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Gene Regulatory Network
Inference
Progress in Disease Treatment
 Personalized medicine is becoming more
prevalent for several kinds of cancer treatment
 10-Feb-2009 – Breast Bioclassifier developed at
the Huntsman Cancer Institute




1/8 women will be diagnosed with breast cancer
Microarray analysis can separate large group who
need no treatment
Savings in cost and lifestyle
With $100 human genomes, doctors can determine
which drugs will be effective for your genotype
Biological Networks
 Gene regulatory network: two genes are connected
if the expression of one gene modulates expression
of another one by either activation or inhibition
 Protein interaction network: proteins that are
connected in physical interactions or metabolic and
signaling pathways of the cell;
 Metabolic network: metabolic products and
substrates that participate in one reaction;
Background Knowledge
 Cell reproduction, metabolism, and responses to
the environment are all controlled by proteins;
 Each gene is responsible for constructing a single
protein;
 Some genes manufacture proteins which control
the rate at which other genes manufacture proteins
(either promoting or suppressing);
 Hence some genes regulate other genes (via the
proteins they create) ;
What is Gene Regulatory
Network?
 Gene regulatory networks (GRNs) are the on-off
switches of a cell operating at the gene level.
 Two genes are connected if the expression of one
gene modulates expression of another one by either
activation or inhibition
 An example.
Sources: http://www.ornl.gov/sci/techresources/Human_Genome/graphics/slides/images/REGNET.jpg
Why Study GRN?
 Genes are not independent;


They regulate each other and act collectively;
This collective behavior can be observed using
microarray;
 Some genes control the response of the cell to
changes in the environment by regulating other
genes;
 Potential discovery of triggering mechanism
and treatments for disease;
Learning Causal Relationships
 High-throughput genetic technologies
empowers to study how genes interact with
each other;
 If gene A consistently turns on after Gene C,
then gene C may be causing gene A to turn
on
 We have to have a lot of carefully controlled
time series data to infer this
Kegg
 http://www.genome.jp/kegg/pathway.html
Pathgen
Microarray data
Genes
Samples
 Gene up-regulate, down-regulate;
Learning from microarray data
 Recurrent Neural Networks
 Bayesian learning approaches
AIRnet: Asynchronous Inference of
Regulatory networks
1. Classify gene levels using k-means clustering
2. Compute influence vectors (i.v.)
3. Convert i.v.'s into a sorted list of edges
4. Use Kruskal's algorithm to find the minimum-cost spanning
tree
Influence Vectors
1. Perform pairwisecomparisons of change in
gene levels between
samples, adding or
subtracting from i.v.
2. Divide i.v. by the total
number of comparisons
Clockwise from top left:
simulated E.coli 1 network;
E.coli 1 inferred correlations above 50%;
simulated E.coli 2 network;
E.coli 2 inferred correlations above 50%;
inferred networks made using 2 bins for each
gene.
Trisomic network
Euploid network →
Graph showing differences between Euploid and Trisomic
Graph highlighting differences between Euploid and Trisomic
using multiple datasets
DREAM in-silico challenge
Using phylogenetic profiles
to predict protein function
 Basic Idea:
Sequence alignment is a good way to infer protein function,
when two proteins do the exact same thing in two different
organisms.
 But can we decide if two proteins function in the
same pathway?
 Assume that if the two proteins function together
they must evolve in a correlated fashion:

every organism that has a homolog of one of the
proteins must also have a homolog of the other protein
Phylogenetic Profile
 The phylogenetic profile of a protein is a string
consisting of 0s and 1s, which represent the absence
or presence of the protein in the corresponding
sequenced genome;
Protein P1: 0 0 1 0 1 1 0 0
Protein P2: 0 0 1 0 1 1 0 0
Protein P3: 1 0 0 1 0 1 0 0

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For a given protein, BLAST against N sequenced
genomes.
If protein has a homolog in the organism n, set coordinate
n to 1. Otherwise set it to 0.
Phylogenetic Profile
Species
Proteins
Pellegrini M, Marcotte EM, Thompson MJ, Eisenberg D, Yeates TO, Assigning protein functions by comparative genome analysis: protein phylogenetic profiles.
Proc Natl Acad Sci U S A. 96(8):4285-8,. 1999
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