Footprints: A Visual Search Tool that Supports Discovery and Coverage Tracking.

Searching a large document collection to learn about a broad subject involves the iterative process of figuring out what to ask, filtering the results, identifying useful documents, and deciding when one has covered enough material to stop searching. We are calling this activity "discoverage," discovery of relevant material and tracking coverage of that material. We built a visual analytic tool called Footprints that uses multiple coordinated visualizations to help users navigate through the discoverage process.

An interactive web application for the dissemination of human systems immunology data.

Background: Systems immunology approaches have proven invaluable in translational research settings. The current rate at which large-scale datasets are generated presents unique challenges and opportunities. Mining aggregates of these datasets could accelerate the pace of discovery, but new solutions are needed to integrate the heterogeneous data types with the contextual information that is necessary for interpretation.

Systems scale interactive exploration reveals quantitative and qualitative differences in response to influenza and pneumococcal vaccines.

Systems immunology approaches were employed to investigate innate and adaptive immune responses to influenza and pneumococcal vaccines. These two non-live vaccines show different magnitudes of transcriptional responses at different time points after vaccination. Software solutions were developed to explore correlates of vaccine efficacy measured as antibody titers at day 28.

An analysis pipeline for the inference of protein-protein interaction networks.

We present a platform for the reconstruction of protein-protein interaction networks inferred from Mass Spectrometry (MS) bait-prey data. The Software Environment for Biological Network Inference (SEBINI), an environment for the deployment of network inference algorithms that use high-throughput data, forms the platform core. Among the many algorithms available in SEBINI is the Bayesian Estimator of Probabilities of Protein-Protein Associations (BEPro3) algorithm, which is used to infer interaction networks from such MS affinity isolation data.

CABIN: collective analysis of biological interaction networks.

The importance of understanding biological interaction networks has fueled the development of numerous interaction data generation techniques, databases and prediction tools. However, not all prediction tools and databases predict interactions with one hundred percent accuracy. Generation of high-confidence interaction networks formulates the first step towards deciphering unknown protein functions, determining protein complexes and inventing drugs.