An Algorithmic Approach to Peptide Sequencing via Tandem Mass ....ppt

An Algorithmic Approach to Peptide Sequencing via Tandem Mass Spectrometry
Ming-Yang Kao
Department puter Science
Northwestern University
Evanston, Illinois
U. S. A.
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Collaborators of This Project
University of Southern California
Ting Chen
Harvard Medical School
 
e M. Church
John Rush
Matthew Tepel
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Perspectives
A key goal of bioinformatics: To study biological systems based on global knowledge of genomes, transcriptomes, and proteomes.
Genome: entire sets of materials in the chromosomes.
Transcriptome: entire sets of gene transcripts.
Proteome: entire sets of proteins.
Genome (DNA)  Transcriptome (RNA)  Proteome (Protein)
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Perspectives
A key goal of bioinformatics: To study biological systems based on global knowledge of genomes, transcriptomes, and proteomes.
Genome: entire sets of materials in the chromosomes.
Transcriptome: entire sets of gene transcripts.
Proteome: entire sets of proteins.
Genome (DNA)  Transcriptome (RNA)  Proteome (Protein)
this talk’s focus
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Proteomics
Proteome: all proteins encoded within a genome
half millions distinct proteins (temporal, spatial, modifications)
~30,000 human genes
mRNA and protein expressions may not correlate
Proteomics: study of protein expression by biological systems
relative abundance and stability; post-translational modifications
fluctuations as a response to environment and altered cellular needs
correlations between protein expression and disease state
protein-protein interactions, plexes
Technologies:
2D gel electrophoresis
mass spectrometry
yeast two-hybrid system
protein chips
this talk’s focus
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A Key Step of Proteomics
How to sequence proteins?
How to sequence protein peptides? (this talk’s focus)
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Outline of This Talk
Problem Formulation (Biology)
Problem Formulation (Computer Science)
putational Techniques
plexity and More Robust Algorithms
Conclusions
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Outline of This Talk (1)
Problem Formulation (Biology)
Problem Formulation (Computer Science)
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