Convergence properties of simple genetic algorithms

The essential parameters determining the behaviour of genetic algorithms were investigated. Computer runs were made while systematically varying the parameter values. Results based on the progress curves obtained from these runs are presented along with results based on the variability of the population as the run progresses

Improving Thermodynamic Models of Transcription by Combining ChIP and Expression Measurements of Synthetic Promoters

Regulation of gene expression is a fundamental process in biology. Accurate mathematical models of the relationship between regulatory sequence and observed expression would advance our understanding of biology. I developed ReLoS, a regulatory logic simulator, to explore mathematical frameworks for describing the relationship between regulatory sequence and observed expression and to explore methods of learning combinatorial regulatory rules from expression data. ReLoS is a flexible simulator allowing a variety of formalisms to be applied. ReLoS was used to explore the question of how complex rules of combinatorial transcriptional regulation must be to explain the complexity of transcriptional regulation observed in biology. A previously published dataset was analyzed for regulatory elements that explained the behavior of regulatory modules for 254 genes in 255 conditions. I found that ReLoS was able to recapitulate a reasonable fraction of the variation: mean gene-wise correlation of 0.7) with only twelve combinatorial rules comprising 13 cis-regulatory elements. This result suggested that learning the combinatorial rules of transcriptional regulation should be possible. State ensemble statistical thermodynamic models are a class of models used to describe combinatorial transcriptional regulation. One way to parameterize these models is measuring the expression of a reporter gene driven by many similar promoters . Models parameterized in this fashion do better at explaining the sequence to expression relationship, but fail to distinguish between multiple biological mechanisms that give rise to equivalent expression results in the synthetic promoters, thus limiting the generalizability of the models. I developed a ChIP-based strategy for quantitatively measuring the relative occupancy of transcription factors on synthetic promoters. This data complements existing methods for obtaining expression data from the same promoters. Comparison of models parameterized with only expression, only occupancy, or expression and occupancy reveals specific biological details that are missed when considering only expression data. In particular, the occupancy data suggests that differential regulatory effects of Cbf1 in glucose versus amino acid are a function of how it interacts with polymerase rather than changes in concentration or binding affinity. Additionally, the occupancy data suggests that Gcn4 binds in a cooperative manner and that Gcn4 occupancy is adversely affected by the presence of a nearby Nrg1 site. Finally, the occupancy data and expression data taken together suggest that Gcn4 binds in competition with another transcription factor. Synthesizing disparate sources of information resulted in an improved understanding of the mechanics of transcriptional regulation of the synthetic promoters and was ultimately largely successful in decoupling the DNA binding energies from the TF interactions with polymerase. However, it suggests that more sophisticated models of the relationship between occupancy and expression may be required in at least some cases. Incorporating different sources of data into models of regulation will continue to be important for learning the biological specifics that drive expression changes

Synthesis of calculational methods for the design and analysis of radiation shields for nuclear rocket systems. Volume 2 - Analysis of radiation measurements in a nuclear rocket propellant tank mockup using simulated liquid hydrogen

Calculational methods for nuclear rocket radiation shield design - analysis of radiation measurements in nuclear rocket propellant tank mockup using simulated liquid hydroge

Discrimination between thermodynamic models of cis-regulation using transcription factor occupancy data

Many studies have identified binding preferences for transcription factors (TFs), but few have yielded predictive models of how combinations of transcription factor binding sites generate specific levels of gene expression. Synthetic promoters have emerged as powerful tools for generating quantitative data to parameterize models of combinatorial cis-regulation. We sought to improve the accuracy of such models by quantifying the occupancy of TFs on synthetic promoters in vivo and incorporating these data into statistical thermodynamic models of cis-regulation. Using chromatin immunoprecipitation-seq, we measured the occupancy of Gcn4 and Cbf1 in synthetic promoter libraries composed of binding sites for Gcn4, Cbf1, Met31/Met32 and Nrg1. We measured the occupancy of these two TFs and the expression levels of all promoters in two growth conditions. Models parameterized using only expression data predicted expression but failed to identify several interactions between TFs. In contrast, models parameterized with occupancy and expression data predicted expression data, and also revealed Gcn4 self-cooperativity and a negative interaction between Gcn4 and Nrg1. Occupancy data also allowed us to distinguish between competing regulatory mechanisms for the factor Gcn4. Our framework for combining occupancy and expression data produces predictive models that better reflect the mechanisms underlying combinatorial cis-regulation of gene expression

Gene expression patterns following unilateral traumatic brain injury reveals a local pro-inflammatory and remote anti-inflammatory response.

BackgroundTraumatic brain injury (TBI) results in irreversible damage at the site of impact and initiates cellular and molecular processes that lead to secondary neural injury in the surrounding tissue. We used microarray analysis to determine which genes, pathways and networks were significantly altered using a rat model of TBI. Adult rats received a unilateral controlled cortical impact (CCI) and were sacrificed 24 h post-injury. The ipsilateral hemi-brain tissue at the site of the injury, the corresponding contralateral hemi-brain tissue, and naïve (control) brain tissue were used for microarray analysis. Ingenuity Pathway Analysis (IPA) software was used to identify molecular pathways and networks that were associated with the altered gene expression in brain tissues following TBI.ResultsInspection of the top fifteen biological functions in IPA associated with TBI in the ipsilateral tissues revealed that all had an inflammatory component. IPA analysis also indicated that inflammatory genes were altered on the contralateral side, but many of the genes were inversely expressed compared to the ipsilateral side. The contralateral gene expression pattern suggests a remote anti-inflammatory molecular response. We created a network of the inversely expressed common (i.e., same gene changed on both sides of the brain) inflammatory response (IR) genes and those IR genes included in pathways and networks identified by IPA that changed on only one side. We ranked the genes by the number of direct connections each had in the network, creating a gene interaction hierarchy (GIH). Two well characterized signaling pathways, toll-like receptor/NF-kappaB signaling and JAK/STAT signaling, were prominent in our GIH.ConclusionsBioinformatic analysis of microarray data following TBI identified key molecular pathways and networks associated with neural injury following TBI. The GIH created here provides a starting point for investigating therapeutic targets in a ranked order that is somewhat different than what has been presented previously. In addition to being a vehicle for identifying potential targets for post-TBI therapeutic strategies, our findings can also provide a context for evaluating the potential of therapeutic agents currently in development

