IPAM Fall 2000
Organizing
Committee
Kenneth
Lange, Simon Tavaré, Michael Waterman, Wing Wong
Program period: Sept. 18-Dec 15, 2000
|
Sept. 18 |
Orientation |
|
Sept. 19-27 |
Tutorials |
|
Oct. 11-15 |
Expression Array Technologies and Methods of Analysis |
|
Nov. 8-12 |
Expression Arrays, Genetic Networks and Diseases |
|
Dec. 11-15 |
Mathematical and Statistical Challenges from Computational Biology |
This program will take place at the Institute for
Pure and Applied Mathematics (IPAM), a new NSF national mathematical sciences
research institute located on the UCLA campus.
Mathematicians, statisticians, computer scientists, and biologists—from
academia and from industry—are all invited to attend.
Funding for participants at all levels is available,
but especially for graduate students and recent PhD’s. Applications to attend the full program are
available at www.ipam.ucla.edu
.
Program
Activities:
Seminar Series I
·
Biological
problems, experimental approaches and new technology.
·
Speakers
to be drawn from participating biologists and scientists from various academic
and industry laboratories.
·
To
be run by senior participants. Weekly.
Seminar Series II
·
Mathematical,
statistical and computational problems in functional genomics and expression
array analysis.
·
To
be run by senior participants. Weekly.
Seminar Series III:
Postdoc Seminars. Weekly.
Brainstorming Seminar
·
Organized
by UCLA Bioinformatics Institute—Chris Lee
Statistical Genetics Course
·
Biomath
207A, by Ken Lange. Open to IPAM participants.
High Dimensional Data Sets Course
·
Statistics
216, by Ker-Chau Li. Open to IPAM
participants.
Special
Events:
Orientation
·
September
18, Monday
·
At
May’s Landing, Malibu
Tutorials:
·
September
19-27
·
Terry
Speed: “Overview of Computational Biology for Mathematical Scientists” (9-10
lectures)
·
Gary
Churchill: “Experimental Design and Data Analysis for Gene Expression
Microarrays" (3 lectures)
·
Tim
Triche, "Gene Expression Profiling as Indices of Biologic and Clinical
Behavior in Cancer: Comparison of Clustering Methods and Correlative Biologic
Indicators" (3 lectures)
·
Chris
Lee, TBA
·
Roger
Brent, TBA
Workshop
on “Expression Array Technologies and Methods of Analysis” (October 11-15).
·
Organizing
committee: Fred Fox (UCLA), Mel Kronick (Agilent), Michael Waterman (USC).
·
Discussion
of current and future technology for gene expression monitoring
·
Methods
for analysis of information generated by such technologies.
·
Representatives
from major companies in this area e.g. Affymetrix, Incyte, Agilent, Rosetta,
Illumina, Gene Logic, etc
Workshop on “Expression arrays, Genetic Networks and
Diseases” (November 8-12).
·
Organizing
committee: Rich Simon (NCI), Simon Tavaré (USC), Terry Speed (Berkeley).
· Application of expression arrays to the study and diagnosis of major diseases such as cancer and allergy
· Complex gene regulation network in the cell.
Meeting on “Mathematical and Statistical Challenges from Computational Biology” (December 11-15).
·
Organizers:
Peter Bickel (Berkeley), Ken Lange (UCLA), Wing Wong (UCLA).
·
To
be held in the UCLA Conference Center in Lake Arrowhead.
Scientific
Content of the Program:
The genes of all cells are composed of DNA. Proteins
serve as structural components as well as enzymes within cells but the genes
contain the blueprints for each protein and the program for controlling the
production of proteins. Genes are transcribed to produce complementary
molecules of mRNA (messenger RNA) and the mRNA is translated to proteins. There
is a one to one correspondence (almost) between genes and proteins. Proteins
perform the work of cells such as energy production, reaction catalysis,
inter-cellular signaling, transcription and translation, cell reproduction,
etc. All cells of an organism contain the same DNA. The level of production of
the each of the types of proteins specifies the state of a cell. This state is
determined by spatial and temporal variables such as tissue location and extra-cellular
stimuli. Level of production of a
protein is determined primarily by level of
transcription of the corresponding gene into mRNA.
