Stephen A. Ramsey

Bio: Stephen A. Ramsey is an academic researcher from Oregon State University. The author has contributed to research in topics: Workflow & Gene expression profiling. The author has an hindex of 32, co-authored 88 publications receiving 4154 citations. Previous affiliations of Stephen A. Ramsey include Seattle Biomed & University of Washington.

A data integration methodology for systems biology.

Abstract: Different experimental technologies measure different aspects of a system and to differing depth and breadth. High-throughput assays have inherently high false-positive and false-negative rates. Moreover, each technology includes systematic biases of a different nature. These differences make network reconstruction from multiple data sets difficult and error-prone. Additionally, because of the rapid rate of progress in biotechnology, there is usually no curated exemplar data set from which one might estimate data integration parameters. To address these concerns, we have developed data integration methods that can handle multiple data sets differing in statistical power, type, size, and network coverage without requiring a curated training data set. Our methodology is general in purpose and may be applied to integrate data from any existing and future technologies. Here we outline our methods and then demonstrate their performance by applying them to simulated data sets. The results show that these methods select true-positive data elements much more accurately than classical approaches. In an accompanying companion paper, we demonstrate the applicability of our approach to biological data. We have integrated our methodology into a free open source software package named pointillist.

Transport in two-dimensional paper networks

Abstract: Two-dimensional paper networks (2DPNs) hold great potential for transcending the capabilities and performance of today’s paper-based analytical devices. Specifically, 2DPNs enable sophisticated multi-step chemical processing sequences for sample pretreatment and analysis at a cost and ease-of-use that make them appropriate for use in settings with low resources. A quantitative understanding of flow in paper networks is essential to realize the potential of these networks. In this report, we provide a framework for understanding flow in simple 2DPNs using experiments, analytical expressions, and computational simulations.

Function of C/EBPdelta in a regulatory circuit that discriminates between transient and persistent TLR4-induced signals.

Abstract: The innate immune system is like a double-edged sword: it is absolutely required for host defense against infection, but when uncontrolled, it can trigger a plethora of inflammatory diseases. Here we use systems-biology approaches to predict and confirm the existence of a gene-regulatory network involving dynamic interaction among the transcription factors NF-kappaB, C/EBPdelta and ATF3 that controls inflammatory responses. We mathematically modeled transcriptional regulation of the genes encoding interleukin 6 and C/EBPdelta and experimentally confirmed the prediction that the combination of an initiator (NF-kappaB), an amplifier (C/EBPdelta) and an attenuator (ATF3) forms a regulatory circuit that discriminates between transient and persistent Toll-like receptor 4-induced signals. Our results suggest a mechanism that enables the innate immune system to detect the duration of infection and to respond appropriately.

Dizzy: stochastic simulation of large-scale genetic regulatory networks

Abstract: We describe Dizzy, a software tool for stochastically and deterministically modeling the spatially homogeneous kinetics of integrated large-scale genetic, metabolic, and signaling networks. Notable features include a modular simulation framework, reusable modeling elements, complex kinetic rate laws, multi-step reaction processes, steady-state noise estimation, and spatial compartmentalization.

Inflammatory Ly6Chi monocytes and their conversion to M2 macrophages drive atherosclerosis regression

Abstract: Atherosclerosis is a chronic inflammatory disease, and developing therapies to promote its regression is an important clinical goal. We previously established that atherosclerosis regression is characterized by an overall decrease in plaque macrophages and enrichment in markers of alternatively activated M2 macrophages. We have now investigated the origin and functional requirement for M2 macrophages in regression in normolipidemic mice that received transplants of atherosclerotic aortic segments. We compared plaque regression in WT normolipidemic recipients and those deficient in chemokine receptors necessary to recruit inflammatory Ly6Chi (Ccr2-/- or Cx3cr1-/-) or patrolling Ly6Clo (Ccr5-/-) monocytes. Atherosclerotic plaques transplanted into WT or Ccr5-/- recipients showed reduced macrophage content and increased M2 markers consistent with plaque regression, whereas plaques transplanted into Ccr2-/- or Cx3cr1-/- recipients lacked this regression signature. The requirement of recipient Ly6Chi monocyte recruitment was confirmed in cell trafficking studies. Fate-mapping and single-cell RNA sequencing studies also showed that M2-like macrophages were derived from newly recruited monocytes. Furthermore, we used recipient mice deficient in STAT6 to demonstrate a requirement for this critical component of M2 polarization in atherosclerosis regression. Collectively, these results suggest that continued recruitment of Ly6Chi inflammatory monocytes and their STAT6-dependent polarization to the M2 state are required for resolution of atherosclerotic inflammation and plaque regression.

The role of pattern-recognition receptors in innate immunity: update on Toll-like receptors

Abstract: The discovery of Toll-like receptors (TLRs) as components that recognize conserved structures in pathogens has greatly advanced understanding of how the body senses pathogen invasion, triggers innate immune responses and primes antigen-specific adaptive immunity. Although TLRs are critical for host defense, it has become apparent that loss of negative regulation of TLR signaling, as well as recognition of self molecules by TLRs, are strongly associated with the pathogenesis of inflammatory and autoimmune diseases. Furthermore, it is now clear that the interaction between TLRs and recently identified cytosolic innate immune sensors is crucial for mounting effective immune responses. Here we describe the recent advances that have been made by research into the role of TLR biology in host defense and disease.

“Bioinformatics” 특집을 내면서

Abstract: BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

Integrative analysis of 111 reference human epigenomes

Abstract: The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.