CS 584 Topics in Computational and Life Science
Semester:
Spring 2007
Meeting
Date: Friday
Meeting
Time: 12:50 -- 2PM; 3 – 4PM;
others scheduled as necessary
Coordinators:
Dr. James Lu (jlu@mathcs.emory.edu; 404-712-8638)
Dr.
Kim Gernert (gernert@emory.edu;
404-727-3501)
Objective:
Our objective is to learn.
You want more detail? Well, alright: Computer Science plays
an increasingly important role in the research study of life sciences (and, to
be sure, in nearly all intellectual inquiries[1]). The development and application of
computing techniques, broadly construed, to the study of biology, medicine, and
healthcare carry particular significance due to their obvious societal
benefits. The scholarly inquiry of
a discipline X based on computing can be divided roughly into two types:
computational-X, and X-informatics.
The former focuses on the construction of mathematical models and
numerical solution techniques to analyze and solve problems in X, while the
latter is concerned with the management and processing of data, information,
and knowledge in X. Examples
include computational biology, computational economics, bioinformatics, and
medical informatics.
Our goal in the course is to
sample and to learn about a few modern computational and informatics techniques
in the context of current life science research studies. Towards that end, the course will be
organized around a series of case studies. Upon completing the course, students (and at least one of
the instructors) will have an understanding of how computing techniques are
assisting the advances of science and medicine. Equally important, we hope to learn and understand how these
interdisciplinary inquiries are shaping, directing, and synthesizing new
Computer Science research.
Students will also be in a position to study and explore related topics
on their own after the course.
Organization:
Each case study is based on an
ongoing project directed by a researcher (both Emory and from outside). The researcher will give a seminar on
the project. We will provide
background lectures prior to each project seminar, and follow up with a
discussion.
Grading:
Grading will be on a S/U
basis. Students will be given
written assignments that will organize, summarize, or analyze each case
study. Questions to stimulate
discussion will be distributed after each seminar. We hope to use the collective efforts of students and
instructors to prepare materials that can be useful for future offerings of the
course. Class attendance and
participation will also be important.
Introduction
19
January: Course
Overview, J. Lu
We give a brief overview of how
some related courses are organized elsewhere, and discuss our course objectives
and meta-objectives (in context).
We discuss course organization, administration, and the roles that
students will play in the course.
Keep in mind that this is trial run of what we hope to be a regular
course in the future, so even the best laid plan will not necessarily work out
exactly – but we will do our best.
Reading: Molecular
Biology for Computer Scientist, Lawrence Hunter, 1993.
26
January: Current Biological Research Overview,
K. Gernert
We will give an overview of
biological research and its application towards predictive health studies. Historically, scientists studied a
single molecule or a single biological process at a time. However, technology now allows
researcher to use high-throughput methods in the study of cells, organisms and
disease processes. This ability
has overwhelmed the scientist with experimental data that requires new
computational resources for storage, querying and analysis. Also, as the computational tools are
developed, scientists are now able to evaluate multiple experimental data types
in concert and thus visualize more and more complicated systems. Such applications have opened the door
to predictive health and related fields.
Reading: http://www.systemsbiology.org/Systems_Biology_in_Depth
Protein Function Prediction
2
February: Biology
Preparation, K. Gernert
We will cover the basic concepts of biology which are
measured in many of the case studies to be presented in this course. Biological concepts will include:
cells – the building blocks of life,
genomics: DNA
– the genetic material, its variability and regulation,
transcriptomics:
RNA – the template for protein synthesis, its variable expression
proteomics:
proteins – polymers which are instrumental in biological
structures and processes, their expression, active state, and regulation.
metabolomics:
monitoring of the substrates and end-products of biological reactions,
clinical studies and clinical labs: multiple questionnaires and lab samples
monitoring the health of the patient.
9
February: Open mathematics and statistics discussion with Dr. Sun
Reading:
9
February (Seminar): An Integrated Approach for Protein Function Prediction
Abstract:
Assigning functions to novel proteins is one of the most
important problems in the post-genomic era. Many different sources of genomic
data, such as protein-protein physical interactions, genetic interactions, gene
expression, and domain structure, contain information about protein function.
We developed a novel approach that employs the theory of kernel based Markov
random fields to infer a protein's functions using an integrated approach
combining various sources of biological data. The model is flexible in that
other protein pairwise relationship information and features of individual
proteins can be easily incorporated. We apply our integrated approach to
predict functions of yeast proteins and in mouse.
