Bio-Mathematics and Statistics Seminar
Monday, March 28
3:00 pm, ILB 410
Everyone is welcome to attend.
A Mathematical Habitat for Analyzing
Biological Sequences
Analyzing and classifying sequences based on structural similarities and
differences, no matter how subtle, is a mathematical problem of escalating
relevance and surging importance in many scientific disciplines. One of the
primary challenges in designing machine learning algorithms to analyze
sequential data, such as biological sequences, is the extraction and
representation of significant features from the data.
This talk presents some encouraging results of an ongoing project focused on
the development of a simple mathematical model to map biological sequences
into a set of abstract mathematical spaces. In particular, the talk focuses on
the development of a mathematical habitat for comparing, classifying, and
analyzing various features of biological sequences, both at the ‘micro’ and
‘macro’ level. The talk also briefly presents results of conducted experiments,
directions for future work, and opportunities for collaboration with scholars
from the life sciences.
Can Akkoç
Tom Johnsten
Ryan Benton
University of South Alabama
University of South Alabama
University of Louisiana
at Lafayette
Department
of Math and Statistics
School of Computer and
Information Sciences
Center for Advanced
Computer Studies