You may attend any number of classes in this series. Classes are free, but you must sign up.

This session will go over the basics of molecular visualization and provide an introduction to how to use UCSF Chimera to load, visualize, and manipulate protein structures. Topics include: installing Chimera; Chimera menus and commands; fetching protein structures from ModBase and PDB; selections and actions; depictions; key tools: Side View, Model Panel, and the Selection Panel; and saving your work: sessions and images.

Participants should have a basic understanding of protein structure. All participants will receive a CD with UCSF Chimera installers for Mac, PC, and Linux as well as example files and additional exercises.

This session will cover general structure visualization and analysis with Chimera. Topics include: identifying hydrogen bonds and contacts; measuring distances and angles, rotating bonds; viewing amino acid sidechain rotamers, "mutating" residues; displaying attributes such as B-factor and residue hydrophobicity; superimposing and comparing structures, morphing; viewing NMR ensembles and molecular dynamics trajectories.

Participants should have an acquaintance with molecular graphics and protein structure, although expertise with Chimera is not required. Participants are encouraged to bring structures of interest (or note their Protein Data Bank IDs for retrieval in the lab) as "real-life" examples to supplement the exercises that will be provided.

This session will cover working with protein sequence alignments together with 3D structures. Topics include: Web resources for protein family sequence alignments; sequence-structure association and crosstalk; calculating alignment conservation and displaying it on structures; using the alignment to match (superimpose) structures; matching structures without a pre-existing alignment; creating sequence alignments from multiple structure superpositions; customizing alignment appearance in Chimera; editing and saving.

Participants should have at least a little experience with Chimera and a basic understanding of protein structure and sequence alignments. Participants are encouraged to bring data on systems of interest (structure IDs, and if available, corresponding sequence alignments) as "real-life" examples to supplement the exercises that will be provided.

This session offers hands-on training for studying density maps, especially those from electron microscopy. You'll look at maps of phage K1E, a virus that infects E. coli, and learn to segment the protein coat from the packaged DNA genome, color to distinguish virus surface structures, morph to compare related viruses, and fit atomic models into the maps. The same techniques are applicable for crystallographic and tomographic density maps.

Participants should have familiarity with Chimera.

This session provides hands-on training for creating images and movies of molecular models and density maps for journal articles and presentations. You'll be introduced to the myriad of options to enhance your graphics: raytracing, depth cueing, supersampling, ribbon styles, silhouette edges, subdivision level, text labels, clipping and capping, transparent or colored backgrounds, fish eye views, presets, lighting, shininess, ambient occlusion, lenticular images, and movie transitions and encoding. You'll try these techniques on your own data (downloaded or brought on a flash drive or CD) or using example data we provide.

Participants should have familiarity with Chimera.

This session will cover methods for customizing Chimera for specific tasks and projects. Topics include: writing command and demonstration scripts; accessing Chimera data structures using Python; adding per-frame actions for analyzing molecular dynamics; adding user-defined headers to sequence alignment displays; adding your own user interface elements to Chimera.

Participants should have hands-on experience with Chimera. If there is a topic of particular interest, please mention it at the beginning of the session (or contact us beforehand) to ensure that we allot sufficient time to go into details.

This session will cover editing and curation of pathways at WikiPathways, with a focus on curation tools. Session topics include: viewing and downloading existing pathways; curation tools: pathway watch list, pathway revisions, discussion pages; community portals at WikiPathways.

Participants should have a basic knowledge of biological pathways. Prior experience with WikiPathways is not required.

This session will cover the basics of using Cytoscape for network visualization, including visualizing data on networks. It will also give an overview of plugins available for Cytoscape. Session topics include: installing Cytoscape; Cytoscape panels and menus; importing and manipulating data; visualizing data on networks; Cytoscape plugins.

Prior experience with Cytoscape is not required.

This session will cover the tools and methods that have been developed at UCSF to explore protein similarity networks. A protein similarity network is a network of nodes and edges where the nodes represent the protein and the edges represent some measure of the similarity between the proteins. These networks have been used to infer functional and evolutionary relationships between proteins and protein families. Session topics include: overview of protein similarity networks; using SFLDLoader to import protein similarity networks into Cytoscape; Cytoscape layouts suitable for protein similarity networks; exploring structural relationships with structureViz; creating your own protein similarity network; adding structural annotation to an existing protein similarity network.

Participants should be familiar with Cytoscape and have some experience with molecular structure visualization.

This session will focus on using Cytoscape for expression data, specifically visualizing expression data on biological networks and analyzing the data in terms of hierarchical clustering and GO over-representation analysis. Session topics include: importing expression data; visualizing it on networks; hierarchical clustering and visualization of expression data; GO overrepresentation analysis with BiNGO.

Participants should have experience with expression data and a basic understanding of cluster analysis and overrepresentation analysis. Prior experience with Cytoscape is not required. Participants can bring their own data, but example data will also be provided.