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From: Cold Spring Harbor Laboratory Meetings & Courses <[email protected]>
Date: Tue, Feb 19, 2019 at 7:01 AM
Subject: Statistical Methods for Functional Genomics CSHL Course June/July
2019
To: <[email protected]>


<http://r20.rs6.net/tn.jsp?f=001eEi3nt2omCQ-cDY2LxanCrytaBkSJ6vknasghLfSCU2vZOr9-3FKpkJoDVj1yeeGRkuBNM0FZueDG9SVHN8waBd5ZGDbsCm9digLDKV3lRbWdSZdyrh2MPRhGzMlcLNVdSw3DXVeqI0K7bv_WHD35CwO48F3GoKtQq-QJYUFhrlZoYcok-tBROYP9XMPTxMxauFj6Mnko-4=&c=TcMPwMwV5TGfEnHZEBM9tn5k8imsTsORwVhk9OmFCDAlrwVf7jOVaw==&ch=uLpaFaYtColDw6IxqCWXFxcSWJ-daNW4bI8WVnlratiwljCiEcSJ6A==>
Statistical Methods for Functional Genomics
<http://r20.rs6.net/tn.jsp?f=001eEi3nt2omCQ-cDY2LxanCrytaBkSJ6vknasghLfSCU2vZOr9-3FKpkJoDVj1yeeGRkuBNM0FZueDG9SVHN8waBd5ZGDbsCm9digLDKV3lRbWdSZdyrh2MPRhGzMlcLNVdSw3DXVeqI0K7bv_WHD35CwO48F3GoKtQq-QJYUFhrlZoYcok-tBROYP9XMPTxMxauFj6Mnko-4=&c=TcMPwMwV5TGfEnHZEBM9tn5k8imsTsORwVhk9OmFCDAlrwVf7jOVaw==&ch=uLpaFaYtColDw6IxqCWXFxcSWJ-daNW4bI8WVnlratiwljCiEcSJ6A==>
June 28 - July 11, 2019
Applications Due: March 15
Instructors
Harmen Bussemaker, Columbia University
Sean Davis, National Institute of Health
Michael Love, University of North Carolina, Chapel Hill
Over the past decade, high-throughput assays have become pervasive in
biological research due to both rapid technological advances and decreases
in overall cost. To properly analyze the large data sets generated by such
assays and thus make meaningful biological inferences, both experimental
and computational biologists must understand the fundamental statistical
principles underlying analysis methods. This course is designed to build
competence in statistical methods for analyzing high-throughput data in
genomics and molecular biology.
Topics

   - The R environment for statistical computing and graphics
   - Introduction to Bioconductor
   - Review of basic statistical theory and hypothesis testing
   - Experimental design, quality control, and normalization
   - High-throughput sequencing technologies
   - Expression profiling using RNA-Seq and microarrays
   - In vivo protein binding using ChIP-Seq
   - High-resolution chromatin footprinting using DNase-Seq
   - DNA methylation profiling analysis
   - Integrative analysis of data from parallel assays
   - Representations of DNA binding specificity and motif discovery
   algorithms
   - Predictive modeling of gene regulatory networks using machine learning
   - Analysis of posttranscriptional regulation, RNA binding proteins, and
   microRNAs

Please click this link to go to the Statistical Methods for Functional
Genomics course website for more info.
<http://r20.rs6.net/tn.jsp?f=001eEi3nt2omCQ-cDY2LxanCrytaBkSJ6vknasghLfSCU2vZOr9-3FKpkJoDVj1yeeGRkuBNM0FZueDG9SVHN8waBd5ZGDbsCm9digLDKV3lRbWdSZdyrh2MPRhGzMlcLNVdSw3DXVeqI0K7bv_WHD35CwO48F3GoKtQq-QJYUFhrlZoYcok-tBROYP9XMPTxMxauFj6Mnko-4=&c=TcMPwMwV5TGfEnHZEBM9tn5k8imsTsORwVhk9OmFCDAlrwVf7jOVaw==&ch=uLpaFaYtColDw6IxqCWXFxcSWJ-daNW4bI8WVnlratiwljCiEcSJ6A==>
Cold Spring Harbor Laboratory - Meetings & Courses | 1 Bungtown Road, Cold
Spring Harbor, NY 11724
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