Search NASA⌕ Search

SEARCH · Search NASA

Results for “Data processing in systems biology”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

Abstract of talk for Silicon Valley Linux Users Group

The use of Linux for research at NASA Ames is discussed.Topics include:work with the Atmospheric Physics branch on software for a spectrometer to be used in the CRYSTAL-FACE mission this summer; work on in the Neuroengineering Lab with code IC including an introduction to the extension of the human senses project,advantages with using linux for real-time biological data processing,algorithms utilized on a linux system, goals of the project,slides of people with Neuroscan caps on, and progress that has been made and how linux has helped.

Clanton, Sam↗

Sensors 2000! Program: Advanced Biosensor and Measurement Systems Technologies for Spaceflight Research and Concurrent, Earth-Based Applications

Sensors 2000! (S2K!) is a specialized, integrated projects team organized to provide focused, directed, advanced biosensor and bioinstrumentation systems technology support to NASA's spaceflight and ground-based research and development programs. Specific technology thrusts include telemetry-based sensor systems, chemical/ biological sensors, medical and physiological sensors, miniaturized instrumentation architectures, and data and signal processing systems. A concurrent objective is to promote the mutual use, application, and transition of developed technology by collaborating in academic-commercial-govemment leveraging, joint research, technology utilization and commercialization, and strategic partnering alliances. Sensors 2000! is organized around three primary program elements: Technology and Product Development, Technology infusion and Applications, and Collaborative Activities. Technology and Product Development involves development and demonstration of biosensor and biotelemetry systems for application to NASA Space Life Sciences Programs; production of fully certified spaceflight hardware and payload elements; and sensor/measurement systems development for NASA research and development activities. Technology Infusion and Applications provides technology and program agent support to identify available and applicable technologies from multiple sources for insertion into NASA's strategic enterprises and initiatives. Collaborative Activities involve leveraging of NASA technologies with those of other government agencies, academia, and industry to concurrently provide technology solutions and products of mutual benefit to participating members.

Hines, J.↗

New developments in space radiation research at NASA: Annotating data using a novel radiation biology ontology

Like many interdisciplinary sciences, data producers and consumers in the field of radiation biology often use a wide variety of terminology to describe their experiments and data. Furthermore, space systems and technologies are rapidly evolving, and a shared understanding and common terminology for these is also lacking. The efficiency of research organizations can be enhanced by standardizing metadata through the use of knowledge resources like ontologies. Employing a sophisticated model such as a formal ontology to standardize metadata enables automated data acquisition processes and supports more complete, accurate meta-analysis through more efficient and complete data discovery and retrieval, particularly when using multiple data sources. Thus, we developed the Radiation Biology Ontology (RBO) in order to improved radiation biology metadata uniformity and transparency. We used open-source software (the Ontology Development Kit, Protégé and WebProtégé) and worked within the OBO Foundry framework, which includes a set of ontology development principles and practices for ontology consistency, uniformity, and accountability. The RBO has now been incorporated into two radiation research data repositories, NASA’s GeneLab omics database (https://genelab.nasa.gov), and the European Commission STORE database (https://www.storedb.org/). Continuous build integration tools allowed our international RBO collaboration to be more efficient and focus its efforts on semantic model design. Currently, the RBO contains over 300 annotated classes and individuals specific to the study of radiation on biological systems, as well as imports of many additional classes from other OBO Foundry ontologies that relate to and/or provide context for these RBO entities. We publish the RBO through the OBO Foundry, so that it is available for browsing, download, and querying through NCBI Bioportal web site and application programming interface. The NASA Ames Life Science Data Archive (ALSDA) is also in the process of adopting use of the RBO, taking NASA one step closer to a knowledge-based system for space biology data. It is our hope that the global communities of radiation research Investigators, data curators and data analysts can similarly leverage the RBO and will contribute to its further development.

radiation↗

Aircraft laser derived chlorophyll distribution across the Iceland-Faeroe front

The ocean surface color (water-leaving radiances) and thermal structure across the Iceland-Faeroe Front under both clear and cloudy conditions were measured from a NASA research aircraft on 25 May 1989. The measurements were made along four north-south lines that were 125 km in length and spaced 35 km apart. The color measurements were made with a 14 channel, non-polarized Multispectral Airborne Radiometer System (MARS) while the thermal data were collected by a thermal radiometer and aircraft bathythermographs. The satellite imagery (NOAA AVHRR) sequence show the development of meanders through the frontal region. These aircraft ocean color and thermal data characterize the biological distribution and are closely coupled to the physical processes occurring in the frontal systems. The ratio of several channels of the ocean color data are used to determine the surface chlorophyll. The retrieved data correlate well with laser-induced chlorophyll fluorescence obtained at the same time and historical chlorophyll data. The observed chlorophyll patchiness appearing across the Iceland-Faeroe Front is believed to be directly and indirectly related to primary and secondary circulation processes in ocean frontal systems. High chlorophyll concentrations were observed on the north side of the front and are inferred to be the result from the advection of Icelandic Coastal Water into the region. The sharp chlorophyll decline at and south of the thermal frontal boundary is clearly related to the subsurface thermal structure.

