Manuscripts In Progress

  1. Zhang, Y., Song, M. (2013) Deciphering interactions in causal networks without parametric assumptions. arXiv:1311.2707.

Publications

    Google Scholar Mingzhou Song 宋明舟

    NCBI Mingzhou Song

    ResearchGate Mingzhou Song

    ORCID Mingzhou Song

Journal Articles

  1. Kumar, Sajal and M. Song. (2022) “Overcoming biases in causal inference of molecular interactions.” Bioinformatics. (Accepted March 20, 2022)
  2. Tenha, Lovemore and M. Song. (2022) “Inference of trajectory presence by tree dimension and subset specificity by subtree cover,” PLOS Computational Biology, vol. 18, no. 6, pp. e1009829. doi:10.1371/journal.pcbi.1009829
  3. Sharma, Ruby, Zeinab Sadeghian Tehrani, Sajal Kumar and M. Song. (2022) “Detecting genetic epistasis by differential departure from independence.” Molecular Genetics and Genomics. (Accepted March 27, 2022)
  4. Debnath, Tathagata and M. Song. (2021) “Fast optimal circular clustering and applications on round genomes,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 18, no. 6, pp. 2061–2071, 2021. doi:10.1109/TCBB.2021.3077573
  5. Sharma, Ruby, Sajal Kumar, and M. Song. (2021) “Fundamental gene network rewiring at the second order within and across mammalian systems,” Bioinformatics, vol. 37, no. 19, pp. 3293–3301, 2021. doi:10.1093/bioinformatics/btab240
  6. Lovell, John T., Nolan B. Bentley, Gaurab Bhattarai, Jerry W. Jenkins, Avinash Sreedasyam, Yanina Alarcon, Clive Bock, Lori Beth Boston, Joseph Carlson, Kimberly Cervantes, Kristen Clermont, Nick Krom, Keith Kubenka, Sujan Mamidi, Christopher P. Mattison, Maria J. Monteros, Cristina Pisani, Christopher Plott, Shanmugam Rajasekar, Hormat Shadgou Rhein, Charles Rohla, M. Song, Rolston St. Hilaire, Shengqiang Shu, Lenny Wells, Jenell Webber, Richard J. Heerema, Patricia E. Klein, Patrick Conner, Xinwang Wang, L.J. Grauke, Jane Grimwood, Jeremy Schmutz, Jennifer J. Randall. (2021) Four chromosome-scale genomes to accelerate breeding in the outbred and diverse tree nut crop, pecan, Nature Communications, vol. 12, article number 4125, 2021. doi:10.1038/s41467-021-24328-w
  7. Zhang, Sujun, Zhenxing Jiang, Jie Chen, Zongfu Han, Jina Chi, Xihua Li, Jiwen Yu, Chaozhu Xing, M. Song, Jianyong Wu, Feng Liu, Jianhong Zhang, and Jinfa Zhang. (2021) The cellulose synthase (CesA) gene family in four Gossypium species: phylogenetics, sequence variation, and gene expression in relation to fiber quality in Upland cotton, Molecular Genetics and Genomics, vol. 296, no. 2, pp. 355–368, 2021. doi:10.1007/s00438-020-01758-7
  8. Song, M. and H. Zhong. (2020) “Efficient weighted univariate clustering maps outstanding dysregulated genomic zones in human cancers,” Bioinformatics, vol. 36, no. 20, pp. 5027–5036, 2020. doi:10.1093/bioinformatics/btaa613
  9. Han, Zongfu, Y. Qin, X. Li, J. Yu, R. Li, C. Xing, M. Song, J. Wu, and J. Zhang. (2020) A genome-wide analysis of pentatricopeptide repeat (PPR) protein-encoding genes in four Gossypium species with an emphasis on their expression in floral buds, ovules, and fibers in upland cotton, Molecular Genetics and Genomics, vol. 295, no. 1, pp. 55–66, 2020. doi:10.1007/s00438-019-01604-5
  10. Zhong, H. and M. Song. (2019) Directional association test reveals high-quality putative cancer driver biomarkers including noncoding RNAs, BMC Medical Genomics, vol. 12, no. 7, article 129, 2019. doi:10.1186/s12920-019-0565-9
  11. Zhong, H. and M. Song. (2019) A fast exact functional test for directional association and cancer biology applications. IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 16, no. 3, pages 818-826. doi: 10.1109/TCBB.2018.2809743
  12. Barchenger, D. W., J. I. Said, Y. Zhang, M. Song, F. A. Ortega, Y. Ha, B.-C. Kang, and P. W. Bosland. (2018) Genome-wide identification of chile pepper pentatricopeptide repeat domains provides insight into fertility restoration. Journal of American Society for Horticultural Science, vol. 143, no. 6, pp. 418-429. doi: 10.21273/JASHS04522-18
