Home
Syllabus
ClassNotes
Articles
Student Papers
Bioinformatics Computing - Class Notes

Aug 23

Lecture:

  • Course overview (Collins & Madey)
  • Introduction to the Genome (Collins)

Aug 25

Lecture (Madey):

  • Information flow from the Genome
  • Central Dogma

Aug 30

News:

  • Next class to meet at 9:30 on Friday, Sept 2

Lecture (Madey)

  • Other information in the Genome

Homework:

  • Read Chapters 1 & 2 in Jones & Pevzner

Sept 2

Lecture (Collins):

  • Review of information flow from the genome to function

Sept 6

Lecture (Madey):

  • What is informatics?
  • Web-based information systems
  • Lecture notes

Sept 8

Lecture (Madey):

  • Algorithms
  • Computer Architecture
  • Lecture outline

Homework (for week of Sept 12)

  • Surf links located in the example section of Sept 6 lecture outline (here)
  • Read chapters 3 & 4 Jones & Pevzner

Sept 13

Lecture (Madey):

  • Analysis 2
  • Bioinformatics Databases
  • Database Technology

Homework

  • Surf active links in today's lecture outline (under Schema)

Resources:

  • Bioinformatics job descriptions (just a few!):

Sept 15

Lecture (Madey)

  • More on Database Technology
  • Visualization

Homework

  • Read chapter 3 in Mount

Sept 20

Presentation (Rob Bruggner)

Homework

Sept 22

Presentations

Homework

  • Read Chapter 6 (Dynamic Programming Algorithms) in Jones & Pevzner

Sept 27

Presentations (Ryan Butler, Andrew Sheehan and Neil Lobo)

  • Neil Lobo

Homework

Sept 29

Presentations (Ryan Butler, Andrew Sheehan and John Tan)

  • Ryan Butler and Andrew Sheehan
    • Global Alignment and Multiple Sequence Alignment (slides)
  • John Tan

Homework

  • Read about Hidden Markov Models
    • Mount: pp. 198-217
    • Jones: Chapter 11

Oct 4

Presentations (Brad White and Bryan Cassone)

Homework

  • Read paper on Stochastic Context Free Grammars For tRNA Modeling (pdf)

Oct 6

Guest Presentation

  • Dr. Mark Craven is an Associate Professor in the Department of Biostatistics and Medical Informatics, and in the Department of Computer Sciences at the University of Wisconsin. His presentation to the class::
    • "Stochastic context free grammars for modeling RNA sequences" (slides)
  • Dr. Craven's presentation given in the Computer Science & Engineering seminar:
    • "Machine Learning Applied to Uncovering Gene Regulation" (slides)

Oct 11

Presentation (Scott Christley)

  • Hidden Markov Models - Theory (slides)

Homework

Oct 13

Presentation (Deborah Thomas)

Homework

  • Review 3 papers on transposons
  • Read following on Dynamic Programming
    • Mount, pp. 83-86
    • Jones & Pevzner, Chapter 6
  • Work on problem described in class today
    • Phylogenetic tree shown in class
    • Alignment shown in class
    • Problem data (three parts)
      • Data File 1. Amino acid FASTA file of 50 piggyBac–like sequences.
      • Data File 2. CLUSTAL alignment file of amino acid sequences of 50 piggyBac–like sequences.
      • Data File 3. NEXUS/PAUP file of amino acid sequences of the 50 piggyBac–like sequences used for phylogenetic analyses.

