CSCE 496/896, Section 004

Computational Methods in Bioinformatics

Fall 2014

Course description

An advanced course that introduces computational methods for understanding biological systems at the molecular level. Topics include bio-sequence analysis, motif finding, structure prediction, phylogenic inference, regulation network analysis, and high-throughput biological data analysis such as microarray, mass spectrometry and sequencing analysis. Specifically, we will teach the students in this class the following:


  • A general introduction to the field of bioinformatics

–      what problems people have been and are currently working on

–      how people solve these problems

–      what key computational techniques are used and needed

–      how much help computing has provided to biological research

  • A way of thinking -- tackling “biological problem” computationally

–      how to look at a “biological problem” from a computational point of view

–      how to collect statistics from biological data

–      how to build a “computational” model

–      how to solve a computational modeling problem algorithmically

  • Some exposure to computational biology and bioinformatics research

–      what are the main research areas

–      key challenges

–      available tools and resources

  • Basic topics of bioinformatics, covering

–      computational genomics

–      computational proteomics

–      structural bioinformatics

–      computational systems biology

Lecture times and location

12:30-1:20pm Monday, Wednesday and Friday in Avery 19


Dr. Juan Cui,

Office location: 122B, Avery Hall

Office phone: 402-472-5023  


Office hours: M/W/F 2:30-4:00pm and by appointment



Senior or graduate standing in computer science, biology, mathematics, or statistics, or permission of instructor.


Text book

Required reading including the first Chapter of book “Current topics in computational molecular biology, T Jiang, Y Xu and MQ Zhang, MIT Press, 2002” and Primer on Molecular Genetics, US Department of Energy. Handouts will be uploaded to the course website.  

Course schedule:   

–      Overview  ( 8/25)

–      Sequence comparison ( 8/27-)

–      Genome barcode  (9/2)

–      Gene finding (9/5)

–      Regulatory binding motif prediction (9/12)

–      Gene expression and microarray data analysis (9/22)

–      Next generation sequencing data analysis (-9/26))

–      Protein identification (-10/13)        

–      Protein structure and function prediction (10/22)

–      MD simulation of protein structures

–      RNA structure prediction and RNA gene finding

–      Comparative genome analysis

–      Biological pathway prediction

–      Dynamics simulation of regulatory and metabolic networks

–      Review

–      Final exam (3:30 to 5:30 p.m., Tuesday, Dec 16)

Coursework and grading

There will be homework after each topic and one take take-home final exam.

  • Class participation  -: 10%
  • Homework  -: 40%
  • Project  –: 20%
  • Final take-home exam  -: 30%


Support on-line materials (to be updated)

Bioinformatics: alive and kicking (

Perl for bioinformatics/BioPerl ( and Google "beginning perl for bioinformatics pdf")

OBRC: Online Bioinformatics Resources Collection (


CSE and UNL policies

You must abide by the Computer Science and Engineering academic integrity policy: Please make sure to properly cite any sources you use and do not plagiarize. Any cheating or plagiarism will be reported to the Chair of your department and your Dean, and will result in an F for the course.