  13. Sharma, R., S. Kumar, H. Zhong, and M. Song. (2017) Simulating noisy, nonparametric, and multivariate discrete patterns. The R Journal, vol. 9, no. 2, pages 366-377. https://doi.org/10.32614/RJ-2017-053
  14. Nguyen, H. H., S. C. Tilton, C. J. Kemp, and M. Song. (2017) Non-monotonic pathway gene expression analysis reveals oncogenic role of p27/Kip1 at intermediate dose. Cancer Informatics, vol. 16, pages 1176935117740132. https://doi.org/10.1177/1176935117740132
  15. Abdelraheem, A., F. Liu, M. Song, and J. F. Zhang. (2017) A meta-analysis of quantitative trait loci for abiotic and biotic stress resistance in tetraploid cotton. Molecular Genetics and Genomics, vol. 292, no. 6, pages 1221-1235. https://doi.org/10.1007/s00438-017-1342-0
  16. Hill, S. M., L. M. Heiser, T. Cokelaer, M. Unger, N. K. Nesser, D. Carlin, Y. Zhang, A. Sokolov, E. Paull, C. K. Wong, K. Graim, A. Bivol, H. Wang, F. Zhu, B. Afsari, L. V. Danilova, A. V. Favorov, W.-S. Lee, D. Taylor, C. W. Hu, B. L. Long, D. P. Noren, A. Bisberg, HPN-DREAM Consortium, G. B. Mills, J. W. Gray, M. Kellen, T. Norman, S. Friend, A. A. Qutub, E. J. Fertig, Y. Guan, M. Song, J. Stuart, P. T. Spellman, H. Koeppl, G. Stolovitzky, J. Saez-Rodriguez, and S. Mukherjee. (2016) Inferring causal molecular networks: empirical assessment through a community-based effort. Nature Methods, vol. 13, no. 4, pages 310-318. https://doi.org/10.1038/nmeth.3773
  17. Wang, H., M. Leung, A. Wandinger-Ness, L. G. Hudson, and M. Song. (2016) Constrained inference of protein interaction networks for invadopodium formation in cancer. IET Systems Biology, vol. 10, no. 2, pages 76-85.
  18. Wang, J., Y. Zhao, I. Ray, and M. Song. (2016) Transcriptome responses in alfalfa associated with tolerance to intensive animal grazing. Scientific Reports, vol. 6, article 19438.
  19. Zhang, J., J. Yu, W. Pei, X. Li, J. Said, M. Song, and S. Sanogo. (2015) Genetic analysis of Verticillium wilt resistance in a backcross inbred line population and a meta-analysis of quantitative trait loci for disease resistance in cotton. BMC Genomics, vol. 16, no. 1, article 577.
  20. Said, J. I., Knapka, J. A., M. Song, and J. Zhang. (2015) Cotton QTLdb: a cotton QTL database for QTL analysis, visualization, and comparison between Gossypium hirsutum and G. hirsutum x G. barbadense populations. Molecular Genetics and Genomics, vol. 290, no. 4, pages 1615-1625.
  21. Zhang, Y., Z. L. Liu, and M. Song. (2015) ChiNet uncovers rewired transcription subnetworks in tolerant yeast for advanced biofuels conversion. Nucleic Acids Research, vol. 43, no. 9, pages 4393-4407. https://doi.org/10.1093/nar/gkv358
  22. Cotton, T. B., H. H. Nguyen, J. I. Said, Z. Ouyang, J. Zhang, and M. Song. (2015) Discerning mechanistically rewired biological pathways by cumulative interaction heterogeneity statistics. Scientific Reports, vol. 5, article 9634.
  23. Said, J. I., M. Song, H. Wang, Z. Lin, X. Zhang, D. D. Fang, and J. Zhang. (2015) A comparative meta-analysis of QTL between intraspecific Gossypium hirsutum and interspecific G. hirsutum x G. barbadense populations. Molecular Genetics and Genomics, vol. 290, no. 3, pages 1003-1025.
  24. Ha, T. J., D. Swanson, M. Larouche, D. Weeden, K. Hamre, M. A. Langston, C. Phillips, M. Song, Z. Ouyang, E. J. Chesler, S. Duvvurru, R. Yordanova, Y. Cui, K. Campbell, G. Ricker, C. Phillips, R. Homayouni and D. Goldowitz. (2015) CbGRiTS: Cerebellar gene regulation in time and space. Developmental Biology, vol. 397, no. 1, pages 18-30.
  25. Song, M., Zhang, Y., Katzaroff, A. J., Edgar, B. A., Buttitta, L. (2014) Hunting complex differential gene interaction patterns across molecular contexts. Nucleic Acids Research, vol. 42, no. 7, pages e57, https://doi.org/10.1093/nar/gku086