Oct 15-23

Fall Break

Oct 25

Lecture (Collins, Christley, & McHenry)

  • Hidden Markov Model assignment
  • Project teams

Homework

Oct 27

Lecture (Madey)

  • History of Dynamic Programming
  • Overview of Dynamic Programming

FYI

Nov 1

Lecture (Collins/Madey)

Homework

Nov 3

Lecture (Lobo and Madey)

Homework

News

  • Recent Notre Dame CSE PhD graduate, Marc Ma, appointed  Director - Applied Bioinformatics Laboratory at NJIT (see the two courses he is teaching this term)

Nov 8

Guest Lecture

  • Professor Lawrence B. Holder, University of Texas Arlington will present on "Graph-based Data Mining in Biological Databases" (slides). The presentation will cover his work  in applying graph-based techniques to proteins and biological networks, other approaches (e.g., logic-based), and applications (e.g., mutagenicity)
    • Dr. Larry Holder is a professor in the Department of Computer Science and Engineering at the University of Texas at Arlington. He received his Ph.D. degree in Computer Science from the University of Illinois at Urbana-Champaign in 1991.  His work in graph-based relational learning has spanned over fifteen years and has resulted in numerous publications and funding from NASA, NSF, DHS and DARPA. Dr. Holder's main research interests include artificial intelligence, machine learning, data mining, and graph theory.
  • Professor Holder will also present a CSE Research Seminar at 3:30 pm, Debartolo 119 on "Graph-based Relational Learning"

Nov 10

Lecture (McHenry, Christley, & Thomas)

  • Project report on Hidden Markov Model project.

Homework

News: Seminar today

  • BioSimGrid: Towards a Worldwide Repository for Biomolecular Simulations

    Dr. Kaihsu Tai
    Laboratory of Molecular Biophysics
    University of Oxford

    208 DeBartolo Hall
    Thursday Nov. 10, 3:30 PM

    BioSimGrid is a database for biomolecular simulations, or a 'Protein  Data Bank extended in time' for molecular dynamics trajectories. We describe the implementation details: architecture, data schema, deposition, and  analysis modules. We encourage the simulation community to explore BioSimGrid  and worktowards a common trajectory exchange format.
    http://biosimgrid.org/

Nov 15

Lecture (Irene Kasumba, Faruck Morcos, and Jeffrey Spies)

Homework

Nov 17

Lecture (Collins)

  • Whole-Genome Shotgun Assembly

Homework

Nov 22

Lecture (Madey)

  • Algorithms for Whole-Genome Shotgun Assembly

Nov 24

No Class - Thanksgiving Break

Nov 29

Lecture (Madey)

Homework

Dec 2

Lecture (Madey)

  • Service oriented architecture for bioinformatics (Part 2)

Homework

Dec 6

Guest Lectures

  • Dongyoung Shin, Danielle Cisler and Sarah Frost
  • Jim Hogan, Ryan Kennedy and Trevor Cickovski
    • Analysis of P element Transposon Sequences in Aedes
      aegypti (paper) (slides)

Homework

Dec 8

Guest Lecture (Dr. Vicky Choi)

  • Dr. Choi, Department of Computer Science, Virginia Tech,  will give a guest lecture introducing Protein Small-molecule Docking and its Application to Drug Design:
  • Dr. Vicky Choi is currently an Assistant Professor at the Department of Computer Science, Virginia Tech. She received her PhD from the Department of Computer Science at Rutgers University in 2002. She was a Visiting Assistant Professor at the Department of Computer Science and Department of Biochemistry at Duke University from 2002 to 2004.
  • Dr. Choi will also present a CSE Research Seminar, Thursday, December 8, 2005, 3:30  p.m., 356 Fitzpatrick
    • "Efficient Point Pattern Matching and Applications to Bioinformatics"

      With the rapid increase in the number of known protein three-dimensional structures resulting from Structural Genomics Initiative, there is a need for more efficient algorithms for computational protein structural analysis, such as detection of common substructure in proteins, protein domain motions analysis and flexible protein structural alignment. In this talk, we introduce a new approximation algorithm, called T-hashing, for the largest common point set problem under noise. T-hashing is simple and faster than known approximation algorithms theoretically. It is also simpler and more efficient than the practical heuristics, such as generalized Hough transform (GHT) and geometric hashing. Current software, which uses either GHT or geometric hashing, can immediately benefit from this work. We will show some preliminary results of using T-hashing for the detection of common substructure in proteins, and protein domain motions analysis. This is a join work with Navin Goyal.
[Home] [Syllabus] [ClassNotes] [Articles] [Student Papers]