Time: 3PM
Room: W201
Speaker: Dr. Fengzhu Sun
Biosketch: Dr. Sun
is an Associate Professor of Molecular and Computational Biology and
Mathematics at USC. His bachelors in Mathematics is from Shandong University,
Masters in Probability and Statistics is from Peking University, and PhD in
Applied Mathematics is from University of Southern California. Dr. Sun was an
assistant professor of genetics and biostatistics at Emory University from 1995
to 2000.
16
February:
Discussion and Summary
Pattern Generation
and Homestasis in Small Neural Networks
23
February: Biology
Preparation, A. Prinz
I would like to spend the class time introducing the students to the
problem of high-dimensional model parameter spaces, the approach of
exploring them with computational brute force, and some of the things
we have learned about the biology of neuronal systems form it. In the
course of that, the students will get exposed to the neuronal model
database
Reading:
Speaker: Dr. Astrid Prinz
Biosketch: Dr. Prinz is Assistant Professor
of Biology at Emory. She received
her Diploma in Physics from the University of Ulm,
Germany in 1996, and her Ph.D. from the Munich Technical University in 2000.
2
March: Mathematics/CS
open discussion with Dr. Hickey
2
March (Seminar): NeuroVis:
combining dimensional stacking and pixelization to visually
explore multidimensional data
Abstract: Give a description here.
Time: 3PM
Room: W201
Speaker: Dr. Timothy Hickey
Biosketch: Dr. Hickey is Professor and Chair
of Computer Science at Brandeis University. He received his Ph.D. in Mathematics from the University of
Chicago in 1986.
9
March: Discussion
and Summary
The Protective Immunity Project
(PIP)
23
March: Biological
Preparation, C. Martens and V. Hertzberg
The Protective Immunity Project (PIP) is examining immune function in renal transplantation. In particular, the temporal effects of immuno-suppressive drug regimens as well as to challenges with vaccination will be characterized. Flow cytometry (FACS) and gene expression microarray (Affymetrix) data will be collected longitudinally in humans as well as in animal models. Computational challenges include storage of these large, complex datasets, data reduction techniques, and numerical algorithms in modelling. (slides)
30
March: Computational
open discussion, Li Xiong
A discussion of possible data mining techniques to analyze the PIP data. (slides)
Cancer Biomedical
Informatics
6
April:
Patrick McConnell
An Introduction to the Cancer Biomedical Informatics Grid (caBIG) (slides)
13
April:
Christopher Flowers
Developing Information Systems for Cancer Research (slides)
20
April:
James Lu
Querying and Browsing Heterogeneous Data Sources
27
April:
Student Presentations
CS 584 Topics in Computational and Life Science
|
1/19 |
Introduction |
|
J.
Lu |
|
1/26 |
Biology
introduction |
|
K.
Gernert |
|
|
|
|
|
|
2/2 |
Biological
prep |
|
K.
Gernert |
|
2/8 |
|
Seminar
time at GA Tech |
Dr.
Fengzhu Sun, USC |
|
2/9 |
Mathematics
and Statistics prep |
|
Dr.
Fengzhu Sun, USC |
|
2/9 |
|
Seminar
3:00 |
Dr.
Fengzhu Sun, USC |
|
2/16 |
Discussion
on Dr. Sun |
|
Lu,
Gernert |
|
|
|
|
|
|
2/23 |
Biological
prep |
|
Dr.
Astrid Prinz Biology,
Emory |
|
3/2 |
Mathematical
prep |
|
Dr.
Timothy Hickey |
|
3/2 |
|
Seminar
3:00 |
Dr.
Timothy Hickey Brandeis
University |
|
3/9 |
Discussion
on Dr. Hickey |
|
Lu,
Gernert |
|
|
|
|
|
|
3/16 |
Spring
break |
|
|
|
3/23 |
Biological
prep |
|
Dr.
Christine Martens, Surgery Dr.
Vicki Hertzberg, Biostatistics |
|
3/30 |
CS |
|
Dr. Li
Xiong, CS |
|
|
|
|
|
|
4/6 |
CS
Development |
caBIG data structure |
Patrick
McConnell, Duke
University |
|
|
|
|
|
|
4/13 |
Biological
prep |
|
Dr.
Christopher Flowers |
|
4/20 |
CS |
|
Dr.
James Lu |
|
|
|
|
|
|
4/27 |
Student
Presentations |
|
|
|
|
|
|
|