GAGE: generally applicable gene set enrichment for pathway analysis

<p>Abstract</p> <p>Background</p> <p>Gene set analysis (GSA) is a widely used strategy for gene expression data analysis based on pathway knowledge. GSA focuses on sets of related genes and has established major advantages over individual gene analyses, including greater robustness, sensitivity and biological relevance. However, previous GSA methods have limited usage as they cannot handle datasets of different sample sizes or experimental designs.</p> <p>Results</p> <p>To address these limitations, we present a new GSA method called Generally Applicable Gene-set Enrichment (GAGE). We successfully apply GAGE to multiple microarray datasets with different sample sizes, experimental designs and profiling techniques. GAGE shows significantly better results when compared to two other commonly used GSA methods of GSEA and PAGE. We demonstrate this improvement in the following three aspects: (1) consistency across repeated studies/experiments; (2) sensitivity and specificity; (3) biological relevance of the regulatory mechanisms inferred.</p> <p>GAGE reveals novel and relevant regulatory mechanisms from both published and previously unpublished microarray studies. From two published lung cancer data sets, GAGE derived a more cohesive and predictive mechanistic scheme underlying lung cancer progress and metastasis. For a previously unpublished BMP6 study, GAGE predicted novel regulatory mechanisms for BMP6 induced osteoblast differentiation, including the canonical BMP-TGF beta signaling, JAK-STAT signaling, Wnt signaling, and estrogen signaling pathways–all of which are supported by the experimental literature.</p> <p>Conclusion</p> <p>GAGE is generally applicable to gene expression datasets with different sample sizes and experimental designs. GAGE consistently outperformed two most frequently used GSA methods and inferred statistically and biologically more relevant regulatory pathways. The GAGE method is implemented in R in the "gage" package, available under the GNU GPL from <url>http://sysbio.engin.umich.edu/~luow/downloads.php</url>.</p

The Sage-Grouse Habitat Mortgage: Effective Conifer Management in Space and Time

AbstractManagement of conservation-reliant species can be complicated by the need to manage ecosystem processes that operate at extended temporal horizons. One such process is the role of fire in regulating abundance of expanding conifers that disrupt sage-grouse habitat in the northern Great Basin of the United States. Removing conifers by cutting has a beneficial effect on sage-grouse habitat. However, effects may last only a few decades because conifer seedlings are not controlled and the seed bank is fully stocked. Fire treatment may be preferred because conifer control lasts longer than for mechanical treatments. The amount of conservation needed to control conifers at large temporal and spatial scales can be quantified by multiplying land area by the time needed for conifer abundance to progress to critical thresholds (i.e., “conservation volume”). The contribution of different treatments in arresting conifer succession can be calculated by dividing conservation volume by the duration of treatment effect. We estimate that fire has approximately twice the treatment life of cutting at time horizons approaching 100 yr, but, has high up-front conservation costs due to temporary loss of sagebrush. Cutting has less up-front conservation costs because sagebrush is unaffected, but it is more expensive over longer management time horizons because of decreased durability. Managing conifers within sage-grouse habitat is difficult because of the necessity to maintain the majority of the landscape in sagebrush habitat and because the threshold for negative conifer effects occurs fairly early in the successional process. The time needed for recovery of sagebrush creates limits to fire use in managing sage-grouse habitat. Utilizing a combination of fire and cutting treatments is most financially and ecologically sustainable over long time horizons involved in managing conifer-prone sage-grouse habitat

Project X functional requirements specification

Project X is a multi-megawatt proton facility being developed to support intensity frontier research in elementary particle physics, with possible applications to nuclear physics and nuclear energy research, at Fermilab. A Functional Requirements Specification has been developed in order to establish performance criteria for the Project X complex in support of these multiple missions. This paper will describe the Functional Requirements for the Project X facility and the rationale for these requirements.Comment: 3 pp. Particle Accelerator, 24th Conference (PAC'11) 28 Mar - 1 Apr 2011: New York, US

Restoring North America’s Sagebrush Steppe Ecosystem Using Seed Enhancement Technologies

Rangelands occupy over a third of global land area, and in many cases are in less than optimum condition as a result of past land use, catastrophic wildfire and other disturbance, invasive species, or climate change. Often the only means of restoring these lands involves seeding desirable species, yet there are few cost effective seeding technologies, especially for the more arid rangeland types. The inability to consistently establish desired plants from seed may indicate that the seeding technologies being used are not successful in addressing the primary sources of mortality in the progression from seed to established plant. Seed enhancement technologies allow for the physical manipulation and application of materials to the seed that can enhance germination, emergence, and/or early seedling growth. In this article we examine some of the major limiting factors impairing seedling establishment in North America’s native sagebrush steppe ecosystem, and demonstrate how seed enhancement technologies can be employed to overcome these restoration barriers. We discuss specific technologies for: (1) increasing soil water availability; (2) enhancing seedling emergence in crusting soil; (3) controlling the timing of seed germination; (4) improving plantability and emergence of small seeded species; (5) enhancing seed coverage of broadcasted seeds; and (6) improving selectivity of pre-emergent herbicide. Concepts and technologies in this paper for restoring the sagebrush steppe ecosystem may apply generally to semi-arid and arid rangelands around the globe

NMR-based assignment of isoleucine vs allo-isoleucine stereochemistry

A simple 1H and 13C NMR spectrometric analysis is demonstrated that permits differentiation of isoleucine and allo-isoleucine residues by inspection of the chemical shift and coupling constants of the signals associated with the proton and carbon at the α-stereocentre. This is applied to the estimation of epimerisation during metal-free N-arylation and peptide coupling reactions

Carcass Trait Effects from Environment, Growth Rate on Pasture, and Breedtypes

Last updated: 6/12/200

Project X functional requirements specification

Project X is a multi-megawatt proton facility being developed to support a world-leading program in Intensity Frontier physics at Fermilab. The facility is designed to support programs in elementary particle and nuclear physics, with possible applications to nuclear energy research. A Functional Requirements Specification has been developed in order to establish performance criteria for the Project X complex in support of these multiple missions, and to assure that the facility is designed with sufficient upgrade capability to provide U.S. leadership for many decades to come. This paper will briefly review the previously described Functional Requirements, and then discuss their recent evolution.Comment: 3 p

Innovation in Rangeland Monitoring: Annual, 30 M, Plant Functional Type Percent Cover Maps for U.S. Rangelands, 1984-2017

Innovations in machine learning and cloud‐based computing were merged with historical remote sensing and field data to provide the first moderate resolution, annual, percent cover maps of plant functional types across rangeland ecosystems to effectively and efficiently respond to pressing challenges facing conservation of biodiversity and ecosystem services. We utilized the historical Landsat satellite record, gridded meteorology, abiotic land surface data, and over 30,000 field plots within a Random Forests model to predict per‐pixel percent cover of annual forbs and grasses, perennial forbs and grasses, shrubs, and bare ground over the western United States from 1984 to 2017. Results were validated using three independent collections of plot‐level measurements, and resulting maps display land cover variation in response to changes in climate, disturbance, and management. The maps, which will be updated annually at the end of each year, provide exciting opportunities to expand and improve rangeland conservation, monitoring, and management. The data open new doors for scientific investigation at an unprecedented blend of temporal fidelity, spatial resolution, and geographic scale