  26. Said, J. I., Z. Lin, X. Zhang, M. Song, and J. Zhang (2013) A comprehensive meta QTL analysis for fiber quality, yield, yield related and morphological traits, drought tolerance, and disease resistance in tetraploid cotton. BMC Genomics, vol. 14, no. 1, article 776.
  27. Cruz-Martinez, K., A. Rosling, Y. Zhang, M. Song, G. L. Andersen, and J. F. Banfield. (2012) Effect of rainfall-induced soil geochemistry dynamics on grassland soil microbial communities. Applied and Environmental Microbiology, vol. 78, no. 21, pages 7587-7595.
  28. Marbach, D., Costello, J. C., Kuffner, R., Vega, N., Prill, R. J., Camacho, D. M., Allison, K. R., the DREAM5 Consortium (..., Ouyang, Z., Song, M., Wang, H., Zhang, Y. ...), Kellis, M., Collins, J. J., and Stolovitzky, G. (2012) Wisdom of crowds for robust gene network inference. Nature Methods, vol. 9, no. 8, pages 796-804. Published online 15 July 2012, doi:10.1038/nmeth.2016.
  29. Ouyang, Z., M. Song, R. Gueth, T. J. Ha, M. Larouche, and D. Goldowitz. (2011) Conserved and differential gene interactions in dynamical biological systems. Bioinformatics, vol. 27, no. 20, pages 2851-2858. Advance Access published August 11, 2011. https://doi.org/10.1093/bioinformatics/btr472
  30. Wang, H. and M. Song. (2011) Ckmeans.1d.dp: Optimal k-means clustering in one dimension by dynamic programming. The R Journal, vol. 3, no. 2, pages 29-33. https://doi.org/10.32614/RJ-2011-015
  31. Nguyen, H. and M. Song. (2011) Integrated cellular and gene interaction modeling of pattern formation. International Journal of Computational Biology and Drug Design, vol. 4, no. 4, pages 361-372.
  32. Song, M., R. M. Haralick, and S. Boissinot. (2010) Efficient and exact maximum likelihood quantization of genomic features using dynamic programming. (preprint) International Journal of Data Mining and Bioinformatics, vol. 4, no. 2, pages 123-141.
  33. Hong, C.-C. and M. Song. (2010) Optimal in silico target gene deletion through nonlinear programming for genetic engineering. PLoS ONE 5(2): e9331. https://doi.org/10.1371/journal.pone.0009331
  34. Angeles, J. G. C., Z. Ouyang, A. M. Aguirre, P. J. Lammers, and M. Song. (2009) Identification of gene interactions in fungal-plant symbiosis through discrete dynamical system modeling. IET Systems Biology, vol. 3, no. 5, pages 414-428, September, 2009. doi: 10.1049/iet-syb.2008.0164
  35. Liu, Z. L., M. Ma, and M. Song. (2009) Evolutionarily engineered ethanologenic yeast detoxifies lignocellulosic biomass conversion inhibitors by reprogrammed pathways. Molecular Genetics and Genomics, vol. 282, pages 233-244, doi: 10.1007/s00438-009-0461-7
  36. Song, M., Z. Ouyang, and Z. L. Liu. (2009) Discrete dynamical system modeling for gene regulatory networks of HMF tolerance for ethanologenic yeast. (preprint) IET Systems Biology, vol. 3, no.3, pages 203-218, May 2009.
  37. Song, M., C. K. Lewis, E. R. Lance, E. J. Chesler, R. K. Yordanova, M. A. Langston, K. H. Lodowski, and S. E. Bergeson. (2009) Reconstructing generalized logical networks of transcriptional regulation in mouse brain from temporal gene expression data. EURASIP Journal on Bioinformatics and Systems Biology, vol. 2009, Article ID 545176, 13 pages, doi:10.1155/2009/545176
  38. Song, M. and S. Boissinot. (2007) Selection against LINE-1 retrotransposons results principally from their ability to mediate ectopic recombination. Gene, vol. 390, no.1-2, pages 206-213, April 2007. doi:10.1016/j.gene.2006.09.033
  39. Song, M. and H. Wang. (2006) A spike sorting framework using nonparametric detection and incremental clustering. Neurocomputing, vol. 69, no.10-12, pages 1380-1384, June 2006.
  40. Song, M., R. M. Haralick, F. H. Sheehan, and R. K. Johnson. (2002) Integrated surface model optimization for freehand 3-D echocardiography. IEEE Transactions on Medical Imaging, special issue on 3-D cardiac image analysis, vol. 21, no. 9, pages 1077-1090, September 2002. https://doi.org/10.1109/TMI.2002.804433

