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.

Benchmark study of automatic annotation of MALDI-TOF N-glycan profiles.

Human experts can annotate peaks in MALDI-TOF profiles of detached N-glycans with some degree of accuracy. Even though MALDI-TOF profiles give only intact masses without any fragmentation information, expert knowledge of the most common glycans and biosynthetic pathways in the biological system can point to a small set of most likely glycan structures at the "cartoon" level of detail. Cartoonist is a recently developed, fully automatic annotation tool for MALDI-TOF glycan profiles.

Separating the drivers from the driven: Integrative network and pathway approaches aid identification of disease biomarkers from high-throughput data.

The recent advances in high-throughput data acquisition have driven a revolution in the study of human disease and determination of molecular biomarkers of disease states. It has become increasingly clear that many of the most important human diseases arise as the result of a complex interplay between several factors including environmental factors, such as exposure to toxins or pathogens, diet, lifestyle, and the genetics of the individual patient. Recent research has begun to describe these factors in the context of networks which describe relationships between biological components, such as genes, proteins and metabolites, and have made progress towards the understanding of disease as a dysfunction of the entire system, rather than, for example, mutations in single genes.

Machine learning based prediction for peptide drift times in ion mobility spectrometry.

Motivation: Ion mobility spectrometry (IMS) has gained significant traction over the past few years for rapid, high-resolution separations of analytes based upon gas-phase ion structure, with significant potential impacts in the field of proteomic analysis. IMS coupled with mass spectrometry (MS) affords multiple improvements over traditional proteomics techniques, such as in the elucidation of secondary structure information, identification of post-translational modifications, as well as higher identification rates with reduced experiment times. The high throughput nature of this technique benefits from accurate calculation of cross sections, mobilities and associated drift times of peptides, thereby enhancing downstream data analysis.

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.

Site-specific protein adducts of 4-hydroxy-2(E)-nonenal in human THP-1 monocytic cells: protein carbonylation is diminished by ascorbic acid.

The protein targets and sites of modification by 4-hydroxy-2(E)-nonenal (HNE) in human monocytic THP-1 cells after exogenous exposure to HNE were examined using a multipronged proteomic approach involving electrophoretic, immunoblotting, and mass spectrometric methods. Immunoblot analysis using monoclonal anti-HNE antibodies showed several proteins as targets of HNE adduction. Pretreatment of THP-1 cells with ascorbic acid resulted in reduced levels of HNE-protein adducts.

Proteomic and phospho-proteomic profile of human platelets in basal, resting state: insights into integrin signaling.

During atherogenesis and vascular inflammation quiescent platelets are activated to increase the surface expression and ligand affinity of the integrin alphaIIbbeta3 via inside-out signaling. Diverse signals such as thrombin, ADP and epinephrine transduce signals through their respective GPCRs to activate protein kinases that ultimately lead to the phosphorylation of the cytoplasmic tail of the integrin alphaIIbbeta3 and augment its function. The signaling pathways that transmit signals from the GPCR to the cytosolic domain of the integrin are not well defined.

Biological Network Inference and analysis using SEBINI and CABIN.

Unlabelled: Attaining a detailed understanding of the various biological networks in an organism lies at the core of the emerging discipline of systems biology. A precise description of the relationships formed between genes, mRNA molecules, and proteins is a necessary step toward a complete description of the dynamic behavior of an organism at the cellular level, and toward intelligent, efficient, and directed modification of an organism. The importance of understanding such regulatory, signaling, and interaction networks has fueled the development of numerous in silico inference algorithms, as well as new experimental techniques and a growing collection of public databases.

A network inference workflow applied to virulence-related processes in Salmonella typhimurium.

Inference of the structure of mRNA transcriptional regulatory networks, protein regulatory or interaction networks, and protein activation/inactivation-based signal transduction networks are critical tasks in systems biology. In this article we discuss a workflow for the reconstruction of parts of the transcriptional regulatory network of the pathogenic bacterium Salmonella typhimurium based on the information contained in sets of microarray gene-expression data now available for that organism and describe our results obtained by following this workflow. The primary tool is one of the network-inference algorithms deployed in the Software Environment for Biological Network Inference (SEBINI).

Network inference algorithms elucidate Nrf2 regulation of mouse lung oxidative stress.

A variety of cardiovascular, neurological, and neoplastic conditions have been associated with oxidative stress, i.e., conditions under which levels of reactive oxygen species (ROS) are elevated over significant periods.

Characterization of the mouse pancreatic islet proteome and comparative analysis with other mouse tissues.

The pancreatic islets of Langerhans, and especially the insulin-producing beta cells, play a central role in the maintenance of glucose homeostasis. Alterations in the expression of multiple proteins in the islets that contribute to the maintenance of islet function are likely to underlie the pathogenesis of types 1 and 2 diabetes. To identify proteins that constitute the islet proteome, we provide the first comprehensive proteomic characterization of pancreatic islets for mouse, the most commonly used animal model in diabetes research.

A domain-based approach to predict protein-protein interactions.

Background: Knowing which proteins exist in a certain organism or cell type and how these proteins interact with each other are necessary for the understanding of biological processes at the whole cell level. The determination of the protein-protein interaction (PPI) networks has been the subject of extensive research. Despite the development of reasonably successful methods, serious technical difficulties still exist.

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.

PQuad--a visual analysis platform for proteomic data exploration of microbial organisms.

Unlabelled: The visual Platform for Proteomics Peptide and Protein data exploration (PQuad) is a multi-resolution environment that visually integrates genomic and proteomic data for prokaryotic systems, overlays categorical annotation and compares differential expression experiments. PQuad requires Java 1.5 and has been tested to run across different operating systems.

Enabling high-throughput data management for systems biology: the Bioinformatics Resource Manager.

Unlabelled: The Bioinformatics Resource Manager (BRM) is a software environment that provides the user with data management, retrieval and integration capabilities. Designed in collaboration with biologists, BRM simplifies mundane analysis tasks of merging microarray and proteomic data across platforms, facilitates integration of users' data with functional annotation and interaction data from public sources and provides connectivity to visual analytic tools through reformatting of the data for easy import or dynamic launching capability. BRM is developed using Java and other open-source technologies for free distribution.

COPASI--a COmplex PAthway SImulator.

Motivation: Simulation and modeling is becoming a standard approach to understand complex biochemical processes. Therefore, there is a big need for software tools that allow access to diverse simulation and modeling methods as well as support for the usage of these methods.

Results: Here, we present COPASI, a platform-independent and user-friendly biochemical simulator that offers several unique features.

Enabling proteomics discovery through visual analysis. The peptide permutation and protein prediction tool.

Proteins play a key role in cellular processes, making proteomics central to understanding systems biology. MS techniques provide a means to observe entire proteomes at a global level. Yet, high-throughput MS proteomics techniques generate data faster than it can currently be analyzed.