performance Evaluation of Viral Infection Diagnosis using T-Cell Receptor Sequence and Artificial Intelligence", in Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (BCB '20), September 21--24, 2020, Virtual Event, USA (Acceptance Rate=30%), 2020.

[30] K. Bockerstett, S. Lewis, C. Noto, E. Ford, J. Saenz, N. Jackson, T.-H. Ahn, J. Mills, R. DiPaolo, "Single Cell Transcriptional Analyses Identify Lineage-Specific Epithelial Responses to Inflammation and Metaplastic Development in the Gastric Corpus", Gastroenterology (IF=20.877), 159, 6, 2020.

[29] K. Bockerstett, S. Lewis, K. Wolf, C. Noto, N. Jackson, E. Ford, T.-H. Ahn, R. DiPaolo "Single-cell transcriptional analyses of spasmolytic polypeptide-expressing metaplasia arising from acute drug injury and chronic inflammation in the stomach", Gut (IF=17.943), 69 (6), 1027-1038, 2020.

[28] Mason-Buck, G., Graf, A., Elhaik, E., Robinson, J., Pospiech, E., Oliveira, M., Moser, J., Lee, P.K.H., Githae, D., Ballard, D., Bromberg, Y., Casimiro-Soriguer, C.S., Dhungel, E., Ahn, T., Kawulok, J., Loucera, C., Ryan, F., Walker, A.R., Zhu, C., Mason, C.E., Amorim, A., Syndercombe Court, D., Branicki, W., Labaj, P, "DNA Based Methods in Intelligence - Moving Towards Metagenomics", Preprints, 2020.

[27] Z. Siddiqui, J. Maldonado, J. Grojean, F. Ye, D. Zhang, J. Longtine, T.-H. Ahn*, and H. Guo*, "Rchimerism: An R-Package for Automated Chimerism Data Analysis", The Journal of Molecular Diagnostics (IF=4.426), 22 (1), 21-20, 2020.

[26] A. Paul, D. Lawrence, M. Song, S.-H. Lim, C. Pan, and T.-H. Ahn*, "Using Apache Spark on Genome Assembly for Scalable Overlap-graph Reduction", Human Genomics, (IF=2.942), Vol 13 Supplement 1, 2019.

[25] V. K. Epuri, S. Sakala, T.-H. Ahn, and M. Song, "Tool Support for Managing RepetitiveProgram Changes in Evolving Software", IET Software, (IF=1.07), 2019.

[24] Z. Harris, E. Dhungel, M. Mosior, and T.-H. Ahn*, "Massive Metagenomic Data Analysis using Abundance-Based Machine Learning", Biology Direct, (IF=2.649), 14, 12, 2019.

[23] J. McMillan, Z. Lu, J. Rodriguez, T.-H. Ahn*, and Z. Lin*, "YeasTSS: An Integrative Web Database of Yeast Transcription Start Sites", Database (Oxford), (IF=3.987), Volume 2019, baz048, 2019.

[22] W. Feng, Z. Yu, M. Kang, H. Gong*, and T.-H. Ahn*, "Practical Evaluation of Different Omics Data Integration Methods", in Precision Health and Medicine. W3PHAI 2019. Studies in Computational Intelligence, vol 843. Springer, Cham, 2019.

[21] A. Paul, D. Lawrence, M. Song, S.-H. Lim, C. Pan, and T.-H. Ahn*, "SORA: Scalable Overlap-graph Reduction Algorithms for Genome Assembly using Apache Spark in the Cloud", in proceedings of the 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2018.

[20] K. Wolf, T. Hether, P. Gilchuk, A. Kumar, A. Rajeh, C. Schiebout, J. Maybruck, R. M. Buller, T.-H. Ahn, S. Joyce, R. DiPaolo, "Identifying and Tracking Low Frequency Virus-Specific TCR Clonotypes Using High-Throughput Sequencing", Cell Reports (IF=8.032), VOLUME 25, ISSUE 9, P2369-2378.E4, 2018

[19] M. McCoy, A. Paul, M. Victor, M. Richner, H. Gabel, H. Gong, A. Yoo*, and T.-H. Ahn*, "LONGO: An R Package for Interactive Gene Length Dependent Analysis for Neuronal Identity" , Bioinformatics (IF=5.481), vol. 34, issue 13, pp. i422-428, ISMB-2018, 2018.

[18] Paul, A.J., D. Lawrence, and T.-H. Ahn*, "Overlap Graph Reduction for Genome Assembly using Apache Spark", in Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics. ACM-BCB 2017, ACM: Boston, Massachusetts, USA. poster, p. 613-613, 2017.

[17] T.-H. Ahn, X. Han, and A. Sandu, "Implicit Simulation Methods for Stochastic Chemical Kinetics", Journal of Applied Analysis and Computation (IF=1.063), 5 (3), pp. 420-452, 2015.

