hms_9815

hms_9815 - Harvard-MIT Division of Health Sciences and...

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Informational Resources (Finding your way through the Human Genome) Alberto Riva, PhD Children s Hospital Informatics Program Harvard Medical School Genomic Medicine HST 586 Harvard-MIT Division of Health Sciences and Technology HST.512: Genomic Medicine Prof. Alberto A. Riva
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HST 586 - 2/26/04 2 © 2004, Alberto Riva, CHIP The Central Dogma of Molecular Biology DNA RNA Genotype Phenotype mRNA Protein(s) Diversity Disease Drug Response Metabolism Physiology
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HST 586 - 2/26/04 3 © 2004, Alberto Riva, CHIP How is information represented? Where does it come from? Where is it stored? How do we find, retrieve and use it?
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HST 586 - 2/26/04 4 © 2004, Alberto Riva, CHIP From genotype to phenotype The genotype is “digital . ± Each base pair can be precisely represented using one of four symbols (A, T, G, C). ± Approximately 3.2 billion base pairs in the human genome. The phenotype is “analog . ± Proteins are not uniquely determined by their sequence. ± Environmental factors are always present. ± Most phenotypes are qualitative in nature.
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HST 586 - 2/26/04 5 © 2004, Alberto Riva, CHIP From phenotype to genotype Our knowledge progresses in the opposite direction: First studies of inherited traits: Mendel, 1866; (Discovery of DNA: Miescher, 1869); Genes are made of DNA: Hershey and Chase, 1952; DNA replication mechanism: Watson and Crick, 1953; Genetic code decyphering: Nirenberg, 1961-1966; Discovery of introns: Sharp and Roberts, 1977; Human Genome Project: 1990-2003.
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HST 586 - 2/26/04 6 © 2004, Alberto Riva, CHIP From genotype to phenotype “The human genome is an abstraction. ± Single-nucleotide polymorphisms (SNPs), microsatellites (repeats), insertions, deletions, translocations, etc etc… ± On the average, one polymorphism every 1,000 bases. Phenotypes are generalizations: ± Species; ± Ethnicity; ± Diseases.
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HST 586 - 2/26/04 7 © 2004, Alberto Riva, CHIP Data and Methods DNA: ± Sequence matching (BLAST, etc.) ± Gene prediction (Genscan, etc.) ± Homology searches ± SNP detection (genotyping) RNA: ± Alternative splicing, transcriptional rearrangements ± Expression analysis (microarrays) ² Differential analysis ² Clustering
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HST 586 - 2/26/04 8 © 2004, Alberto Riva, CHIP Data and Methods Protein: ± Prediction of active domains ± 3-D structure prediction ± Protein homology and conservation ± Automated construction and analysis of metabolic / regulatory pathways Phenotype: ± Population genetics ± Association studies ± Clinical trials
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HST 586 - 2/26/04 9 © 2004, Alberto Riva, CHIP What is a gene? Classical geneticist: “Gene = smallest unit of inheritance Medical researcher: “Gene = disease-causing trait Molecular biologist: “Gene = recipe for one or more proteins
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HST 586 - 2/26/04 10 © 2004, Alberto Riva, CHIP What is a gene? Biochemist:
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This note was uploaded on 03/27/2008 for the course HST 512 taught by Professor Ramoni during the Spring '06 term at MIT.

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hms_9815 - Harvard-MIT Division of Health Sciences and...

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