Peer-Reviewed Papers in Conference Proceedings

  1. Nguyen, Hien H., Hua Zhong and M. Song, “Optimality, accuracy, and efficiency of an exact functional test,” Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, Main track. pp. 2683–2689, Kyoto, Japan, January 5–10, 2021. doi:10.24963/ijcai.2020/372 (Acceptance rate 12.6%)
  2. Sharma, Ruby, Xuye Luo, Sajal Kumar and M. Song, “Three co-expression pattern types across microbial transcriptional networks of plankton in two oceanic waters,” Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (BCB ’20), Article No.: 14, pp. 1–10, Virtual Event, USA, September 21–24, 2020. doi:10.1145/3388440.3412485
  3. Wang, Jiandong, Sajal Kumar and M. Song, “Joint grid discretization for biological pattern discovery,” Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (BCB ’20), Article No.: 57, pp. 1–10, Virtual Event, USA, September 21–24, 2020. doi:10.1145/3388440.3412415
  4. Tenha, Lovemore and M. Song, “Statistical evidence for the presence of trajectory in single-cell data,” International Symposium on Bioinformatics Research and Applications, December 1–4, 2020. (Accepted)
  5. Kumar, Sajal and M. Song, “Statistical Inference of Discrete Combinatorial Functional Dependency in Biological Systems,” Proceedings of the 14th Machine Learning in Computational Biology (MLCB) Meeting, Vancouver, Canada, December 13–14, 2019. https://mlcb.github.io/mlcb2019 proceedings/papers/paper 24.pdf
  6. Dvoráková, Eliska, Sajal Kumar, Jirı Kléma, Filip Zelezný, Karel Drbal, and M. Song, “Evaluating model-free directional dependency methods on single-cell RNA sequencing data with severe dropout,” Proceedings of International Conference on Bioinformatics Research and Applications (ICBRA), pp. 55–62, Seoul, South Korea, December 19–21, 2019. (Oral presentation) doi:10.1145/3383783.3383793
  7. Kumar, S., H. Zhong, R. Sharma, Y. Li and M. Song. (2018) Scrutinizing functional interaction networks from RNA binding proteins to their targets in cancer. Proceedings of IEEE International Conference on Bioinformatics and Biomedicine, pp. 185-190, Madrid, Spain, December 2-6, 2018. (Oral presentation) https://doi.org/10.1109/BIBM.2018.8621502
  8. Nguyen, H. and M. Song. (2010) Integrated cellular and gene interaction model for cell migration in embryonic development. In Proceedings of IEEE International Conference on Bioinformatics and Biomedicine Workshop and Posters, Workshop on Integrative Data Analysis in Systems Biology, pages 229-233, Hong Kong, China, December 18-21, 2010. (Oral presentation)
  9. Ouyang, Z. and M. Song. (2009) Comparative identification of differential interactions from trajectories of dynamic biological networks. Lecture Notes in Informatics, vol. 157, pages 163-172: Proceedings of German Conference on Bioinformatics, Halle, Germany, September 28-30, 2009. (Oral presentation)
  10. Song, M., C.-C. Hong, Y. Zhang, L. Buttitta, and B. A. Edgar. (2009) Comparative generalized logic modeling reveals differential gene interactions during cell cycle exit in Drosophila wing development. Lecture Notes in Informatics, vol. 157, pages 143-152: Proceedings of German Conference on Bioinformatics, Halle, Germany, September 28-30, 2009. (Oral presentation)
  11. Ouyang, Z. and M. Song. (2009) Statistical analysis of discrete dynamical system models for biological networks. In Proceedings of the First International Joint Conferences on Systems Biology, Bioinformatics and Intelligent Computing, pages 472-478, Shanghai, China, August 3-6, 2009. (Oral presentation)
  12. Song, M. and L. Zhang. (2008) Comparison of cluster representations from partial second- to full fourth-order cross moments for data stream clustering. In Proceedings of the Eighth IEEE International Conference on Data Mining, pages 560-569, Pisa, Italy, December 15-19, 2008. (Oral presentation; one of 70 regular papers out of 724 submissions)
