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Winston Haynes

Showing results (1-10 of 19) with videos related to

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Omics : a Journal of Integrative Biology|June 24, 2010
Meta-analysis for protein identification: a case study on yeast dataRoger Higdon, Winston Haynes, Eugene Kolker
Metabolites|June 25, 2014
Integrative analysis of longitudinal metabolomics data from a personal multi-omics profileLarissa Stanberry, George I Mias, Winston Haynes, et al.
Mabs|April 26, 2024
Applications and challenges in designing VHH-based bispecific antibodies: leveraging machine learning solutionsMichael Mullin, James McClory, Winston Haynes, et al.
Nucleic Acids Research|December 6, 2011
MOPED: Model Organism Protein Expression DatabaseEugene Kolker, Roger Higdon, Winston Haynes, et al.
Omics : a Journal of Integrative Biology|August 4, 2011
Classifying proteins into functional groups based on all-versus-all BLAST of 10 million proteinsNatali Kolker, Roger Higdon, William Broomall, et al.
Big Data|July 23, 2016
Unraveling the Complexities of Life Sciences DataRoger Higdon, Winston Haynes, Larissa Stanberry, et al.
Journal of Proteomics|May 26, 2011
SPIRE: Systematic protein investigative research environmentEugene Kolker, Roger Higdon, Phil Morgan, et al.
Omics : a Journal of Integrative Biology|April 12, 2011
Bioinformatics and data-intensive scientific discovery in the beginning of the 21st centuryRoger Barga, Bill Howe, David Beck, et al.
Big Data|July 22, 2016
A Case Study: Analyzing City Vitality with Four Pillars of Activity-Live, Work, Shop, and PlayMatt Griffin, Blake W Nordstrom, Jon Scholes, et al.
Nature Communications|November 11, 2018
Leveraging heterogeneity across multiple datasets increases cell-mixture deconvolution accuracy and reduces biological and technical biasesFrancesco Vallania, Andrew Tam, Shane Lofgren, et al.
Pageof 2

Showing results (1-10 of 19) with videos related to

Sort By:
Pageof 2
Omics : a Journal of Integrative Biology|June 24, 2010
Meta-analysis for protein identification: a case study on yeast dataRoger Higdon, Winston Haynes, Eugene Kolker
Metabolites|June 25, 2014
Integrative analysis of longitudinal metabolomics data from a personal multi-omics profileLarissa Stanberry, George I Mias, Winston Haynes, et al.
Mabs|April 26, 2024
Applications and challenges in designing VHH-based bispecific antibodies: leveraging machine learning solutionsMichael Mullin, James McClory, Winston Haynes, et al.
Nucleic Acids Research|December 6, 2011
MOPED: Model Organism Protein Expression DatabaseEugene Kolker, Roger Higdon, Winston Haynes, et al.
Omics : a Journal of Integrative Biology|August 4, 2011
Classifying proteins into functional groups based on all-versus-all BLAST of 10 million proteinsNatali Kolker, Roger Higdon, William Broomall, et al.
Big Data|July 23, 2016
Unraveling the Complexities of Life Sciences DataRoger Higdon, Winston Haynes, Larissa Stanberry, et al.
Journal of Proteomics|May 26, 2011
SPIRE: Systematic protein investigative research environmentEugene Kolker, Roger Higdon, Phil Morgan, et al.
Omics : a Journal of Integrative Biology|April 12, 2011
Bioinformatics and data-intensive scientific discovery in the beginning of the 21st centuryRoger Barga, Bill Howe, David Beck, et al.
Big Data|July 22, 2016
A Case Study: Analyzing City Vitality with Four Pillars of Activity-Live, Work, Shop, and PlayMatt Griffin, Blake W Nordstrom, Jon Scholes, et al.
Nature Communications|November 11, 2018
Leveraging heterogeneity across multiple datasets increases cell-mixture deconvolution accuracy and reduces biological and technical biasesFrancesco Vallania, Andrew Tam, Shane Lofgren, et al.
Pageof 2