[16] M. Land, L. Hauser, S. Jun, I. Nookaew, M. Leuze, T.-H. Ahn, T. Karpinets, O. Lund, G. Kora, T. Wassenaar, S. Poudel, and D. Ussery, "Insights from 20 years of bacterial genome sequencing", Functional & Integrative Genomics (IF=3.889), 15 (2), pp141-161, 2015.

[15] T.-H. Ahn, J. Chai, and C. Pan, "Sigma:Strain-level Inference of Genomes from Metagenomic Analysis for Biosurveillance", Bioinformatics (IF=5.481), vol. 31, issue 2, pp. 170-177, 2015.

[14] T.-H. Ahn, A. Sandu, L.T. Watson, C.A. Shaffer, Y. Cao, and W.T. Baumann, "A Framework to Analyze the Performance of Load Balancing Schemes for Ensembles of Stochastic Simulations", International Journal of Parallel Programming (IF=0.897), Vol. 43 Issue 4, pp 597-630, 2015.

[13] J. Chai, G. Kora, T.-H. Ahn, D. Hyatt, and C. Pan, "FunctionalPhylogenomics Analysis of Bacteria and Archaea using Consistent GenomeAnnotation with UniFam", BMC Evolutionary Biolog (IF=3.027), 14(1):207, 2014.

[12] B. Haider, T.-H. Ahn, B. Bushnell, J. Chai, A. Copeland, and C. Pan, "Omega: an Overlap-graph de novo Assembler for Metagenomics", Bioinformatics (IF=5.481), vol. 30, issue 19, pp. 2717-2722, 2014.

[11] Z. Li, Y. Wang, Q. Yao, N.B. Justice, T.-H. Ahn, D. Xu, R.L. Hettich, J.F. Banfield, and C. Pan, "Diverse and divergent post-translational modification of proteins of closely related bacteria in two growth stages of a natural microbial community", Nature Communication (IF=12.353), 5, article number 4405, 2014.

[10] D. Dechev and T.-H. Ahn, "Using SST/macro for Effective Analysis of MPI-based Applications: Evaluating Large-Scale Genomic Sequence Search", IEEE Access (IF=3.557), vol. 1, pp. 428-435, 2013.

[9] Y. Wang, T.-H. Ahn, Z. Li, and C. Pan, "Sipros/ProRata: a versatile informatics system for quantitative community proteomics", Bioinformatics (IF=5.481), vol. 29, no. 16, pp. 2064-2065, 2013.

[8] T.-H. Ahn and A. Sandu, "Implicit Second Order Weak Taylor Tau-Leaping Methods for the Stochastic Simulations of Chemical Kinetics", Procedia Computer Science, Volume 4, pp 2297-2306, International Conference on Computational Science, ICCS (Acceptance rate = 24%), 2011.

[7] D.A. Ball, T.-H. Ahn, P. Wang, K.C. Chen, Y. Cao, J.J. Tyson, J. Peccoud, and W.T. Baumann, "Stochastic Exit from Mitosis in Budding Yeast: Model Predictions and Experimental Observations", Cell Cycle (IF=3.952), vol. 10, issue 6, pp. 1-11, 2011.

[6] T.-H. Ahn, D. Dechev, H. Lin, H. Adalsteinsson and C. Janssen, "Evaluating Performance Optimizations of Large-Scale Genomic Sequence Search Applications Using SST/macro", in Proceedings of International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2011), Noordwijkerhout, Netherlands, (Acceptance rate: 25/141=17.7%), 2011.

[5] T.-H. Ahn and A. Sandu, "Fully Implicit Tau-Leaping Methods for the Stochastic Simulation of Chemical Kinetics", in Proceedings of the 19th High Performance Computing Symposium (HPC 2011) part of the 2011 Spring Simulation Multiconference, ser. SpringSim '11, Boston, MA, USA: Society for Computer Simulation International, 2011.

[4] T.H. Ahn and A. Sandu, "Parallel Stochastic Simulations of Budding Yeast Cell Cycle: Load Balancing Strategies and Theoretical Analysis", in Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology, ser. BCB '10, New York, NY, USA:ACM, pp. 237-246, (Acceptance rate: 76/307=25%), 2010.

[3] T.-H. Ahn, L. T. Watson, Y. Cao, C. A. Shaffer, and W. T. Baumann, "Cell cycle modeling for budding yeast with stochastic simulation algorithms", Computer Modeling in Engineering and Sciences (IF=0.75), vol. 51, no. 1, pp. 27-52, 2009.

[2] T.-H. Ahn, P. Wang, L.T. Watson, Y. Cao, C.A. Shaffer, and W.T. Baumann, "Stochastic cell cycle modeling for budding yeast", in Proceedings of the 2009 Spring Simulation Multiconference, ser. SpringSim '09, San Diego, CA, USA: Society for Computer Simulation International, pp. 113:1-113:6, 2009.

[1] T.-H. Ahn, Y. Cao, and L.T. Watson, "Stochastic Simulation Algorithms for Chemical Reactions," in Proceedings of the 2008 International Conference on Bioinformatics & Computational Biology, BIOCOMP'08, Las Vegas, Nevada, USA, pp. 431-436, July, 2008.


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