  13. Song, M., R. M. Haralick, and S. Boissinot. (2007) Maximum likelihood quantization of genomic features using dynamic programming. In Proceedings of the 6th International Conference on Machine Learning and Applications (ICMLA) , pages 547-553, Cincinnati, OH. December 13-15, 2007. (Oral presentation)
  14. Song, M., C. K. Lewis, E. R. Lance, E. J. Chesler, R. Kirova, M. A. Langston, and S. E. Bergeson. (2007) Inferring transcriptional regulation through logical networks from temporal mouse brain gene expression data, (preprint). In Proceedings of 2nd Conference on Foundations of Systems Biology in Engineering (FOSBE), pages 31-36, Stuttgart, Germany. September 9-12, 2007. (Oral presentation)
  15. Song, M. and L. Z. Liu. (2006) A linear discrete dynamic system model for temporal gene interaction and regulatory network influence in response to bioethanol conversion inhibitor HMF for ethanologenic yeast. Lecture Notes in Bioinformatics -- Systems Biology and Computational Proteomics, LNCS Vol. 4532, pages 77-95, Springer. 2007. (Revised Selected Papers from Joint RECOMB 2006 Satellite Workshops on Systems Biology, and on Computational Proteomics, San Diego, CA, USA, December 1-3, 2006. [Oral presentation])
  16. Song, M. and H. Wang. (2006) Detecting low complexity clusters by skewness and kurtosis in data stream clustering. In Proceedings of the Ninth International Symposium on Artificial Intelligence and Mathematics, Ft. Lauderdale, Florida. January, 2006. (Oral presentation)
  17. Song, M. and H. Wang. (2005) Highly efficient incremental estimation of Gaussian mixture models for online data stream clustering. In Proceedings of SPIE Vol. 5803: Intelligent Computing - Theory and Applications III, pages 174-183, Orlando, Florida. March, 2005.
  18. Song, M., R. M. Haralick, F. H. Sheehan, and R. K. Johnson. (2002) An integrated approach to surface modeling in freehand 3-D echocardiography. Second Joint Meeting of the IEEE Engineering in Medicine and Biology Society and Biomedical Engineering Society, pages 1082-1083, Houston, Texas USA, October 23-26, 2002.
  19. Song, M. and R. M. Haralick. (2002) Optimal multidimensional quantization for pattern recognition. In Proceedings of SPIE Vol. 4875 Second International Conference on Image and Graphics, pages 15-30, Hefei China. August 16-18, 2002.
  20. Song, M. and R. M. Haralick. (2002) Optimal grid quantization. In Proceedings of International Conference on Pattern Recognition, vol. III, pages 444-447, Quebec City, Canada, August 11-15, 2002.
  21. Song, M. and R. M. Haralick. (2002) Optimally quantized and smoothed histograms. Computer Vision, Pattern Recognition and Image Processing, pages 894-897, Durham, North Carolina. March, 2002.
  22. Song, M., R. M. Haralick, and F. H. Sheehan. (2000) Ultrasound imaging simulation and echocardiographic image synthesis. In Proceedings of International Conference on Image Processing, vol.III, pages 420-423. Vancouver, Canada. 2000. [ Abstract | PDF | Postscript ]
  23. Song, M., A. Guo, and R. M. Haralick. (2000) Single view computer vision in polyhedral world: geometric inference and performance characterization. In Proceedings of International Conference on Pattern Recognition, vol.I, pages 766-769. Barcelona, Spain. 2000. [ Abstract | PDF | Postscript ]
  24. Aksoy, S., Ye, M., Schauf, M., Song, M., Wang, Y., Haralick, R.M., Parker, J.R., Pivovarov, J., Royko, D., Sun, C., and Farnebäck, G. (2000) Algorithm performance contest. In Proceedings of International Conference on Pattern Recognition, vol.IV, pages 870-876. Barcelona, Spain. 2000.
  25. Song, M., A. Cai, and J. Sun. (1996) Motion estimation in DCT domain. In Proceedings of International Conference on Communication Technology, vol.2, pages 670-674. Beijing, China. Published by IEEE. New York, NY, USA. 1996. [ Abstract | HTML | PDF ]

