ECE 497/597 Special Topics: Bioinformatics Algorithms and Computing Hardware (Fall 2009)

Class meeting time:	Mondays and Wednesdays 12:15-1:30pm
Class location:	MEC 206

Syllabus
  
    PDF  

Textbook

    Dan E. Krane and Michael L. Raymer, Fundamental Concepts of Bioinformatics, Benjamin Cummins, 2003, ISBN 9780805346336 


There will be three main segments to this course:
I) Molecular biology and bioinformatics (8/24 through 10/5)
II) Some bioinformatics algorithms in detail and efficient algorithm implementation in software (10/7 through 10/28)
III) Hardware for acceleration of computationally expensive bioinformatics algorithms (11/4 through 11/30)

The material prior to Exam #1 can be found in the textbook. Supplementary material will be supplied in class
for the remainder of the course.

Schedule

    Date       day         Material Covered in Class   
    8/24        M           Genetic Material & Genes
    8/26        W          Protein Structure & Function

    8/31        M            Sequence Alignment
    9/2          W          Dynamic Programming
 
    9/7          M            Holiday
    9/9          W           Fast Alignment Algorithms & Multiple Alignment

    9/14        M            Phylogenetics
    9/16        W            Phylogenetic Tree Estimation Methods

    9/21        M            Protein-coding Gene Recognition
    9/23        W            Protein Folding

    9/28        M            Exam #1       
    9/30        W            Non-coding RNA (ncRNA) Secondary Structure Prediction

    10/5        M            Non-coding RNA Gene Search with Covariance Models
    10/7        W            Bit-parallel Algorithms

    10/12      M            Multimedia Instruction Sets
    10/14      W            Computational Intelligence (CI) Methods

    10/19      M            Application of CI to ncRNA Structure Prediction           
    10/21      W            Application of CI to Partial Covariance Models

    10/26      M            Improved Covariance Model Parameter Estimation - 1
    10/28      W            Improved Covariance Model Parameter Estimation - 2

    11/2        M            Exam #2
    11/4        W            Cluster Computing

    11/9        M            Application Specific Integrated Circuits
    11/11      W            Case Study: Kestrel

    11/16      M            Field-Programmable Gate Arrays
    11/18      W            Hardware Neural Network Implementations

    11/23      M            Holiday
    11/25      W           Holiday

    11/30      M            Using Video Chips for Bioinformatics Computation
    12/2        W            Exam #3

    12/7        M            TBD topics
    12/9        W            No class (Dr. Smith at conference)


Supplemental Material

Profile HMMs: See PrincetonHMM PDF file in the attachments below.

Covariance models: Read section 2 only of http://scholarworks.boisestate.edu/electrical_facpubs/31/

Example Rfam CM parameter files: See RF00004.cm and RF01108.cm in attachments below.

Kestrel Processor: See Kestrel.pdf and Kestrel2.pdf below.

SAMBA Processor

Folding at Home (Stanford distributed protein folding project)

Bioinformatics hardware companies:
Time Logic
Paracel (no longer sells hardware, but creates software optimized for cluster computing)
CLC bio