Special Topics in Computational Biology: Protein Structure Prediction 15-872(A)
Instructor
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Chris Langmead, WeH 4103, cjl at
cs.cmu.edu
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Description
We will read a series of papers on protein structure prediction. Topics such
as ab initio prediction,
comparative modeling, and threading will be covered, among others. Students
will be required to present papers, prepare short written summaries of each
paper they present, and complete a term-project.
The class Wiki will be the primary means of distributing
materials.
Prerequisites:
15-879 or permission of instructor
Course Information
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Classes: T, TH 7:00 - 8:20 PM ; WeH 5409
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Office Hours: by appointment
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Syllabus
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Date
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Speaker
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Reading
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Slides
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1/11
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Chris Langmead
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None; introduction to the course
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Class_1.ppt
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1/18
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Chris Langmead
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Paper 1: Protein Structure
Prediction and Structural Genomics, Baker and Sali; Paper 2: Have We seen all
structures corresponding to short protein fragmentsin
the PDB? An update, Du et al
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Jan182005.ppt
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1/25
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Peter Zullo
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“Mining
Protein Contact Maps” Hu et al
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2/1
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Swapnil Upganlawar
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A
surprising simplicity to protein folding
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2/3
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2/8
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Ka-Young An
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Protein
Backbone Angle Prediction with Machine Learning Approaches
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2/10
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Mohit Kumar
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Use
of Chemical Shifts in Macromolecular Structure Determination Wishart and Case
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2/15
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Ruben Valas
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Predicting
Disorder for N-, C- and Internal Regions
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2/17
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Narayanan R.
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Conserved
residue clustering and protein structure prediction Shueler-furman and Baker
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2/22
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NO CLASS
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2/24
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NO CLASS
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3/1
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K.Arun
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A multibody, whole-residue potential for protein
structures, with
testing by Monte Carlo simulated
annealing Mayewski
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3/3
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Peter Zullo
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A complete and effective move set for simplified protein
folding Lesh et al
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3/8
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NO CLASS; Spring Break
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3/10
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NO CLASS; Spring Break
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3/15
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K.Arun
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Assessment of progress over the CASP experiments.
Venclovas C, Zemla A, Fidelis K, Moult J.
Proteins. 2003;53 Suppl 6:585-95.
http://www3.interscience.wiley.com/cgi-bin/fulltext/106559026/PDFSTART
http://predictioncenter.llnl.gov/casp6/meeting/presentations/talks.html
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3/17
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No Class
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3/22
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Swapnil Upganlawar
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HMMSTR: a Hidden Markov Model for Local Sequence-Structure
Correlations in Proteins
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3/24
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Mohit Kumar
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Rapid
and accurate calculation of protein 1H, 13C, and 15N chemical shifts
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3/29
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Yan Liu
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Population
statistics of protein structures: lessons from structural classifications
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3/31
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Ka-Young An
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A
Machine Learning Strategy for Protein Analysis
‘Meta’Approaches to Protein Structure Prediction
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4/5
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No Class
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4/7
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No Class
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4/12
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Ruben Valas
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Factors Affecting the
Ability of Energy Functions to
Discriminate
Correct from Incorrect Folds
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4/14
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No Class, Carnival
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4/19
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Narayanan R.
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TRILOGY:
Discovery of sequence-structure patterns across diverse proteins
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4/21
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No Class
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4/26
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Project presentations
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4/28
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No Class
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