Conference Presentations, Abstracts, Posters, and other Publications

  1. Zhang Y., H. Wang, and M. Song. (2013) FUNCHISQ: Deciphering interactions in causal networks. RECOMB/ISCB Conference on Regulatory and Systems Genomics, with DREAM Challenges, Toronto, Canada, Nov 8-12, 2013. (Poster and abstract)
  2. Herrera Jr., C. M., S. D. Palmer, Y. Zhang, J. Xu, and M. Song. (2009) Identification of SNP-SNP interactions in association study by generalized logical network modeling, RECOMB, Tucson, AZ, May 18-21, 2009. (Poster and abstract)
  3. Hong, C.-C. and M. Song. (2009) Optimal in silico target gene deletion through nonlinear programming in genetic engineering. RECOMB, Tucson, AZ, May 18-21, 2009. (Poster and abstract)
  4. Palmer, S. D. and M. Song. (2009) Quantization of multivariate continuous random variables by sequential dynamic programming. In Proceedings of the Computing Alliance of Hispanic-Serving Institutions (CAHSI) Annual Meeting 2009, pages 43-46. Google Headquarters, Mountain View, CA. January 15-18, 2009. (Poster and extended abstract)
  5. Swanson, D. J., T. J. Ha, R. Glenn, Y. Cui, R. Homayouni, M. Berry, E. Tjioe, M. A. Langston, C. Phillips, M. Song, E. J. Chesler, S. Duvvuru, E. Brauer, K. Hamre, and D. Goldowitz. (2008) Gene regulation in time and space (GRiTS): Molecular signatures of cerebellar development. Society for Neuroscience Annual Meeting, Washington, DC, Nov 15-19, 2008. (Poster and abstract)
  6. Ouyang, Z. and M. Song. (2008) Gene regulatory network reconstruction using discrete dynamical system modeling with exact p-values. RECOMB Satellite on Systems Biology and DREAM3 Challenges, Cambridge, MA, Oct 29 - Nov 2, 2008. (Poster and abstract)
  7. Song, M., Y. Zhang, and S. D. Palmer. (2008) Detecting interactions among genes using generalized logical network modeling with permutation tests. RECOMB Satellite on Systems Biology and DREAM3 Challenges, Cambridge, MA, Oct 29 - Nov 2, 2008. (Poster and abstract)
  8. Ouyang, Z. and M. Song. (2008) Evaluation in dynamic system modeling of gene networks. The Second q-bio Conference. Santa Fe, NM. August 6-9, 2008. (Poster and abstract)
  9. Ouyang, Z., J. G. C. Angeles, A. M. Aguirre, and M. Song. (2008) Dynamic system modeling of gene expression in plant-fungi symbiosis. The Second q-bio Conference. Santa Fe, NM. August 6-9, 2008. (Poster and abstract)
  10. Palmer, S. D., C. Luce, F. O. Holguin, C. Sengupta-Gopalan, and M. Song. (2008) Generalized logical networks of metabolomic interactions in alfalfa and Medicago truncatula. The Second q-bio Conference. Santa Fe, NM. August 6-9, 2008. (Poster and abstract)
  11. Herrera Jr., C. M., J. Havstad, E. Berndt, and M. Song. (2008) Computing a generalized logical network from neural codes. The Second q-bio Conference. Santa Fe, NM. August 6-9, 2008. (Poster and abstract)
  12. Chisham, B., W. Phillips, and M. Song. (2008) Analysis of the effect of beverage consumption on gene expression in blood. The Second q-bio Conference. Santa Fe, NM. August 6-9, 2008. (Poster and abstract)
  13. Herrera Jr., C. M., C. Luce, M. Song, and P. Di Lorenzo. (2008) Computing a generative model for neural codes. Computational Neuroscience Meeting: CNS*2008, Portland, OR. July 19-24, 2008. BMC Neuroscience 2008, 9(Suppl I):P124. (Poster and abstract)
