马占山
MaZS-Photo-CCEEAG.JPG

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)和昆虫学(1997)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(DBG2OLCSPARCSparseAssembler),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 3rd generation 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 3rdGS 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: 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:  

  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—promising in silico biomarkers 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 promising in silico biomarker 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  

 

 

 

 

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