Computing in the Biosciences

EECS researchers examine fundamental problems in biology and how principles and technologies of computing can be applied to life sciences. They advance computational methods and tools for applications in biological, biochemical, and medical fields. Interdisciplinary research in biosciences at KU includes modeling, analysis, data management, and algorithm optimization.

A server stack
EECS researchers are searching for the causes of cancer and Autism, among numerous other projects supported by the high performance computing facility. The Bioinformatics Computing Facility is undergoing a major renovation that will increase computing power by 20 fold.

Program Objectives

  • Understand basic concepts and fundamental problems in biology.
  • Understand fundamental principles and technologies of computing in biosciences.
  • Understand how to apply and adapt computational methods to address life sciences problems, particularly bioinformatics problems.
  • Have the ability to effectively communicate to impact technological decisions.

Associated Faculty

Arvin Agah
Arvin Agah
Charles E. & Mary Jane Spahr Professor
 agah@ku.edu
 785-864-8821
 http://people.eecs.ku.edu/~agah/
 3018 Eaton Hall

Primary Research Interests

  • Applied Artificial Intelligence
  • Autonomous Mobile Robots
Jerzy Grzymala-Busse
Jerzy W Grzymala-Busse
Professor Emeritus
 jerzygb@ku.edu
 785-864-4488
 https://people.eecs.ku.edu/~jerzygb/index.html
 3014 Eaton Hall

Primary Research Interests

  • Data mining
  • Knowledge discovery
  • Machine learning
  • Expert systems
  • Reasoning under uncertainty
  • Rough set theory
Jim Miller
James R. Miller
Associate Professor Emeritus
 jrmiller@ku.edu
 785-864-7384
 http://people.eecs.ku.edu/~miller/
 2036 Eaton Hall

Primary Research Interests

  • Computer Graphics
  • Visualization
  • Geometric Modeling
  • Technology in Education
Suzanne Shontz
Suzanne Shontz
Professor
 shontz@ku.edu
 785-864-8816
 http://people.eecs.ku.edu/~shontz
 Eaton Hall 1D

Primary Research Interests

  • High Performance Scientific Computing Algorithms
  • Parallel Unstructured Mesh and Optimization Algorithms
  • Model Order Reduction
  • Computational Medicine
  • Image Processing
Cuncong Zhong
Cuncong Zhong
Assistant Professor
 cczhong@ku.edu
 785-864-8825
 https://cbb.ittc.ku.edu/
 2026 Eaton Hall

Primary Research Interests

  • Bioinformatics and Computational Biology
  • Genomics
  • Metagenomics
  • Genetics
  • Non-coding RNA

Associated Facilities

Artificial intelligence development tools and languages:

  • Lisp, CLOS, CLIPS, Prolog, GBB, OPS, MEM-1

Computational clusters:

  • Linux cluster with 64 dual processor 3.2 Ghz Xeon processors and 64 dual core 2.8 Ghz Xeon processors for a total of 384 processors 37 TB of on-line storage Reconfigurable floating-point gate arrays

Bioinformatics software including:

  • ClustalW, Emboss GENSCAN, hmmer, Ncbi toolkit

Data mining tools:

  • SNOB, Cobweb, ID3, C4.5, statistical analysis packages, LERS Genomics Unified Schema installation

Information retrieval and Web tools:

  • KUIR Information Retrieval Library
  • Parallel development tools including MPI, Pfortran, and PC
  • Parallel GROMOS for molecular dynamics

Associated Disciplines

Associated Programs

Core Coursework (MS)

Courses

Elective Coursework (MS)

Courses