  14. Luce, C., M. Song, T. DeSantis, and E. Brodie. (2008) Modeling the interactions among microbial communities under environmental conditions through high density phylogenetic microarrays. Computational Methods in Water Resources, XVII International Conference, San Francisco, CA. July 6-10, 2008. (Oral presentation and abstract)
  15. Song, M. and C. M. Herrera Jr.. (2008) Boolean network modeling of neural spikes. New Mexico Bioinformatics Symposium, Santa Fe, NM. March, 2008. (Poster and abstract)
  16. Song, M. and C. M. Herrera Jr.. (2007) Computing a generative model for neural codes from responses to taste stimuli. Computing Alliance of Hispanic-Serving Institutions, Miami, FL. December, 2007. (Poster and abstract)
  17. Song, M., C. Luce, T. DeSantis, A. Arkin, E. Brodie and G. Andersen. (2007) Generalized logical network modeling of interactions among bacteria in aerosols under meteorological factors using high density phylogenetic microarrays. American Geophysical Union Fall Meeting. San Francisco, CA. December 10-14, 2007 (Poster and abstract)
  18. Song, M., E. R. Lance, C. K. Lewis, E. J. Chesler, R. Kirova, and S. E. Bergeson. (2007) Maximum likelihood quantization and logical networks for modeling biological interactions. The 11th Annual International Conference on Research in Computational Molecular Biology (RECOMB). Oakland, CA. April, 2007. (Poster and abstract)
  19. Song, M. and H. Wang. (2004) Incremental estimation of Gaussian mixture models for online data stream clustering. International Conference on Bioinformatics and its Applications. Fort Lauderdale, FL. 2004. (Poster and abstract)
  20. Song, M. and N. Mullodzhanov. (2004) Modeling and finding gene regulatory network by combining generalized logical network with probability description for state transition and time delay. The 7th International Meeting of the Microarray Gene Expression Data Society, Toronto, September, 2004. (Abstract)
  21. Song, M., S. Boissinot, R. M. Haralick, and I. T. Phillips. (2003) Estimate recombination rate distribution by optimal quantization. In Proceedings of IEEE Computational Systems Bioinformatics Conference, pages 403-406, Stanford CA. August, 2003. (Poster and abstract)
  22. Song, M. and H. T. Lam. (2003) A non-parametric Bayesian framework for spike sorting using optimal quantization. Joint Statistical Meetings, San Francisco CA. August, 2003. (Oral presentation and paper)

Book Chapters

  1. Liu, Z. L. and M. Song. (2009) Genomic Adaptation of Saccharomyces cerevisiae to Inhibitors of the Conversion of Lignocellulosic Biomass to Ethanol. Applied Mycology (eds M. Rai and P. D. Bridge), Chapter 8, pages 136-155, CAB International, 2009.
  2. Song, M. and R. M. Haralick. (2005) Nonparametric pixel appearance probability model using grid quantization for local image information representation (preprint). Medical Imaging Systems Technology: Modalities, Chapter 10, pages 297-329, World Scientific Publishing CO. December, 2005.

Theses

  1. Song, M. (2002) Integrated Surface Model Optimization from Images and Prior Shape Knowledge. Ph.D. Thesis. Department of Electrical Engineering, University of Washington, Seattle, WA. 2002. [ Abstract ]
  2. Song, M. (1999) Ultrasound Imaging Simulation and Echocardiographic Image Synthesis. M.S. Thesis. Department of Electrical Engineering, University of Washington, Seattle, WA. 1999. [ Abstract ]
Joe Song
Last modified: Sun March 27 2022