GediNET for discovering gene associations across diseases using knowledge based machine learning approach.

The most common approaches to discovering genes associated with specific diseases are based on machine learning and use a variety of feature selection techniques to identify significant genes that can serve as biomarkers for a given disease. More recently, the integration in this process of prior knowledge-based approaches has shown significant promise in the discovery of new biomarkers with potential translational applications. In this study, we developed a novel approach, GediNET, that integrates prior biological knowledge to gene Groups that are shown to be associated with a specific disease such as a cancer.

Telomere dysfunction implicates POT1 in patients with idiopathic pulmonary fibrosis.

Exonic sequencing identified a family with idiopathic pulmonary fibrosis (IPF) containing a previously unreported heterozygous mutation in POT1 p.(L259S). The family displays short telomeres and genetic anticipation.

Lack of Atorvastatin Effect on Monocyte Gene Expression and Inflammatory Markers in HIV-1-infected ART-suppressed Individuals at Risk of non-AIDS Comorbidities.

Background: Many people living with HIV have persistent monocyte activation despite viral suppression by antiretroviral therapy (ART), which contributes to non-AIDS complications including neurocognitive and other disorders. Statins have immunomodulatory properties that might be beneficial by reducing monocyte activation.

Methods: We previously characterized monocyte gene expression and inflammatory markers in 11 HIV-positive individuals on long-term ART (HIV/ART) at risk for non-AIDS complications because of low nadir CD4+ counts (median 129 cells/uL) and elevated hsCRP.

Functional Annotation of MicroRNAs Using Existing Resources.

MicroRNAs (miRNAs) are endogenous small noncoding RNAs that are involved in most biological signaling pathways, including the cell cycle, apoptosis, proliferation, immune response, metabolism as well as in biological processes including organ development and in human diseases like cancers. During the past two decades, high-throughput transcriptomic profiling using next generation sequencing and microarrays have been extensively utilized to identify differentially expressed miRNAs across different conditions and diseases. A natural extension of miRNA identification is to the process of functionally annotating known or predicted gene targets of those miRNAs and, by inference, revealing their potential influences on diverse biological pathways and functions.

Clinical presentation of COVID-19 - a model derived by a machine learning algorithm.

COVID-19 pandemic has flooded all triage stations, making it difficult to carefully select those most likely infected. Data on total patients tested, infected, and hospitalized is fragmentary making it difficult to easily select those most likely to be infected. The Israeli Ministry of Health made public its registry of immediate clinical data and the respective status of infected/not infected for all viral DNA tests performed up to Apr.