Arnone, Robert A.↗

GL4U: Using Space Biology Omics Data to Provide Bioinformatics Training for Students and Educators

NASA’s GeneLab project provides researchers open access to space-relevant multi-omics data via the Open Science Data Repository (OSDR) that can be mined to understand the effects of spaceflight on biological systems. To maximize the number of scientists who understand and utilize GeneLab data and data processing pipelines, GeneLab created GeneLab for Colleges and Universities (GL4U). GL4U provides space biology-relevant training in bioinformatics to the next generation of scientists through direct (training students) and indirect (training educators) approaches. The GL4U pilot programs were conducted in June 2021 (direct training) and 2022 (indirect training). During the pilots, students and educators at Historically Black Colleges and Universities (HBCUs) and Minority Serving Institutions (MSIs) participated in a week-long (direct training) or two-week-long (indirect training) bootcamp consisting of space biology-specific lectures and hands-on instruction using Jupyter Notebooks to analyze space biology RNA sequencing data from OSDR. During the educator pilot, participants received materials, training, and the necessary compute resources to enable them to run the bootcamp at their home institutions, thereby extending the reach of this initiative. In July 2023, GeneLab is partnering with JPL to expand GL4U to include amplicon sequencing (Amp-Seq) analysis training. During the GL4U Amp-Seq bootcamp, student and educator participants will receive training on how to analyze and interpret Amp-Seq data using the NASA GeneLab data processing pipeline. All bootcamp material, including instructions for requesting compute resources, will be made publicly available on GitHub for educators to teach the GL4U content in subsequent semesters. GL4U provides undergraduate students from underrepresented groups the opportunity to learn about NASA and Space Biology, and to enhance their career prospects by gaining hands-on experience analyzing omics data, a skillset that is highly applicable and marketable in the life sciences. We present results from pre- and post-training surveys completed by all participants of the Amp-Seq bootcamp.

Amanda M Saravia-Butler↗

GL4U: Bioinformatics training for students and educators using space omics data

NASA’s GeneLab project provides researchers open access to space-relevant experiment multi-omics data that can be mined to understand the effects of spaceflight on biological systems. To maximize the number of scientists who understand and utilize GeneLab data and data processing pipelines, GeneLab has created GeneLab for Colleges and Universities (GL4U). GL4U provides space biology-relevant training in bioinformatics to the next generation of scientists through direct and indirect approaches. The GeneLab team plans to host two annual data processing bootcamps, one for college-level students (direct) and one for college educators (indirect – training of trainers), in which participants learn to analyze GeneLab’s space-relevant omics data. The GL4U direct training pilot program was conducted in June 2021. During the pilot, students participated in a week-long bootcamp consisting of space biology-specific lectures and hands-on instruction using Jupyter Notebooks to analyze RNA sequence data. This pilot demonstrated the capacity of GL4U for training young scientists and encouraging data re-use. During the educator pilot, scheduled for June 2022, educators will receive materials and training to enable them to run the bootcamp at their home institutions or alternatively to adapt the content to implement within existing courses, thereby extending the reach of this initiative.

Amanda Marie Saravia-butler↗

GL4U: Using Space Omics Data to Provide Bioinformatics Training for Students and Educators

NASA’s GeneLab project provides researchers open access to space-relevant experiment multi-omics data that can be mined to understand the effects of spaceflight on biological systems. To maximize the number of scientists who understand and utilize GeneLab data and data processing pipelines, GeneLab has created GeneLab for Colleges and Universities (GL4U). GL4U provides space biology-relevant training in bioinformatics to the next generation of scientists through direct and indirect approaches. The GeneLab team plans to host two annual data processing bootcamps, one for college-level students (direct) and one for college educators (indirect – training of trainers), in which participants learn to analyze GeneLab’s space-relevant omics data. The GL4U direct training pilot program was conducted in June 2021. During the pilot, students participated in a week-long bootcamp consisting of space biology-specific lectures and hands-on instruction using Jupyter Notebooks to analyze RNA sequence data. This pilot demonstrated the capacity of GL4U for training young scientists and encouraging data re-use. In June 2022, GL4U partnered with Jet Propulsion Laboratory’s (JPL) Planetary Protection Center of Excellence to conduct the indirect training pilot program by training educators at historically black colleges and universities (HBCUs) and minority serving institutions (MSIs). During the educator pilot, participants received materials, training, and will be provided the necessary compute resources to enable them to run the bootcamp at their home institutions or alternatively to adapt the content to implement within existing courses, thereby extending the reach of this initiative. The GL4U training program provides undergraduate students from underrepresented groups the opportunity to learn about NASA and Space Biology, and to enhance their career prospects by gaining hands-on experience analyzing omics data, a skillset that is highly applicable and marketable in the life sciences. Pre- and post-bootcamp surveys were completed by all participants and show the overwhelming success of the bootcamps.

