PMart Web Application: Marketplace for Interactive Analysis of Panomics Data.

PMart is a web-based tool for reproducible quality control, exploratory data analysis, statistical analysis, and interactive visualization of 'omics data, based on the functionality of the R package. The newly improved user interface supports more 'omics data types, additional statistical capabilities, and enhanced options for creating downloadable graphics. PMart supports the analysis of label-free and isobaric-labeled (e.

The conserved endocannabinoid anandamide modulates olfactory sensitivity to induce hedonic feeding in C. elegans.

The ability of cannabis to increase food consumption has been known for centuries. In addition to producing hyperphagia, cannabinoids can amplify existing preferences for calorically dense, palatable food sources, a phenomenon called hedonic amplification of feeding. These effects result from the action of plant-derived cannabinoids that mimic endogenous ligands called endocannabinoids.

Theory and practice of using cell strainers to sort Caenorhabditis elegans by size.

The nematode Caenorhabditis elegans is a model organism widely used in basic, translational, and industrial research. C. elegans development is characterized by five morphologically distinct stages, including four larval stages and the adult stage.

Intact maternal buffering of stress response in infant rats despite altered responsivity towards maternal olfactory cues in the valproic acid model of autism-like behavior.

Disrupted processing of social cues and altered social behaviors are among the core symptoms of autism spectrum disorders (ASDs), and they emerge as early as the first year of life. These differences in sensory abilities may affect the ability of children with ASDs to securely attach to a caregiver and experience caregiver buffering of stress. Prenatal exposure to valproic acid (VPA) has been used to model some aspects of ASDs in rodents.

PSpecteR: A User-Friendly and Interactive Application for Visualizing Top-Down and Bottom-Up Proteomics Data in R.

Visual examination of mass spectrometry data is necessary to assess data quality and to facilitate data exploration. Graphics provide the means to evaluate spectral properties, test alternative peptide/protein sequence matches, prepare annotated spectra for publication, and fine-tune parameters during wet lab procedures. Visual inspection of LC-MS data is constrained by proteomics visualization software designed for particular workflows or vendor-specific tools without open-source code.

P-Mart: Interactive Analysis of Ion Abundance Global Proteomics Data.

The use of mass-spectrometry-based techniques for global protein profiling of biomedical or environmental experiments has become a major focus in research centered on biomarker discovery; however, one of the most important issues recently highlighted in the new era of omics data generation is the ability to perform analyses in a robust and reproducible manner. This has been hypothesized to be one of the issues hindering the ability of clinical proteomics to successfully identify clinical diagnostic and prognostic biomarkers of disease. P-Mart ( https://pmart.

P-MartCancer-Interactive Online Software to Enable Analysis of Shotgun Cancer Proteomic Datasets.

P-MartCancer is an interactive web-based software environment that enables statistical analyses of peptide or protein data, quantitated from mass spectrometry-based global proteomics experiments, without requiring in-depth knowledge of statistical programming. P-MartCancer offers a series of statistical modules associated with quality assessment, peptide and protein statistics, protein quantification, and exploratory data analyses driven by the user via customized workflows and interactive visualization. Currently, P-MartCancer offers access and the capability to analyze multiple cancer proteomic datasets generated through the Clinical Proteomics Tumor Analysis Consortium at the peptide, gene, and protein levels.

Degree of anxiety in food allergic children in a tertiary care center.

Background: The link between internalizing psychiatric disorders, such as anxiety and depression, and allergic diseases has attracted a high level of interest from psychiatrists and immunologists. Recent studies have found increased anxiety in children with asthma, but findings in children with food allergy (FA) have been inconsistent.

Objective: It was hypothesized that children with FA would score significantly higher on a standardized anxiety screen than general pediatric (GP) patients but not as high as patients with diagnosed anxiety disorders.

Analysis of high-throughput ELISA microarray data.

Our research group develops analytical methods and software for the high-throughput analysis of quantitative enzyme-linked immunosorbent assay (ELISA) microarrays. ELISA microarrays differ from DNA microarrays in several fundamental aspects and most algorithms for analysis of DNA microarray data are not applicable to ELISA microarrays. In this review, we provide an overview of the steps involved in ELISA microarray data analysis and how the statistically sound algorithms we have developed provide an integrated software suite to address the needs of each data-processing step.

An internal calibration method for protein-array studies.

