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Computational Biology and Genomics at Boston College Biology

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A teaching laboratory equipped with PC laptop computers running LINUX ... Automated detection of somatic mutations in diploid individual samples. Marth et al. ... – PowerPoint PPT presentation

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Title: Computational Biology and Genomics at Boston College Biology


1
Computational Biology and Genomics at Boston
College Biology
Gabor T. Marth Department of Biology, Boston
College marth_at_bc.edu http//clavius.bc.edu/marthl
ab/MarthLab
2
Computational research labs
Prof. Peter Clote
RNA secondary structure and energy
landscape Protein motif recognition
3
Resources
  • CLAVIUS a multi-CPU UNIX computer cluster
  • UNIX development servers
  • A teaching laboratory equipped with PC laptop
    computers running LINUX over VMWARE
  • A professional new server room under construction

4
The CompBio teaching program
  • Currently part of the Biology graduate program
    (PhD only)
  • We have 2 Bioinformatics graduate students with
    a larger class expected for Fall 2006
  • Curriculum combines Biology, Computer Science,
    Math and Statistics courses
  • We are working towards an inter-departmental
    Bioinformatics / Computational Biology PhD program

5
The Computational Genetics Lab
http//clavius.bc.edu/marthlab/MarthLab
6
Sequence variations (polymorphisms)
The Human Genome Project has determined a
reference sequence of the human genome
However, every individual is unique, and is
different from others at millions of nucleotide
locations
sequence polymorphisms
7
Why are sequence variations important?
source of phenotypic difference
allow tracking ancestral human history
8
1. Polymorphism discovery tools
Polymorphism discovery in clonal sequences
Marth et al. Nature Genetics 1999
9
2. Mining genetic variation data
Cataloguing all naturally occurring normal
sequence polymorphisms
10
Genetic and epigenetic changes in cancer
11
3. Demographic inference
12
Data statistical distributions
1. marker density (MD) distribution of number of
SNPs in pairs of sequences
Clone 1 Clone 2 SNPs
AL00675 AL00982 8
AS81034 AK43001 0
CB00341 AL43234 2
SNP Minor allele Allele count
A/G A 1
C/T T 9
A/G G 3
13
Models mathematical and simulation
stationary
expansion
collapse
bottleneck
past
history
present
MD (simulation)
AFS (direct form)
Marth et al. PNAS 2003
14
Conclusions based on model fitting
European data
African data
Marth et al. Genetics 2004
15
4. Medical Genetics
The polymorphism structure of individuals follow
strong patterns
http//pga.gs.washington.edu/
16
3. An international project is under way to map
out human polymorphism structure
17
we build computational tools to test
sample-to-sample variability for clinical studies
Instead of genotyping additional sets of
(clinical) samples with costly experimentation,
and comparing the variation structure of these
consecutive sets directly
we generate additional samples with
computational means, based on our Population
Genetic models of demographic history. We then
use these samples to test the efficacy of
gene-mapping approaches for clinical research.
18
5. We develop methods to connect genotype and
clinical outcome in simple gene systems
genetic marker (haplotype) in genome regions of
drug metabolizing enzyme (DME) genes
clinical endpoint (adverse drug reaction)
computational prediction based on haplotype
structure
molecular phenotype (drug concentration measured
in blood plasma)
functional allele (known metabolic polymorphism)
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