| 1/5/16 |
Introduction |
slides |
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Ron Dror |
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| 1/7/16 |
Simulation of drug targets and simulation analysis |
slides |
1. Structural basis for modulation of a G-protein-coupled receptor by allosteric drugs
2. Identifying localized changes in large systems: Change-point detection for biomolecular simulations
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Ron Dror |
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| 1/12/16 |
No Class |
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| 1/14/16 |
Using multiplayer online video games for structure prediction and design |
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1. Predicting protein structures with a multiplayer online game
2. RNA design rules from a massive open laboratory
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a. Scientific rigor through videogames
b. Crystal structure of a monomeric retroviral protease solved by protein folding game players
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Rhiju Das |
2. Anthony Ma |
| 1/19/16 |
Machine learning on molecular structures |
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1. High Precision Prediction of Functional Sites in Protein Structures
2. AtomNet: A Deep Convolutional Neural Network for Bioactivity Prediction in Structure-based Drug Discovery
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a. Improving Structure-Based Function Prediction Using Molecular Dynamics
b. Convolutional Networks on Graphs for Learning Molecular Fingerprints
c. Large-scale prediction and testing of drug activity on side-effect targets
d. The SeqFEATURE library of 3D functional site models: comparison to existing methods and applications to protein function annotation
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Ray Zhuang |
1. Connor Brinton
2. Raphael Townshend |
| 1/21/16 |
Alchemical methods for computing binding affinities of drug candidates |
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1. Alchemical Free Energy Calculations: Ready for Prime Time?
2. Accurate and Reliable Prediction of Relative Ligand Binding Potency in Prospective Drug Discovery by Way of a Modern Free-Energy Calculation Protocol and Force Field
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Alchemical free energy methods for drug discovery: progress and challenges
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John Cherian |
1. Cayla Miller
2. Yoon Kim |
| 1/26/16 |
Modern protein design |
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1. De novo design of a transmembrane Zn2+-transporting four-helix bundle
2. Computational design of ligand-binding proteins with high affinity and selectivity
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a. AbDesign: An algorithm for combinatorial backbone design guided by natural conformations and sequences
b. Principles for designing ideal
protein structures
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Rishi Bedi
Kira Watkins |
1. Stevan Jeknic
1. Tim Abbott
2. Kalli Kappel
2. Brian Do |
| 1/28/16 |
Coevolution methods for predicting structure from large numbers of genetic sequences |
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1. Large scale determination of previously unsolved protein structures using evolutionary information
2. Improved Contact Predictions Using the Recognition of Protein Like Contact Patterns
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a. Three-Dimensional Structures of Membrane Proteins from Genomic Sequencing
b. From residue coevolution to protein conformational ensembles and functional dynamics
c. Protein structure prediction from sequence variation
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Cayla Miller
Yuan Xue |
1. Rishi Bedi
1. Maheetha Bharadwaj
2. Yingzhou Li
2. Tim Abbott |
| 2/2/16 |
New methods for solving tough crystal structures |
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1. Super-resolution biomolecular crystallography with low-resolution data
2. Enabling X-ray free electron laser crystallography for challenging biological systems from a limited number of crystals
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a. Improving the Accuracy of Macromolecular Structure Refinement at 7Å Resolution
b. Structural biology: ‘seeing’ crystals the XFEL way
c. A grid-enabled web service for low-resolution crystal structure refinement
d. Deformable elastic network refinement for low-resolution macromolecular crystallography
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Yoon Kim
Arjun Aditham |
1. Kevin Larsen
1. Kira Watkins
2. Rishi Bedi
2. Yuan Xue |
| 2/4/16 |
Markov state models for molecular dynamics simulations |
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1. Everything you wanted to know about Markov State Models but were afraid to ask
2. Markov state models of biomolecular conformational dynamics
