Walter and Eliza Hall Institute of Medical Research

About: Walter and Eliza Hall Institute of Medical Research is a nonprofit organization based out in Melbourne, Victoria, Australia. It is known for research contribution in the topics: Antigen & Immune system. The organization has 5012 authors who have published 10620 publications receiving 873561 citations.

The role of BH3-only proteins in the immune system.

Abstract: Programmed cell death--also known as apoptosis--has a crucial role in the immune system of mammals and other animals. It removes useless cells and potentially dangerous cells, including lymphocytes, and is involved in killing pathogen-infected or damaged cells. Defects in this process have been found to cause or contribute to diseases of the immune system, including immunodeficiency, autoimmunity, lymphoma and leukaemia. This review describes BH3-only proteins, a pro-apoptotic subgroup of the BCL-2 family, and their role in the development and function of the immune system.

Immunological processes in malaria pathogenesis.

Abstract: Malaria is possibly the most serious infectious disease of humans, infecting 5-10% of the world's population, with 300-600 million clinical cases and more than 2 million deaths annually. Adaptive immune responses in the host limit the clinical impact of infection and provide partial, but incomplete, protection against pathogen replication; however, these complex immunological reactions can contribute to disease and fatalities. So, appropriate regulation of immune responses to malaria lies at the heart of the host-parasite balance and has consequences for global public health. This Review article addresses the innate and adaptive immune mechanisms elicited during malaria that either cause or prevent disease and fatalities, and it considers the implications for vaccine design.

Robust hyperparameter estimation protects against hypervariable genes and improves power to detect differential expression

Abstract: One of the most common analysis tasks in genomic research is to identify genes that are differentially expressed (DE) between experimental conditions. Empirical Bayes (EB) statistical tests using moderated genewise variances have been very effective for this purpose, especially when the number of biological replicate samples is small. The EB procedures can however be heavily influenced by a small number of genes with very large or very small variances. This article improves the differential expression tests by robustifying the hyperparameter estimation procedure. The robust procedure has the effect of decreasing the informativeness of the prior distribution for outlier genes while increasing its informativeness for other genes. This effect has the double benefit of reducing the chance that hypervariable genes will be spuriously identified as DE while increasing statistical power for the main body of genes. The robust EB algorithm is fast and numerically stable. The procedure allows exact small-sample null distributions for the test statistics and reduces exactly to the original EB procedure when no outlier genes are present. Simulations show that the robustified tests have similar performance to the original tests in the absence of outlier genes but have greater power and robustness when outliers are present. The article includes case studies for which the robust method correctly identifies and downweights genes associated with hidden covariates and detects more genes likely to be scientifically relevant to the experimental conditions. The new procedure is implemented in the limma software package freely available from the Bioconductor repository.