A state of the art structure prediction and way more (licenced via University of Washington).
Download the noncanonical amino acid (NCAA) rotamer libraries for Rosetta
Download the peptoid rotamer libraries for Rosetta
Microbiome Data Analysis
Resources for microbial ecology, particularly for population relative abundances generated from 16S amplicon sequencing.
Learn a network using Sparse InversE Covariance estimation for Ecological Association Inference. Provides a pipeline for estimating conditional independence between components of cross-sectional, high-dimensional compositions and model selection. The package also includes a scalable framework for simulating realistic data under various random network models. Kurtz et al. (2015)
Compositionally-robust methods for Partial Least Squares discriminant analysis and regression, which models linear relationships between features of log-ratio transformed compositions and sample classes or environmental/host factors. Lee et al. (2014)
NoGO is a resource for obtaining negative examples of gene function across many common organisms, comparing three state-of-the-art prediction algorithms employing different schemes for defining negative examples (genese that are predicted to NOT have a particular Gene Ontology annotation).
The FunCProp (Function Computational Propagation) project applies novel label propagation techniques to many different types of gene and protein data in order to predict protein function via Gene Ontology annotations.
BioNetBuilder is a Cytoscape plugIn that offers a user friendly interface to create biological networks integrated from several databases.
Learns parsimonious regulatory networks from systems biology datasets. Companion to cMonkey. Written in R, free after publication.
A web server for rosetta structure prediction and Ginzu protein-domain parsing (submit a few of your favorite unknown proteins here).
A systems biology data-integration and viz platform. Initially developed to map expression data onto biological networks.
Data-integration platform (developed by Paul Shannon). A way to manage many different data-types and views as a mutli-threaded gaggle controlled by the gaggle-boss.
Learns significant clusters, control elements and subnetworks from diverse systems-biology data. Written in R, free after publication.