6.3 Steven Braun - Improving figure clarity
1:35:57
6.3 Steven Braun - Improving figure clarity
6.6 Nils Gehlenborg-Data, Visualization, and Discovery
1:16:03
6.6 Nils Gehlenborg-Data, Visualization, and Discovery
6.4 Ting Huang-Improving Figure Clarity
1:23:55
6.4 Ting Huang-Improving Figure Clarity
6.1 Jan Vitek-Introduction / Overview of R
1:33:47
6.1 Jan Vitek-Introduction / Overview of R
6.2 Steven Brau-Visualization Foundations Composition and Layout
1:33:10
6.2 Steven Brau-Visualization Foundations Composition and Layout
6.5 Steven Braun-Data Exploration and Linked Views
33:49
6.5 Steven Braun-Data Exploration and Linked Views
7.3 Lev Litichevskiy-Drug Characterization Clustering and Connectivity
56:29
7.3 Lev Litichevskiy-Drug Characterization Clustering and Connectivity
5.6 Naomi Altman- Multiple testing
1:56:10
5.6 Naomi Altman- Multiple testing
7.2 Jacob D. Jaffe-Case Studies in Quantitative Proteomics
1:17:01
7.2 Jacob D. Jaffe-Case Studies in Quantitative Proteomics
7.1 Ruedi Aebersold-Data Generation
1:31:08
7.1 Ruedi Aebersold-Data Generation
5.5 Olga Vitek/ Meena Choi - Challenge in high dimensional studies
1:25:38
5.5 Olga Vitek/ Meena Choi - Challenge in high dimensional studies
5.3 Olga Vitek - Methods for high-throughput biology
1:34:05
5.3 Olga Vitek - Methods for high-throughput biology
5.4 Rafael Irizarry-Bias, Unwanted Variability in High Throughput Technologies
1:40:02
5.4 Rafael Irizarry-Bias, Unwanted Variability in High Throughput Technologies
5.1 Olga Vitek/ Meena Choi - MSstats
1:31:43
5.1 Olga Vitek/ Meena Choi - MSstats
5.2 Olga Vitek - MSstats Normalization and Run Summarization
1:34:57
5.2 Olga Vitek - MSstats Normalization and Run Summarization
4.6 Jan Vitek-Funcion and Functional Programming
1:30:44
4.6 Jan Vitek-Funcion and Functional Programming
4.5 Tsung-Heng Tsai - Tidyverse Iteration Models
1:26:19
4.5 Tsung-Heng Tsai - Tidyverse Iteration Models
4.2 Jan Vitek-Introduction : Overview of R
1:29:33
4.2 Jan Vitek-Introduction : Overview of R
4.8 Kylie Bemis-Performance, Profiling, and Debugging in R
1:20:21
4.8 Kylie Bemis-Performance, Profiling, and Debugging in R
4.7 Kylie Bemis-Object-oriented Programming in R
1:19:06
4.7 Kylie Bemis-Object-oriented Programming in R
4.9 Kylie Bemis - Scalability in R
1:14:35
4.9 Kylie Bemis - Scalability in R
4.3 Sarah Taheri - Notes on how to use R Markdown
53:24
4.3 Sarah Taheri - Notes on how to use R Markdown
4.4 Tsung-Heng Tsai - Tidyverse-data wrangling
31:22
4.4 Tsung-Heng Tsai - Tidyverse-data wrangling
4.1 Tsung-Heng Tsai - Case study and typical operations with base R
55:08
4.1 Tsung-Heng Tsai - Case study and typical operations with base R
1.1 Susan Abbatiello - System Suitability for LC MS
58:15
1.1 Susan Abbatiello - System Suitability for LC MS
1.9 Cyril Galitzine - Nonlinear LOB and LOD estimation
19:58
1.9 Cyril Galitzine - Nonlinear LOB and LOD estimation
1.8 D.R.Mani-Making Sense of LOB, LOD, LOQ in Targeted Proteomics
33:41
1.8 D.R.Mani-Making Sense of LOB, LOD, LOQ in Targeted Proteomics
1.7 Sue Abbatiello-Calibration Curves and Standards
1:28:59
1.7 Sue Abbatiello-Calibration Curves and Standards
1.4 Susan Abbatiello - CPTAC
38:11
1.4 Susan Abbatiello - CPTAC
1.6 Lindsay Pino - Reproducibility, Stability Testing, Repeatibility
1:23:47
1.6 Lindsay Pino - Reproducibility, Stability Testing, Repeatibility