With the recent development of gene expression
arrays, it has become possible to simultaneously measure the level of expression
of thousands of genes by measuring the amount of each type of mRNA present in a
collection of cells. This is done by printing DNA samples at high density onto
a microscope slide to create a DNA microarray that can be used, through
hybridization, to probe a complex mixture of RNA or cDNA molecules derived from
a particular cell source. Alternatively, oligonucleotide probes for the mRNA or
cDNA molecules can be directly synthesized at very high density onto microchips
by photo-litography or ink-jet technology.
Biologists will study differences in gene expression among cell types to
elucidate the steps of normal development and tissue differentiation. By
examining the level of gene expression in cell populations of disease and
pre-disease states, investigators will attempt to understand the steps of
disease development and to identify the genes involved in disease
susceptibility and gene-environment interactions. Currently DNA microarrays
contain 10,000-20,000 of the complement of approximately 75,000 human genes.
Within the next 2 years it is anticipated that microarrays will be produced
that contain DNA from almost all human genes.
The greatest hurdles to the effective development
and use of DNA microarrays are problems of mathematics and statistics. There
are key problems of image analysis of the fluorescent signals for which
improved solutions are needed. There are difficult problems of combinatorial
mathematics for the design of oligonucleotides in the related development of
oligo-arrays that are
useful for new sequencing and genotyping methods.
There are challenging problems of how to elucidate genetic networks based on
time-sequenced gene expression data. There are important problems of how to
classify cells based on expression pattern and how to develop diagnostic
disease classifications systems. Because of the high dimensionality of the data
obtained from microarray experiments, there are many challenging problems of
multiplicity and multivariate analysis that must be addressed. DNA microarrays
will finally provide the data to attempt to understand simple organisms as
entire systems and this will require new levels of collaboration among
mathematical scientists and biologists.
The goal of this program is to bring leading
investigators in this area into contact with other mathematicians and
statisticians, especially those of the younger generation, who are interested
in participating in these interdisciplinary research areas. Such a program will
serve the timely and important function of disseminating the current scientific
issues to the wider mathematical community. It will also provide an opportunity
for active researchers to interact closely and intensely. As is often the case
in emerging fields, although it is clear that mathematics will play a central
role in the future progress of these areas, the mathematical formulations have
not been sufficiently developed. A major goal of the program is to help to
identify and crystallize the formulation of the mathematical, statistical and
computational issues, and to form a working group of interdisciplinary
researchers.
Partial list
of scientists who have agreed to participate and spend
significant
time (from 7 days to 3 months) at the Institute:
Gary Churchill, Jackson Laboratory
Jean-Michel Claverie, IGS, Marseilles
David Haussler, U.C. Santa Cruz
Mel Kronick, Agilent Technologies
Kenneth Lange, U.C. Los Angeles (co-organizer)
Bud Mishra, Courant Institute
Pete Smietana, GeneLogic
Richard Simon, National Institute of Health.
Terry Speed, U.C. Berkeley and Hall Institute of
Medical Research, Melbourne
Simon Tavaré, University of Southern California
(co-organizer).
Michael Waterman, University of Southern California
(co-organizer).
Wing Hung Wong, U.C. Los Angeles (co-organizer).
(Additional senior participants will be invited)
In addition, there will be short term visitors
including representatives
from various academic experimental groups, and from
related biotechnology
companies such as Roche Bioscience, Affymetrix,
Agilent and Rosetta.
Funding:
Substantial funding is available, especially for
advanced graduate students and post-docs, for those who want to attend the full
program. Please contact us if you are
interested or get an application via the IPAM website.
Contact:
Institute for Pure and Applied Mathematics (IPAM)
e-mail: ipam@ucla.edu
web: www.ipam.ucla.edu