BIOL 495: Bioinformatics
Spring 2004
Tentative Course Schedule

Jan 26 - Eisen
Definition of Bioinformatics
Applications of Bioinformatics

• Studies in Evolution
• Drug Development
• Local interest - Biotechnology Board

Feb 2 - Eisen
DNA Structure
DNA Replication

Feb 16 - Merat
Protein structure - Primary through Quaternary
Protein sequencing

Feb 23 - Merat
Protein databases
Protein analysis

Mar 1 - Students
Presentation of project progress reports

Mar 15 - Yanushka
Algorithms for DNA Analysis I

Mar 22 - Yanushka
Algorithms for DNA Analysis II

Mar 29 - Eisen
Alignments & Phylogenetic trees

Apr 5 - Merat
A case study in protein analysis

Apr 12, Apr 19, Apr 26
Research presentations by scientists in the Memphis area. Dr. Malinda Fitzgerald will have a joint meeting with the Biological Careers class to discuss careers in bioinformatics

May 3 - Students
Presentation of student projects in poster session format

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An example of what bioinformatics can do:
Using Math vs. Cancer: Simple test detects early ovarian disease
By Delthia Ricks, STAFF WRITER

December 2, 2003

Ovarian tumors are one of the most difficult cancers to detect in an early stage but researchers at Stony Brook University today report being one step closer to making such a test reality.

The researchers have produced a complex mathematical algorithm to analyze myriad proteins in a mere pinprick-amount of blood from a finger. Such a tool can identify the pattern of proteins present in even the earliest development of ovarian cancer, researchers said.

The team of mathematicians and cancer specialists joined a project begun by two government scientists aiming for a highly accurate detection method, one that ultimately can be used as a mass screening test for ovarian cancer.

"We're very excited about this," said Dr. John Kovach, director of the Long Island Cancer Center at Stony Brook University Hospital. If the test succeeds in several more rounds of study, then scientists will have conducted much of the work required for Food and Drug Administration approval, he said.

Currently, Kovach said, the only test available is used to spot a protein that is usually present in a relatively mature ovarian tumor.

Nearly 25,000 women are diagnosed with the cancer each year, and 14,000 die of it, government figures show.

The mathematical formula, developed by Stony Brook biostatistician Wei Zhu, uses mass spectrometry, technology that measures the thousands of proteins in blood. Her formula helps reveal submicroscopic fragments and trace proteins. Such complexes could prove difficult to spot using conventional laboratory techniques.

"Our algorithm is 100 percent accurate" when used to distinguish samples from a woman with ovarian cancer and those from a woman who is healthy, Zhu said. The test was tried on more than 200 blood samples, about 116 from women with ovarian cancer. The test made no mistakes in either set.

The test is the brainchild of two cancer researchers, Dr. Lance Liotta of the National Cancer Institute and Dr. Emanuel Petricoin of the Food and Drug Administration. They developed the process in collaboration with Maryland-based biotechnology company, Correlogic Systems Inc., and reported preliminary studies last year in the British medical journal The Lancet.

Zhu said the initial mathematics approach was not powerful enough to avoid finding false negatives.

She and her Stony Brook colleagues refined the math and report the results in today's Proceedings of the National Academy of Sciences. She predicts the test may be available within a year or so. Clinical trials to test the technique are now being organized.

Rep. Steve Israel (D-Huntington) last year introduced a bill supporting the science. Israel is encouraged by the notion that such a test can be used on a large scale, much like Pap screening to detect cervical cancer. The Pap test has helped to dramatically reduce the incidence of cervical cancer in the past 50 years.

The new test is based on the arcane field of proteomics, the study of entire protein systems - proteomes - what they do and how they interact with each other. "Our goal was to develop an algorithm for ovarian cancer because ovarian cancer is very deadly when you don't find it early," Zhu said. "When you find it at an early stage, it is 90 percent curable with surgery alone. That's why this test is so important."

Where Ovarian Cancer Ranks

A look at the leading causes of death in the United States:

Cancer 23%
Other 29%
Heart Diseases 30%
Respiratory 4%
Accidents 4%
Diabetes 3%
Stroke / cerebrovascular 7%

Lung / bronchus 31%
Prostate 10%
Colon / rectum 10%
Pancreas 5%
Non-Hodgkin's lymphoma 4%

Lung / bronchus 25%
Breast 15%
Colon / rectum 11%
Pancreas 6%
Ovary 5%

SOURCE: National Center for Health Statistics; American Cancer Society

Copyright © 2003, Newsday, Inc.