The 2017 Dagstuhl Seminar on Computational Proteomics provided an opportunity for a broad discussion on ABSTRACT: The 2017 Dagstuhl Seminar on Computational the current state and future directions of the generation and use of peptide tandem mass spectrometry spectral libraries. Their use in proteomics is growing slowly, but there are multiple challenges in the field that must be addressed to further increase the adoption of spectral libraries and related techniques. The primary bottlenecks are the paucity of high quality and comprehensive libraries and the general difficulty of adopting spectral library searching into existing workflows. There are several existing spectral library formats, but none captures a satisfactory level of metadata;...
Thesis (Ph. D.)--University of Washington, 2003Tandem mass spectrometry is a powerful technology for...
Thesis (Ph.D.)--University of Washington, 2022Over the last 30 years, the field of computational mas...
In this article, current and future applications of spectral clustering are discussed in the context...
The 2017 Dagstuhl Seminar on Computational Proteomics provided an opportunity for a broad discussion...
The 2017 Dagstuhl Seminar on Computational Proteomics provided an opportunity for a broad discussion...
The 2017 Dagstuhl Seminar on Computational Proteomics provided an opportunity for a broad discussion...
The 2017 Dagstuhl Seminar on Computational Proteomics provided an opportunity for a broad discussion...
The 2017 Dagstuhl Seminar on Computational Proteomics provided an opportunity for a broad discussion...
Spectral library searching is an emerging approach in peptide identifications from tandem mass spect...
More and more proteomics datasets are becoming available in public repositories. The knowledge embed...
Spectral library searching is an emerging approach in peptide identification from tandem mass (MS/MS...
Spectral library searching is a new approach in proteomic data analysis that promises to address som...
The characterization of proteins, peptides, metabolites, and natural products are crucial to the und...
Spectral library searching is an emerging approach in peptide identifications from tandem mass spect...
Thesis (Ph.D.)--University of Washington, 2018As the field of proteomics matures, it faces several c...
Thesis (Ph. D.)--University of Washington, 2003Tandem mass spectrometry is a powerful technology for...
Thesis (Ph.D.)--University of Washington, 2022Over the last 30 years, the field of computational mas...
In this article, current and future applications of spectral clustering are discussed in the context...
The 2017 Dagstuhl Seminar on Computational Proteomics provided an opportunity for a broad discussion...
The 2017 Dagstuhl Seminar on Computational Proteomics provided an opportunity for a broad discussion...
The 2017 Dagstuhl Seminar on Computational Proteomics provided an opportunity for a broad discussion...
The 2017 Dagstuhl Seminar on Computational Proteomics provided an opportunity for a broad discussion...
The 2017 Dagstuhl Seminar on Computational Proteomics provided an opportunity for a broad discussion...
Spectral library searching is an emerging approach in peptide identifications from tandem mass spect...
More and more proteomics datasets are becoming available in public repositories. The knowledge embed...
Spectral library searching is an emerging approach in peptide identification from tandem mass (MS/MS...
Spectral library searching is a new approach in proteomic data analysis that promises to address som...
The characterization of proteins, peptides, metabolites, and natural products are crucial to the und...
Spectral library searching is an emerging approach in peptide identifications from tandem mass spect...
Thesis (Ph.D.)--University of Washington, 2018As the field of proteomics matures, it faces several c...
Thesis (Ph. D.)--University of Washington, 2003Tandem mass spectrometry is a powerful technology for...
Thesis (Ph.D.)--University of Washington, 2022Over the last 30 years, the field of computational mas...
In this article, current and future applications of spectral clustering are discussed in the context...