Using Markov Models and Statistics to Learn, Extract, Fuse, and Detect Patterns in Raw Data

Many systems are partially stochastic in nature. We have derived data driven approaches for extracting stochastic state machines (Markov models) directly from observed data. This chapter provides an overview of our approach with numerous practical applications. We have used this approach for inferring shipping patterns, exploiting computer system side-channel information, and detecting botnet activities. For contrast, we include a related data-driven statistical inferencing approach that detects and localizes radiation sources.Comment: Accepted by 2017 International Symposium on Sensor Networks, Systems and Securit

The effect of Dnaaf5 gene dosage on primary ciliary dyskinesia phenotypes

DNAAF5 is a dynein motor assembly factor associated with the autosomal heterogenic recessive condition of motile cilia, primary ciliary dyskinesia (PCD). The effects of allele heterozygosity on motile cilia function are unknown. We used CRISPR-Cas9 genome editing in mice to recreate a human missense variant identified in patients with mild PCD and a second, frameshift-null deletion in Dnaaf5. Litters with Dnaaf5 heteroallelic variants showed distinct missense and null gene dosage effects. Homozygosity for the null Dnaaf5 alleles was embryonic lethal. Compound heterozygous animals with the missense and null alleles showed severe disease manifesting as hydrocephalus and early lethality. However, animals homozygous for the missense mutation had improved survival, with partially preserved cilia function and motor assembly observed by ultrastructure analysis. Notably, the same variant alleles exhibited divergent cilia function across different multiciliated tissues. Proteomic analysis of isolated airway cilia from mutant mice revealed reduction in some axonemal regulatory and structural proteins not previously reported in DNAAF5 variants. Transcriptional analysis of mouse and human mutant cells showed increased expression of genes coding for axonemal proteins. These findings suggest allele-specific and tissue-specific molecular requirements for cilia motor assembly that may affect disease phenotypes and clinical trajectory in motile ciliopathies

Influence of viral infection on the relationships between airway cytokines and lung function in asthmatic children

Abstract Background Few longitudinal studies examine inflammation and lung function in asthma. We sought to determine the cytokines that reduce airflow, and the influence of respiratory viral infections on these relationships. Methods Children underwent home collections of nasal lavage during scheduled surveillance periods and self-reported respiratory illnesses. We studied 53 children for one year, analyzing 392 surveillance samples and 203 samples from 85 respiratory illnesses. Generalized estimated equations were used to evaluate associations between nasal lavage biomarkers (7 mRNAs, 10 proteins), lung function and viral infection. Results As anticipated, viral infection was associated with increased cytokines and reduced FVC and FEV1. However, we found frequent and strong interactions between biomarkers and virus on lung function. For example, in the absence of viral infection, CXCL10 mRNA, MDA5 mRNA, CXCL10, IL-4, IL-13, CCL4, CCL5, CCL20 and CCL24 were negatively associated with FVC. In contrast, during infection, the opposite relationship was frequently found, with IL-4, IL-13, CCL5, CCL20 and CCL24 levels associated with less severe reductions in both FVC and FEV1. Conclusions In asthmatic children, airflow obstruction is driven by specific pro-inflammatory cytokines. In the absence of viral infection, higher cytokine levels are associated with decreasing lung function. However, with infection, there is a reversal in this relationship, with cytokine abundance associated with reduced lung function decline. While nasal samples may not reflect lower airway responses, these data suggest that some aspects of the inflammatory response may be protective against viral infection. This study may have ramifications for the treatment of viral-induced asthma exacerbations.https://deepblue.lib.umich.edu/bitstream/2027.42/146519/1/12931_2018_Article_922.pd

Open Science principles for accelerating trait-based science across the Tree of Life.

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges