A5080577250- Tuberculosis Research and Epidemiology
- Mycobacterium research and diagnosis
- Genetic Associations and Epidemiology
- Smoking Behavior and Cessation
- Nutrition, Genetics, and Disease
- Health, Environment, Cognitive Aging
- Epigenetics and DNA Methylation
- Livestock and Poultry Management
- Genomics and Phylogenetic Studies
- vaccines and immunoinformatics approaches
- Statistical Methods and Inference
- Phytochemical Studies and Bioactivities
- Alcohol Consumption and Health Effects
- Asthma and respiratory diseases
- Substance Abuse Treatment and Outcomes
- Bioinformatics and Genomic Networks
- Radiomics and Machine Learning in Medical Imaging
- Health Systems, Economic Evaluations, Quality of Life
- Social and Educational Sciences
- Statistical Methods and Bayesian Inference
- Genetic Mapping and Diversity in Plants and Animals
- Machine Learning in Bioinformatics
- RNA and protein synthesis mechanisms
- Biochemical and Molecular Research
- Blood Pressure and Hypertension Studies
SomaLogic (United States)
2019-2023
University of Minnesota
2019-2021
Twin Cities Orthopedics
2019-2021
National Jewish Health
2014-2020
University of Colorado Denver
2014-2020
University of Colorado Boulder
2020
University of Colorado Anschutz Medical Campus
2015
ABSTRACT Blood transcriptional signatures are promising for tuberculosis (TB) diagnosis but have not been evaluated among U.S. patients. To be used clinically, classifiers need reproducible accuracy in diverse populations that vary genetic composition, disease spectrum and severity, comorbidities. In a prospective case-control study, we identified novel active TB patients systematically compared their to from published studies. samples HIV-uninfected adults with TB, pneumonia, or latent...
Abstract Genome-wide association meta-analysis (GWAMA) is an effective approach to enlarge sample sizes and empower the discovery of novel associations between genotype phenotype. Independent replication has been used as a gold-standard for validating genetic associations. However, current GWAMA often seeks aggregate all available datasets, it becomes impossible find large enough independent dataset replicate new discoveries. Here we introduce method, MAMBA (Meta-Analysis Model-based...
Tuberculosis (TB) is one of the leading causes death due to an infectious disease in world. Understanding mechanisms drug resistance has become pivotal detection and treatment newly emerging resistant TB cases. We have analyzed three pairs Mycobacterium tuberculosis strains pre- post-drug identify mutations involved progression drugs rifampicin isoniazid. In strain, we confirmed a mutation rpoB (S450L) that known confer rifampicin. discovered novel L101R katG gene isoniazid which may...
Central to most omic scale experiments is the interpretation and examination of resulting gene lists corresponding differentially expressed, regulated, or observed protein sets. Complicating a lack functional annotation assigned large percentage many microbial genomes. This particularly noticeable in mycobacterial genomes, which are significantly divergent from model species used for characterization, but extremely important clinically. Mycobacterial species, ranging M. tuberculosis...
Class imbalance can present a major issue in time-to-event analyses for instances where the number of individuals diagnosed with disease are far outnumbered by those who remain undiagnosed within specified time frame.An example this is incidence rate myocardial infarction (MI) among patients stable coronary heart disease, MI events typically sparse over course study.This may result inaccurate risk predictions more likely to be having an event.In study, we combine sampling Cox proportional...
Although respiratory diseases exhibit in a wide array of clinical manifestations, certain may share related genetic mechanisms or be influenced by similar chemical stimuli. Here we explore and infer relationships among genes, diseases, chemicals using network matrix based clustering methods. In order to better understand elucidate these shared analyzed comprehensive collection gene, disease, pertinent analysis approaches. Our methods enabled us analyze make biological inferences over 200...
Abstract Background: Prognostic models for assessing future health outcomes can be developed using time-to-event (also known as “survival”) data. This methodology is ubiquitous in statistical literature and the analysis of cancer outcomes, but its use high-dimensional analyses tends to limited methods are difficult implement a machine learning environment. Additionally, development certified prognostic clinical tests proteomic biomarkers detecting risk time-consuming, prone overfitting...
Abstract Background The increasing incidence of drug resistance in tuberculosis and other infectious diseases poses an escalating cause for concern, emphasizing the urgent need to devise robust computational molecular methods identify resistant strains. Although machine learning-based approaches using whole-genome sequence data can facilitate inference resistance, current implementations do not optimally take advantage information public databases are small sample sizes mixed attribute...