Core liver homeostatic co-expression networks are preserved but respond to perturbations in an organism- and disease-specific manner.

Findings about chronic complex diseases are difficult to extrapolate from animal models to humans. We reason that organs may have core network modules that are preserved between species and are predictably altered when homeostasis is disrupted. To test this idea, we perturbed hepatic homeostasis in mice by dietary challenge and compared the liver transcriptome with that in human fatty liver disease and liver cancer.

Abnormalities of Aspiration and Swallowing Function in Survivors of Acute Respiratory Failure.

The mechanisms responsible for aspiration are relatively unknown in patients recovering from acute respiratory failure (ARF) who required mechanical ventilation. Though many conditions may contribute to swallowing dysfunction, alterations in laryngeal structure and swallowing function likely play a role in the development of aspiration. At four university-based tertiary medical centers, we conducted a prospective cohort study of ARF patients who required intensive care and mechanical ventilation for at least 48 h.

Development of an Accurate Bedside Swallowing Evaluation Decision Tree Algorithm for Detecting Aspiration in Acute Respiratory Failure Survivors.

Background: The bedside swallowing evaluation (BSE) is an assessment of swallowing function and airway safety during swallowing. After extubation, the BSE often is used to identify the risk of aspiration in acute respiratory failure (ARF) survivors.

Research Question: We conducted a multicenter prospective study of ARF survivors to determine the accuracy of the BSE and to develop a decision tree algorithm to identify aspiration risk.

AltitudeOmics: Red Blood Cell Metabolic Adaptation to High Altitude Hypoxia.

Red blood cells (RBCs) are key players in systemic oxygen transport. RBCs respond to in vitro hypoxia through the so-called oxygen-dependent metabolic regulation, which involves the competitive binding of deoxyhemoglobin and glycolytic enzymes to the N-terminal cytosolic domain of band 3. This mechanism promotes the accumulation of 2,3-DPG, stabilizing the deoxygenated state of hemoglobin, and cytosol acidification, triggering oxygen off-loading through the Bohr effect.

A graphical model method for integrating multiple sources of genome-scale data.

Making effective use of multiple data sources is a major challenge in modern bioinformatics. Genome-wide data such as measures of transcription factor binding, gene expression, and sequence conservation, which are used to identify binding regions and genes that are important to major biological processes such as development and disease, can be difficult to use together due to the different biological meanings and statistical distributions of the heterogeneous data types, but each can provide valuable information for understanding the processes under study. Here we present methods for integrating multiple data sources to gain a more complete picture of gene regulation and expression.

SNPEVG: a graphical tool for GWAS graphing with mouse clicks.

Background: Genome-wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers generate large quantities of tests results. Global and local graphical viewing of the test results is an effective approach to digest and interpret GWAS results.

Results: SNPEVG is a set of graphical tools for instant global and local viewing and graphing of GWAS results for all chromosomes and for each trait.

Ontology quality assurance through analysis of term transformations.

Motivation: It is important for the quality of biological ontologies that similar concepts be expressed consistently, or univocally. Univocality is relevant for the usability of the ontology for humans, as well as for computational tools that rely on regularity in the structure of terms. However, in practice terms are not always expressed consistently, and we must develop methods for identifying terms that are not univocal so that they can be corrected.

Parallel and serial computing tools for testing single-locus and epistatic SNP effects of quantitative traits in genome-wide association studies.

Background: Genome-wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers provide opportunities to detect epistatic SNPs associated with quantitative traits and to detect the exact mode of an epistasis effect. Computational difficulty is the main bottleneck for epistasis testing in large scale GWAS.

Results: The EPISNPmpi and EPISNP computer programs were developed for testing single-locus and epistatic SNP effects on quantitative traits in GWAS, including tests of three single-locus effects for each SNP (SNP genotypic effect, additive and dominance effects) and five epistasis effects for each pair of SNPs (two-locus interaction, additive x additive, additive x dominance, dominance x additive, and dominance x dominance) based on the extended Kempthorne model.

Genome-wide analysis of single-locus and epistasis single-nucleotide polymorphism effects on anti-cyclic citrullinated peptide as a measure of rheumatoid arthritis.

The goal of this study was to identify single-locus and epistasis effects of SNP markers on anti-cyclic citrullinated peptide (anti-CCP) that is associated with rheumatoid arthritis, using the North American Rheumatoid Arthritis Consortium data. A square root transformation of the phenotypic values of anti-CCP with sex, smoking status, and a selected subset of 20 single-nucleotide polymorphism (SNP) markers in the model achieved residual normality (p > 0.05).

Detection of SNP epistasis effects of quantitative traits using an extended Kempthorne model.

Epistasis effects (gene interactions) have been increasingly recognized as important genetic factors underlying complex traits. The existence of a large number of single nucleotide polymorphisms (SNPs) provides opportunities and challenges to screen DNA variations affecting complex traits using a candidate gene analysis. In this article, four types of epistasis effects of two candidate gene SNPs with Hardy-Weinberg disequilibrium (HWD) and linkage disequilibrium (LD) are considered: additive x additive, additive x dominance, dominance x additive, and dominance x dominance.

SiMCAL 1 algorithm for analysis of gene expression data related to the phosphatidylserine receptor.

Objective: SiMCAL 1 (simple multilevel clustering and linking, version 1) is a novel clustering algorithm for time-series microarray data, presented here with an application to a specific data set. The purpose of the algorithm is to present a complete feature set not found in either Jarvis-Patrick clustering, from which it is derived, or in other popular clustering methods such as hierarchical and k-means. The data concern the activity of the phosphatidylserine receptor (PSR) which is believed to be a crucial molecular switch in the mediation of inflammatory response in apoptosis and lysis.