动物进化与遗传前沿交叉卓越创新中心

马占山

马占山，研究员，博导，计算生物与医学生态学学科负责人。美国爱达荷大学计算机科学(2008年)和昆虫学(1997年)双博士，计算机科学和计算生物学研究科学家。具有在美国硅谷等地近10年的涵盖电子、网络、软件、信息安全领域的计算机高级工程师经历, 并曾担任人类微生物菌群研究计划(Human Microbiome Project)主要研发科学家。

受邀为英国“Faculty of 1000 Biology & Medicine”撰写学术评论(2008-2016)。2011年分别入选云南省高端科技人才和海外高层次人才; 2015年入选云岭产业领军人才。在计算机科学、工程数学、计算智能与人工智能、昆虫学、生态学、生物信息学、人类微生物群系宏基因组等领域的重要期刊发表论文近百篇；合作研发出大型基因测序软件（DBG2OLC，SPARC，SparseAssembler)，并申请10多项发明专利。

主要研究方向及内容

1.基因大数据科学、三代基因测序软件技术：合作发布如下软件技术

DBG2OLC; SPARC; SparseAssembler;10x-Genomics-assisted 3GS Hybrid Assembly.

[1] DBG2OLC [三代基因测序组装软件: An ultra efficient de Novo genome assembler for the 3^rdgeneration sequencing technologies (PacBio & Oxford Nanopore)] Available at:

https://sites.google.com/site/dbg2olc/

https://sourceforge.net/projects/dbg2olc/

[2] Sparc [三代基因测序纠错软件: A sparsity-based consensus algorithm for long erroneous 3^rdGS sequencing reads] Available at:

https://sourceforge.net/projects/sparc-consensus/

https://github.com/yechengxi/Sparc

[3] SparseAssembler [二代基因测序组装软件: Sparsek-mer Graph for Memory Efficient de novo Genome Assembly). The core algorithm (Sparsek-mer) was used in BGI’s SoapDenovo-II, the updated version of BGI’s flagship software SoapDenovo] Available at:

https://sites.google.com/site/sparseassembler/

https://sourceforge.net/projects/sparseassembler/

[4]10x-assisted-3GS Hybrid Assembly:

Ma ZS, LW Li, CX Ye, MS Peng, YP Zhang (2018) 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

2.人类微生物群系（菌群）医学生态学理论和方法。

主编《生物信息学：计算技术与软件导论》（科学出版社，该书获国家科技出版基金奖励资助），并在ISME Journal, Ecological Monographs,Molecular Ecology, Science Translational Medicine等发表论文近50篇。

3.网络安全可靠性、可存活性理论、进化博弈论、计算智能、人工智能。

编著：《Reliability, Survivability and Resilience: A Unified Theoretic Approach with

Survival Analysis, Dynamic Hybrid Fault Models and Extended Evolutionary Game Theory》

(in press) Springer.并在IEEE Translations on Reliability等期刊和EI国际会议发表论文30余篇。

代表性论文

Ma ZS, Li LW, Gotelli NJ (2019) Diversity-disease relationships and shared species analyses for human microbiome-associated diseases.The ISME Journal(In revision).

Ma ZS, Ellison AM (2018) Dominance network analysis provides a new framework for studying the diversity-stability relationship.Ecological Monographs. (Accepted)

Ma ZS, Ellison AM (2018) A unified concept of dominance applicable at both community and species scale.Ecosphere, https://doi.org/10.1002/ecs2.2477.

Ma ZS,Li LW, Ye CX, Peng MS, Zhang YP (2018)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

Ma ZS (2018) Extending species-area relationships (SAR) to diversity-area relationships (DAR),Ecology and Evolution, DOI: 10.1002/ece3.4425

Ma ZS (2018) Sketching the human microbiome biogeography with DAR (diversity-area relationship) profiles.Microbial Ecology, vol. 76,https://doi.org/10.1007/s00248-018-1245-6

Ma ZS, Li LW, Li W (2018) Assessing and interpreting the within-Body biogeography of human microbiome diversity.Frontiers in Microbiology, 9:1619.

Ma ZS, Li LW (2018) Measuring metagenome diversity and similarity with Hill numbers.Molecular Ecology Resources, https://doi.org/10.1111/1755-0998.12923

Ma ZS, Ye DD (2017) Trios—promisingin silicobiomarkers for differentiating the effect of disease on the human microbiome network.Scientific Reports, 7(1):13259.

Ma ZS (2017) The P/N (Positive-to-Negative Links) ratio in complex networks—a promisingin silicobiomarker for detecting changes occurring in the human microbiome.Microbial Ecology, vol. 75(4): DOI:10.1007/s00248-017-1079-7.

Ma ZS (2015) Power law analysis of the human microbiome.Molecular Ecology, vol. 24, DOI: 10.1111/mec.13394.

Ma ZS (2013) Stochastic populations, power law, and fitness aggregation in Genetic Algorithms.Fundamenta Informaticae, vol. 122, pp173-206.

Ma ZS (2012) Chaotic populations in Genetic Algorithms. Applied Soft Computing, 12(8): 2409-2424.

Ma ZS & Krings AE (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.

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