SparseAssembler [二代基因测序组装软件: Sparse k-mer Graph for Memory Efficient de novo Genome Assembly). The core algorithm (Sparse k-mer) was used in BGI’s SoapDenovo-II, the updated version of BGI’s flagship software SoapDenovo]. Available at:
14.Li LW & Ma ZS (2019) Comparative power law analysis for the spatial heterogeneity scaling of the hot-spring and human microbiomes. Molecular Ecology. DOI: http://dx.doi.org/10.1111/mec.15124
15.Ma ZS (2019) A new DTAR (diversity–time–area relationship) model demonstrated with the indoor microbiome. Journal of Biogeography, https://doi.org/10.1111/jbi.13636
16.Ma ZS, Li LW, Ye CX, Peng MS, Zhang YP (2019) Hybrid assembly of ultra-long Nanopore reads augmented with 10×-genomics contigs: Demonstrated with a human genome. Genomics, vol. 110, https://doi.org/10.1016/j.ygeno.2018.12.013
17.Ma ZS & AM Ellison (2018) A unified concept of dominance applicable at both community and species scale. Ecosphere, https://doi.org/10.1002/ecs2.2477.
18.Ma ZS (2018) Extending species-area relationships (SAR) to diversity-area relationships (DAR), Ecology and Evolution, DOI: 10.1002/ece3.4425
19.Ma ZS (2018) Diversity time-period and diversity-time-area relationships exemplified by the human microbiome. Scientific Reports, 8(1):7214.
21.Ma ZS, Li LW, Li W (2018) Assessing and interpreting the within-Body biogeography of human microbiome diversity. Frontiers in Microbiology, 9:1619.
22.Ma ZS, Li LW (2018) Measuring metagenome diversity and similarity with Hill numbers. Molecular Ecology Resources, https://doi.org/10.1111/1755-0998.12923
23.Li W, Yuan Y, Xia Y, Sun Y, Miao Y, Ma ZS (2018) A cross-scale neutral theory approach to the influence of obesity on community assembly of human gut microbiome. Frontiers in Microbiology, 2018.
24.Sun Y, Li LW, Xia Y, Li W, Wang K, Wang L, Miao Y, Ma ZS (2018) The gut microbiota heterogeneity and assembly changes associated with the IBD. Scientific Reports. DOI:10.1038/s41598-018-37143-z
25.Li LW & Ma ZS (2018) Global microbiome diversity scaling in hot springs with DAR (diversity-area relationship) profiles. Frontiers in Microbiology. DOI: https://doi.org/10.3389/fmicb.2019.00118
26.Ma ZS, Li LW (2018) Semen microbiome biogeography: an analysis based on a Chinese population study. Frontiers in Microbiology. DOI: 10.3389/fmicb.2018.03333.
27.Ma ZS, Ye DD (2017) Trios—promising in silico biomarkers for differentiating the effect of disease on the human microbiome network. Scientific Reports, 7(1):13259.
28.Ma ZS (2017) The P/N (Positive-to-Negative Links) ratio in complex networks—a promising in silico biomarker for detecting changes occurring in the human microbiome. Microbial Ecology, vol. 75(4): DOI:10.1007/s00248-017-1079-7.
29.Ma ZS, Li L (2017) Quantifying the human vaginal community state types (CSTs) with the species specificity index. Peer J, 2017, 5(6). DOI: 10.7717/peerj.3366.
30.Chen HJ, Peng S, Dai L, Zou Q, Yi B, Yang X, Ma ZS (2017) Oral microbial community assembly under the influence of periodontitis. PLOS ONE, 12(8):e0182259. doi: 10.1371/journal.pone.0182259.
31.Dai L, Kou H, Xia Y, Wen X, Ma ZS (2017) Does colorectal cancer significantly influence the assembly of gut microbial communities?. Peer J, 5(8):e3383. DOI:10.7717/peerj.3383.
32.Wei L, Xing PW, Su R, Shi G, Ma ZS, Zou Q (2017) CPPred-RF: A Sequence-based predictor for identifying cell-penetrating peptides and their uptake efficiency. Journal of Proteome Research, 2017:acs.jproteome.7b00019.