Application of remote sensing to study nearshore circulation

The research to use remote sensing techniques for studying the continental shelf is reported. The studies reported include: (1) nearshore circulation in the vincinity of a natural tidal inlet; (2) identification of indicators of biological activity; (3) remote navigation system for tracking free drifting buoys; (4) experimental design of an estuaring tidal circulation; and (5) Skylab support work

A cis-regulatory logic simulator

<p>Abstract</p> <p>Background</p> <p>A major goal of computational studies of gene regulation is to accurately predict the expression of genes based on the cis-regulatory content of their promoters. The development of computational methods to decode the interactions among cis-regulatory elements has been slow, in part, because it is difficult to know, without extensive experimental validation, whether a particular method identifies the correct cis-regulatory interactions that underlie a given set of expression data. There is an urgent need for test expression data in which the interactions among cis-regulatory sites that produce the data are known. The ability to rapidly generate such data sets would facilitate the development and comparison of computational methods that predict gene expression patterns from promoter sequence.</p> <p>Results</p> <p>We developed a gene expression simulator which generates expression data using user-defined interactions between cis-regulatory sites. The simulator can incorporate additive, cooperative, competitive, and synergistic interactions between regulatory elements. Constraints on the spacing, distance, and orientation of regulatory elements and their interactions may also be defined and Gaussian noise can be added to the expression values. The simulator allows for a data transformation that simulates the sigmoid shape of expression levels from real promoters. We found good agreement between sets of simulated promoters and predicted regulatory modules from real expression data. We present several data sets that may be useful for testing new methodologies for predicting gene expression from promoter sequence.</p> <p>Conclusion</p> <p>We developed a flexible gene expression simulator that rapidly generates large numbers of simulated promoters and their corresponding transcriptional output based on specified interactions between cis-regulatory sites. When appropriate rule sets are used, the data generated by our simulator faithfully reproduces experimentally derived data sets. We anticipate that using simulated gene expression data sets will facilitate the direct comparison of computational strategies to predict gene expression from promoter sequence. The source code is available online and as additional material. The test sets are available as additional material.</p

Drumming Behavior of Selected Nearctic Stoneflies (Plecoptera)

Drumming was recorded for 11 of 13 Nearctic stonefly species, representing 4 families. Both male and female signals were obtained from 5 species, and were either 2-way or 3-way communications. Signals were species-specific; those of males and females varied from 3-39 and 1-14 beats/ signal, respectively. Duration of male signals varied from 105-8,016 ms; those of females, except Perlinella drymo (1 beat), varied from 402-1318 ms. Signals among related taxa showed greatest similarities. Duration of male signals of Perlinella drymo became progressively shorter at each of 4 temperatures from 7-29 0C. Females of Perlinella drymo would only repeatedly answer male signals recorded at near their own temperature, and would not repeatedly answer recorded male signals of 8 other species

Applicability and Utility of the Astromaterials X-Ray Computed Tomography Laboratory at Johnson Space Center

The Astromaterials Acquisition and Curation Office at NASAs Johnson Space Center is responsible for curating all of NASAs astromaterial sample collections (i.e. Apollo samples, Luna Samples, Antarctic Meteorites, Cosmic Dust Particles, Microparticle Impact Collection, Genesis solar wind atoms, Stardust comet Wild-2 particles, Stardust interstellar particles, and Hayabusa asteroid Itokawa particles) [1-3]. To assist in sample curation and distribution, JSC Curation has recently installed an X-ray computed tomography (XCT) scanner to visualize and characterize samples in 3D. [3] describes the instrumental set-up and the utility of XCT to astromaterials curation. Here we describe some of the current and future projects and illustrate the usefulness of XCT in studying astromaterials

The Need for Medical Geology in Space Exploration: Implications for the Journey to Mars and Beyond

The previous manned missions to the Moon represent milestones in human ingenuity, perseverance, and intellectual curiosity. They also highlight a major hazard for future human exploration of the Moon and beyond: surface dust. Not only did the dust cause mechanical and structural integrity issues with the suits, the dust "storm" generated upon reentrance into the crew cabin caused "lunar hay fever" and "almost blindness". It was further reported that the allergic response to the dust worsened with each exposure. The lower gravity environment exacerbated the exposure, requiring the astronauts to wear their helmet within the module in order to avoid breathing the irritating particles. Due to the prevalence of these high exposures, the Human Research Roadmap developed by NASA identifies the Risk of Adverse Health and Performance Effects of Celestial Dust Exposure as an area of concern. Extended human exploration will further increase the probability of inadvertent and repeated exposures to celestial dusts. Going forward, hazard assessments of celestial dusts will be determined through sample return efforts prior to astronaut deployment. However, even then the returned samples could also put the Curators, technicians, and scientists at risk during processing and examination