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Improvements in Markov State Model Construction Reveal Many Non-Native Interactions in the Folding of NTL9
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Kolade Adebowale
Anthony Ma |
1. Shirin Sadri
2. Connor Brinton
2. Anjan Dwaraknath |
| 2/9/16 |
RNA Secondary Structure Prediction & Design of Protein/Nucleic Acid Complexes |
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1. Computational design of co-assembling protein–DNA nanowires
2. Accurate SHAPE-directed RNA secondary structure modeling, including pseudoknots
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High-throughput mutate-map-rescue evaluates SHAPE- directed RNA structure and uncovers excited states |
Kalli Kappel
Kevin Larsen |
1. Ray Zhuang
1. Kolade Adebowale
2. Anthony Ma |
| 2/11/16 |
Computational methods for single-particle electron microscopy |
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1. A Bayesian View on Cryo-EM Structure Determination
2. Advances in Single-Particle Electron Cryomicroscopy Structure Determination applied to Sub-tomogram Averaging
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a. A Primer to Single-Particle Cryo-Electron Microscopy
b. Dynamics in cryo EM reconstructions visualized with maximum-likelihood derived variance maps
c. Prevention of overfitting in cryo-EM structure determination
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Yingzhou Li
Rolando Perez |
1. Kevin Larsen
1. Richard Tang
2. Long-huei Chen
2. Kalli Kappel |
| 2/16/16 |
Protein-protein interactions |
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1. Structure-based prediction of protein–protein interactions on a genome-wide scale
2. Interactome3d: adding structural details to protein networks
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Networks of bZIP Protein-Protein Interactions Diversified Over a Billion Years of Evolution
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Connor Brinton
Raphael Townshend |
1. Yingzhou Li
1. Rolando Perez
2. Brian Do
2. Yoon Kim |
| 2/18/16 |
Three-dimensional genome architecture |
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1. Three-dimensional genome architecture: players and mechanisms
2. Genome architectures revealed by tethered chromosome conformation capture and population-based modeling
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Comprehensive Mapping of Long-Range Interactions Reveals Folding Principles of the Human Genome
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Tim Abbott
Brian Do |
1. Arjun Aditham
2. Kira Watkins
2. Kolade Adebowale |
| 2/23/16 |
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Michael Levitt |
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| 2/25/16 |
Three-dimensional genome architecture |
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1. A 3D Map of the Human Genome at Kilobase Resolution Reveals Principles of Chromatin Looping
2. Chromatin extrusion explains key features of loop and domain formation in wild-type and engineered genomes
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Adrian Sanborn |
1. Maheetha Bharadwaj
2. Stevan Jeknic
2. Long-huei Chen |
| 3/1/16 |
Compressed sensing for fluorescence microscopy |
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1. Faster STORM using compressed sensing
2. Compressive fluorescence microscopy for biological and hyperspectral imaging
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Fast compressed sensing analysis for super- resolution imaging using L1-homotopy
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Anjan Dwaraknath
Richard Tang |
1. Yuan Xue
1. Raphael Townshend
2. Arjun Aditham |
| 3/3/16 |
Machine learning on microscopy images |
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1. Automated Learning of Subcellular Variation among Punctate Protein Patterns and a Generative Model of Their Relation to Microtubules
2. Scoring diverse cellular morphologies in image-based screens with iterative feedback and machine learning
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Maheetha Bharadwaj
Shirin Sadri |
1. John Cherian
1. Richard Tang
2. Anjan Dwaraknath |
| 3/8/16 |
Cellular-level simulation |
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1. ReaDDy - A Software for Particle-Based Reaction- Diffusion Dynamics in Crowded Cellular Environments
2. Computational modeling of cellular signaling processes embedded into dynamic spatial contexts
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a. Fast monte carlo simulation methods for biological reaction-diffusion systems in solution and on
surfaces
b. ReaDDyMM: Fast Interacting Particle Reaction-Diffusion Simulations Using Graphical Processing Units
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Stevan Jeknic
Long-huei Chen |
1. Shirin Sadri
1. Cayla Miller
2. Rolando Perez |
| 3/10/16 |
No Class |
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