Elucidate multidimensionality of type 1 diabetes mellitus heterogeneity by multifaceted information.

Type 1 diabetes (T1D) is an autoimmune disease. Different factors, including genetics and viruses may contribute to T1D, but the causes of T1D are not fully known, and there is currently no cure. The advent of high-throughput technologies has revolutionized the field of medicine and biology, and analysis of multi-source data along with clinical information has brought a better understanding of the mechanisms behind disease pathogenesis.

Construction and Analysis of Protein-Protein Interaction Network of Heroin Use Disorder.

Heroin use disorder (HUD) is a complex disease resulting from interactions among genetic and other factors (e.g., environmental factors).

Association between depressive disorders and risk of breast cancer recurrence after curative surgery.

The aim of the study was to investigate the association between depressive disorders and risk of tumor recurrence in patients with breast cancer after curative surgery.A nationwide cohort study between January 2001 and December 2007 was conducted. Data were taken from the Taiwan National Health Insurance Research Database.

Genetic signatures of heroin addiction.

Heroin addiction is a complex psychiatric disorder with a chronic course and a high relapse rate, which results from the interaction between genetic and environmental factors. Heroin addiction has a substantial heritability in its etiology; hence, identification of individuals with a high genetic propensity to heroin addiction may help prevent the occurrence and relapse of heroin addiction and its complications. The study aimed to identify a small set of genetic signatures that may reliably predict the individuals with a high genetic propensity to heroin addiction.

Genotyping of human neutrophil antigens (HNA) from whole genome sequencing data.

Background: Neutrophil antigens are involved in a variety of clinical conditions including transfusion-related acute lung injury (TRALI) and other transfusion-related diseases. Recently, there are five characterized groups of human neutrophil antigen (HNA) systems, the HNA1 to 5. Characterization of all neutrophil antigens from whole genome sequencing (WGS) data may be accomplished for revealing complete genotyping formats of neutrophil antigens collectively at genome level with molecular variations which may respectively be revealed with available genotyping techniques for neutrophil antigens conventionally.

Associations between HIV and human pathways revealed by protein-protein interactions and correlated gene expression profiles.

Background: AIDS is one of the most devastating diseases in human history. Decades of studies have revealed host factors required for HIV infection, indicating that HIV exploits host processes for its own purposes. HIV infection leads to AIDS as well as various comorbidities.

Development of a questionnaire on everyday navigational ability to assess topographical disorientation in Alzheimer's disease.

We developed a Questionnaire on Everyday Navigational Ability (QuENA) to detect topographical disorientation (TD) in patients with Alzheimer's disease (PwAD). In the QuENA, 3 items were designed to assess landmark agnosia, 2 for egocentric disorientation, 3 for heading disorientation, and 2 for inattention. The PwAD and their caregivers rated QuENA according to which TD symptoms would occur.

A quantitative analysis of monochromaticity in genetic interaction networks.

Background: A genetic interaction refers to the deviation of phenotypes from the expected when perturbing two genes simultaneously. Studying genetic interactions help clarify relationships between genes, such as compensation and masking, and identify gene groups of functional modules. Recently, several genome-scale experiments for measuring quantitative (positive and negative) genetic interactions have been conducted.

Selection of DDX5 as a novel internal control for Q-RT-PCR from microarray data using a block bootstrap re-sampling scheme.

Background: The development of microarrays permits us to monitor transcriptomes on a genome-wide scale. To validate microarray measurements, quantitative-real time-reverse transcription PCR (Q-RT-PCR) is one of the most robust and commonly used approaches. The new challenge in gene quantification analysis is how to explicitly incorporate statistical estimation in such studies.

Effect of Epstein-Barr virus infection on global gene expression in nasopharyngeal carcinoma.

It was proposed that Epstein-Barr virus (EBV) is closely associated with nasopharyngeal carcinoma (NPC); however, the molecular mechanisms involved in the effect of EBV on NPC host genes have not yet been well defined. For this study, two sets of microarray experiments, NPC (EBV-free) vs normal epithelial cells and EBV(+) vs EBV(-) NPC arrays, were analyzed and the datasets were cross-compared to identify any correlation between gene clusters involved in EBV targeting and the NPC host gene expression profiles. Statistical analysis revealed that EBV seems to have a preference for targeting more genes from the differentially expressed group in NPC cells than those from the ubiquitously expressed group.

A stochastic differential equation model for quantifying transcriptional regulatory network in Saccharomyces cerevisiae.

Motivation: The explosion of microarray studies has promised to shed light on the temporal expression patterns of thousands of genes simultaneously. However, available methods are far from adequate in efficiently extracting useful information to aid in a greater understanding of transcriptional regulatory network. Biological systems have been modeled as dynamic systems for a long history, such as genetic networks and cell regulatory network.