Nuisance factors in a protein-array study add obfuscating variation to spot intensity measurements, diminishing the accuracy and precision of protein concentration predictions. The effects of nuisance factors may be reduced by design of experiments, and by estimating and then subtracting nuisance effects. Estimated nuisance effects also inform about the quality of the study and suggest refinements for future studies.

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.

ELISA-BASE: an integrated bioinformatics tool for analyzing and tracking ELISA microarray data.

Summary: ELISA-BASE is an open source database for capturing, organizing and analyzing enzyme-linked immunosorbent assay (ELISA) microarray data. ELISA-BASE is an extension of the BioArray Software Environment (BASE) database system.

Availability: http://www.

Predicting protein concentrations with ELISA microarray assays, monotonic splines and Monte Carlo simulation.

Making sound proteomic inferences using ELISA microarray assay requires both an accurate prediction of protein concentration and a credible estimate of its error. We present a method using monotonic spline statistical models (MS), penalized constrained least squares fitting (PCLS) and Monte Carlo simulation (MC) to predict ELISA microarray protein concentrations and estimate their prediction errors. We contrast the MSMC (monotone spline Monte Carlo) method with a LNLS (logistic nonlinear least squares) method using simulated and real ELISA microarray data sets.

A Bayesian estimator of protein-protein association probabilities.

Unlabelled: The Bayesian Estimator of Protein-Protein Association Probabilities (BEPro aff3) is a software tool for estimating probabilities of protein-protein association between bait and prey protein pairs using data from multiple-bait, multiple-replicate, protein liquid chromatography tandem mass spectrometry LC-MS/MS affinity isolation experiments.

Availability: BEPro (3) is public domain software, has been tested on WIndows XP, Linux and Mac OS, and is freely available from http://www.pnl.

Evaluation of surface chemistries for antibody microarrays.

Antibody microarrays are an emerging technology that promises to be a powerful tool for the detection of disease biomarkers. The current technology for protein microarrays has been derived primarily from DNA microarrays and is not fully characterized for use with proteins. For example, there are a myriad of surface chemistries that are commercially available for antibody microarrays, but there are no rigorous studies that compare these different surfaces.

Statistically inferring protein-protein associations with affinity isolation LC-MS/MS assays.

Affinity isolation of protein complexes followed by protein identification by LC-MS/MS is an increasingly popular approach for mapping protein interactions. However, systematic and random assay errors from multiple sources must be considered to confidently infer authentic protein-protein interactions. To address this issue, we developed a general, robust statistical method for inferring authentic interactions from protein prey-by-bait frequency tables using a binomial-based likelihood ratio test (LRT) coupled with Bayes' Odds estimation.

ProMAT: protein microarray analysis tool.

Summary: ProMAT is a software tool for statistically analyzing data from enzyme-linked immunosorbent assay microarray experiments. The software estimates standard curves, sample protein concentrations and their uncertainties for multiple assays. ProMAT generates a set of comprehensive figures for assessing results and diagnosing process quality.

ELISA microarray technology as a high-throughput system for cancer biomarker validation.

A large gap currently exists between the ability to discover potential biomarkers and the ability to assess the real value of these proteins for cancer screening. One major challenge in biomarker validation is the inherent variability in biomarker levels. This variability stems from the diversity across the human population and the considerable molecular heterogeneity between individual tumors, even those that originate from a single tissue.

Automated Microarray Image Analysis Toolbox for MATLAB.

Unlabelled: The Automated Microarray Image Analysis (AMIA) Toolbox for MATLAB is a flexible, open-source, microarray image analysis tool that allows the user to customize analyses of microarray image sets. This tool provides several methods to identify and quantify spot statistics, as well as extensive diagnostic statistics and images to evaluate data quality and array processing. The open, modular nature of AMIA provides access to implementation details and encourages modification and extension of AMIA's capabilities.

Evaluating concentration estimation errors in ELISA microarray experiments.

Background: Enzyme-linked immunosorbent assay (ELISA) is a standard immunoassay to estimate a protein's concentration in a sample. Deploying ELISA in a microarray format permits simultaneous estimation of the concentrations of numerous proteins in a small sample. These estimates, however, are uncertain due to processing error and biological variability.

Is there an auditory-visual flash-lag effect?

A flash adjacent to the path of a moving object appears behind the moving object: the 'flash-lag effect'. We sought to test the flash-lag effect with a 'click' instead of a flash: a white triangle horizontally traversed the screen at a constant 12 degrees /s passing through a fixation cross in the presence of a quiet click. The subject judged whether the click occurred before or after the triangle passed through the cross.