33.Zou Q, Wan S, Zeng X, Ma ZS (2017) Reconstructing evolutionary trees in parallel for massive sequences. BMC Systems Biology, 11(S6):100. DOI: 10.1186/s12918-017-0476-3.
35.Ye CX & ZS Ma (2016) Sparc: a sparsity-based consensus algorithm for long erroneous sequencing reads. PeerJ. 4:e2016; DOI 10.7717/peerj.2016 https://peerj.com/articles/2016/
36.Ye CX, C Hill, J Ruan, ZS Ma (2016) DBG2OLC: Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies. http://www.nature.com/articles/srep31900
37.Li LW & Ma ZS (2016) Testing the Neutral Theory of Biodiversity with Human Microbiome Datasets. Scientific Reports. 6, Article No. 31448
38.Ma ZS, LW Li, Wendy Li, Jie Li, HJ Chen (2016) Integrated network-diversity analyses suggest suppressive effect of Hodgkin’s lymphoma and slightly relieving effect of chemotherapy on human milk microbiome. Scientific Reports, vol. 6, Article Number 28048, doi:10.1038/srep28048
39.Wang Y, Wang R, Li Y, Ma ZS* (2016) Sex Ratio Elasticity Influences the Selection of Sex Ratio Strategy. Scientific Reports, 2016, 6(1):39807
40.Ma ZS et al (2016) A Brief Review on the Ecological Network Analysis with Applications in the Emerging Medical Ecology. pp7-41, In “Hydrocarbon and Lipid Microbiology Protocols, Springer Protocols Handbooks”. Editors: McGenity T. et al. Springer.
41.Ma ZS et al. (2015) Network analysis suggests a potentially ‘evil’ alliance of opportunistic pathogens inhibited by a cooperative network in human milk bacterial communities. Scientific Reports 5, Article number: 8275
42.Ma ZS (2015) Power law analysis of the human microbiome. Molecular Ecology, vol. 24, DOI: 10.1111/mec.13394.
43.Ma ZS (2015) Towards computational models of animal cognition, an introduction for computer scientists. Cognitive Systems Research 33:42-69
44.Ma ZS (2015) Towards computational models of animal communication, an introduction for computer scientists. Cognitive Systems Research 33:70-99
45.Ye CX, Hill C, Ruan J, Ma ZS* (2014). DBG2OLC: efficient assembly of large genomes using the compressed overlap graph. Paper: http://adsabs.harvard.edu/cgi-bin/bib_query?arXiv:1410.2801 Software: http://sites.google.com/site/dbg2olc/
46.Li H, Ye DD, Wang X, Settles ML, Wang J, Zhou L, Dong P, Ma ZS* (2014) Soil bacterial communities of different natural forest types in China. Plant and Soil 383.
48.Ma, ZS, Liexun Yang, Ronald P. Neilson, Andrew Hess, Richard Millar (2014) A Survivability-Centered Research Agenda for Cloud Computing Supported Emergency Response and Management Systems. 17pp. The 35th IEEE-AIAA Aerospace Conference (Aerospace 2014), Big Sky, Montana, USA, March 7-15th, 2014. doi: 10.1109/AERO.2014.6836515
49.Zhang ZG, Geng JW, Tang XD, Fan H, Xu JC, Wen XJ, ZS Ma*, P. Shi* (2014) Spatial heterogeneity and co-occurrence patterns of human mucosal associated intestinal microbiota. The ISME Journal, doi:10.1038/ismej.2013.185
50.Ma, ZS (2013) Stochastic Populations, Power Law, and Fitness Aggregation in Genetic Algorithms. Fundamenta Informaticae, vol. 122, pp173-206.
51.Ma, ZS (2013) First passage time and first passage percolation models for analyzing network resilience and effective strategies in strategic information warfare research. I. J. Information and Computer Security. 5(4): 334-358.
53.Ma, ZS (2012) A unified definition for reliability, survivability and resilience inspired by the handicap principle and ecological stability. I. J. of Critical Infrastructures, 8(2):242-272.
