Bielawski Group

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group:joe:home [2013/05/06 10:51]
joe 		group:joe:home [2013/05/06 11:38]
joe
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-Dr. Joseph P. Bielawski is an associate professor cross-appointed in the Departments of Biology (75%) and Mathematics & Statistics (25%) at Dalhousie University (Halifax, NS).  Dr. Bielawski did his PhD in Genetics at Texas A&M University, and did his posdoctoral training at the University College London under Dr. Ziheng Yang in the area of computational molecular evolution.+I am an associate professor cross-appointed in the Departments of Biology (75%) and Mathematics & Statistics (25%) at Dalhousie University (Halifax, NS).  Dr. Bielawski did his PhD in Genetics at Texas A&M University, and did his posdoctoral training at the University College London under Dr. Ziheng Yang in the area of computational molecular evolution.
  
 His expertise is in statistical modeling of genes, genomes and metagenomes.  His research group employs models to investigate the process of functional divergence from the gene level to the metagenome level. He is currently working on novel Bayesian models dedicated to metagenome data.  His expertise is in statistical modeling of genes, genomes and metagenomes.  His research group employs models to investigate the process of functional divergence from the gene level to the metagenome level. He is currently working on novel Bayesian models dedicated to metagenome data. 
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 ===== Research interests: ===== ===== Research interests: =====
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 **Statistical modeling of molecular evolution:**  Research within this field is focused on (1) improving Markov models of codon and protein evolution, (2) assessment of model performance, and (3) combining such models with data mining methods for the purpose of genome-scale data analysis. The majority of the work has been with codon models, and my work in this area has had considerable influence on how statistical methods are used to detect adaptive molecular evolution. **Statistical modeling of molecular evolution:**  Research within this field is focused on (1) improving Markov models of codon and protein evolution, (2) assessment of model performance, and (3) combining such models with data mining methods for the purpose of genome-scale data analysis. The majority of the work has been with codon models, and my work in this area has had considerable influence on how statistical methods are used to detect adaptive molecular evolution.
  
group/joe/home.txt ยท Last modified: 2014/11/18 15:08 (external edit)

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