54.Ma, ZS (2012) A Note on Extending Taylor’s Power Law for Characterizing Human Microbial Communities: Inspiration from Comparative Studies on the Distribution Patterns of Insects and Galaxies, and as a Case Study for Medical Ecology and Personalized Medicine. http://adsabs.harvard.edu/abs/2012arXiv1205.3504M
55.Ye, CX, ZS Ma, CH. Cannon, M Pop and DW. Yu. 2012. Exploiting sparseness in de novo genome assembly. BMC Bioinformatics, 13(Suppl 6):S1.
56.Gajer, P, RM. Brotman, G Bai, J Sakamoto, UME Schütte, X Zhong, SSK Koenig, L Fu, ZS Ma, X Zhou, Z Abdo, LJ Forney and J Ravel. (2012) Temporal Dynamics of the Human Vaginal Microbiota. Science Translational Medicine. 4:(132): 132ra52.
57.Ma ZS et al (2012) A Bird's Eye View of Microbial Community Dynamics. In “Microbial Ecological Theory: Current Perspectives.” Editors: LA Ogilvie and PR Hirsch. Caister Academic Press.
58.Ma, ZS & AW Krings (2011) Dynamic hybrid fault modeling and extended evolutionary Game theory for reliability, survivability and fault tolerance analyses. IEEE Transactions on Reliability. vol. 60(1):180-196.
59.Ma, ZS (2011) Ecological ‘theater’ for evolutionary computing ‘play’: some insights from population ecology and evolutionary ecology. I. Journal of Bio-Inspired Computing 4(1):31-55.
60.Ma, ZS (2011) Did we miss some evidence of chaos in laboratory insect populations? Population Ecology, 53:405–412.
61.Ma, ZS (2011) Frailty modeling for risk analysis in network security and survivability. I. J. Computer and Information Security, 4:276-294.
62.Ma, ZS et al (2011). Insect navigation and communication in flight and migration: a potential model for joining and collision avoidance in MAVs (Micro-Aerial Vehicle) and mobile robots fleet control. Proc. of the 32nd IEEE-AIAA Aerospace Conference. 14pp, Big Sky, Montana, USA.
64.Ma, ZS, et al (2011) Has the cyber warfare threat been overstated? A cheap talk game-theoretic perspective on the Google-hacking claim. The 7th Cyberspace Sciences and Information Intelligence Research Workshop, 7th CSIIRW11. October 14-16, 2011. Oak Ridge National Lab, Oak Ridge, USA.
65.Ma, ZS et al (2011) Caring about trees in the forest: incorporating frailty in risk analysis for personalized medicine. Personalized Medicine, 8(6): 681-688
66.Ma, ZS (2010) Is Strategic Information Warfare Really Asymmetric? —a New Perspective from the Handicap Principle. Journal of Information Warfare, 9(3): 51-61.
67.Ma, ZS (2010) Survival Analysis Approach to Life Table Analysis and Hypothesis Testing for Russian Wheat Aphid Populations. Bulletin of Entomological Research. vol. 100(3): 315-324
68.Ma, ZS et al (2010) Logics in Animal Cognition: Are They Important to Brain Computer Interfaces (BCI) and Future Space Missions? Proc. 31st IEEE-AIAA Aerospace Conference 2010, 8pp. Big Sky, Montana, USA.
69.Ma ZS (2010) An integrated approach to network intrusion detection with block clustering analysis, generalised logistic regression and linear discriminant analysis. I. J. Information and Computer Security. DOI: http://dx.doi.org/10.1504/IJICS.2010.03186
70.Ma ZS (2010) A New Extended Evolutionary Game Theory Approach to Strategic Information Warfare Research. J. of Information Warfare, vol. 8(2).
71.Ma ZS (2010) Towards a Population Dynamics Theory for Evolutionary Computing: Learning from Biological Population Dynamics in Nature. Springer Lecture Notes in Artificial Intelligence, vol. 5855, pp 195-205
72.Ma ZS (2010) Towards an Extended Evolutionary Game Theory with Survival Analysis and Agreement Algorithms for Modeling Uncertainty, Vulnerability, and Deception. Springer Lecture Notes in Artificial Intelligence, vol. 5855, pp 608-618
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