Amanda M. Saravia-Butler↗

GL4U: Bioinformatics Training for Students and Educators Using Space Omics Data

NASA’s GeneLab project provides researchers open access to space-relevant experiment multi-omics data that can be mined to understand the effects of spaceflight on biological systems. To maximize the number of scientists who understand and utilize GeneLab data and data processing pipelines, GeneLab has created GeneLab for Colleges and Universities (GL4U). GL4U provides space biology-relevant training in bioinformatics to the next generation of scientists through direct and indirect approaches. The GeneLab team plans to host two annual data processing bootcamps, one for college-level students (direct) and one for college educators (indirect – training of trainers), in which participants learn to analyze GeneLab’s space-relevant omics data. The GL4U direct training pilot program was conducted in June 2021. During the pilot, students participated in a week-long bootcamp consisting of space biology-specific lectures and hands-on instruction using Jupyter Notebooks to analyze RNA sequence data. This pilot demonstrated the capacity of GL4U for training young scientists and encouraging data re-use. During the educator pilot, scheduled for June 2022, educators will receive materials and training to enable them to run the bootcamp at their home institutions or alternatively to adapt the content to implement within existing courses, thereby extending the reach of this initiative.

Amanda Marie Saravia-butler↗

Federated Giovanni: A Distributed Web Service for Analysis and Visualization of Remote Sensing Data

The Geospatial Interactive Online Visualization and Analysis Interface (Giovanni) is a popular tool for users of the Goddard Earth Sciences Data and Information Services Center (GES DISC) and has been in use for over a decade. It provides a wide variety of algorithms and visualizations to explore large remote sensing datasets without having to download the data and without having to write readers and visualizers for it. Giovanni is now being extended to enable its capabilities at other data centers within the Earth Observing System Data and Information System (EOSDIS). This Federated Giovanni will allow four other data centers to add and maintain their data within Giovanni on behalf of their user community. Those data centers are the Physical Oceanography Distributed Active Archive Center (PO.DAAC), MODIS Adaptive Processing System (MODAPS), Ocean Biology Processing Group (OBPG), and Land Processes Distributed Active Archive Center (LP DAAC). Three tiers are supported: Tier 1 (GES DISC-hosted) gives the remote data center a data management interface to add and maintain data, which are provided through the Giovanni instance at the GES DISC. Tier 2 packages Giovanni up as a virtual machine for distribution to and deployment by the other data centers. Data variables are shared among data centers by sharing documents from the Solr database that underpins Giovanni's data management capabilities. However, each data center maintains their own instance of Giovanni, exposing the variables of most interest to their user community. Tier 3 is a Shared Source model, in which the data centers cooperate to extend the infrastructure by contributing source code.

Giovanni↗

Exobiology and the search for biological signatures on Mars

In preparation for a Mars Rover/Sample return mission, the mission goals and objectives must be identified. One of the most important objectives must address exobiology and the question of the possibility of the origin and evolution of life on Mars. In particular, key signatures or bio-markers of a possible extinct Martian biota must be defined. To that end geographic locations (sites) that are likely to contain traces of past life must also be identified. Sites and experiments are being defined in support of a Mars rover sample return mission. In addition, analyses based on computer models of abiotic processes of CO2 loss from Mars suggest that the CO2 from the atmosphere may have precipitated as carbonates and be buried within the Martian regolith. The carbon cycle of perennially frozen lakes in the dry valley of Antarctica are currently being investigated. These lakes were purported to be a model system for the ancient Martian lakes. By understanding the dynamic balance between the abiotic vs. biotic cycling of carbon within this system, information is gathered which will enable the interpretation of data obtained by a Mars rover with respect to possible carbonate deposits and the processing of carbon by biological systems. These ancient carbonate deposits, and other sedimentary units would contain traces of biological signatures that would hold the key to understanding the origin and evolution of life on Mars, as well as Earth.

Mancinelli, Rocco L.↗

Enabling Space Biological Knowledge Discovery Through Image and Video Data Sharing

Increased biomedical risks associated with deep space crewed missions (cis-Lunar, Mars transit/surface) require development of health countermeasures, novel ecosystem support, risk modeling, and fundamental space biological knowledge discovery. Molecular-omics, physiological-phenotypic-behavioral, and environmental-radiation telemetry data from space biological and health studies are needed for reuse by scientists to address these tasks. The data as well as space-relevant biospecimens are being made more findable, accessible, interoperable, and reusable through NASA’s Open Science Data Repository (OSDR). This new OSDR umbrella grouping includes NASA GeneLab, the NASA Ames Life Sciences Data Archive (ALSDA), and the NASA Biological Institutional Scientific Collection. The OSDR system design appropriately handles metadata and processed-tabular results from ALSDA studies collected from space experiments. But raw and processed ALSDA bioimage and video datasets require an expansion of OSDR’s data architecture to handle ingestion, curation, and egress. The academic-industry bioimaging field saw a scientific renaissance in the past several years through leveraging open-source software, international collaborations, machine learning, and other open science/programming approaches. As crewed missions and more biological experiments are on the deep space horizon, OSDR is embracing data stewardship through listening to feedback from subject matter experts and designing an expanded architecture which is appropriate for NASA’s goals to enable analysis and reuse of bioimaging and video data for the public science community.Discovery Through Image and Video Data Sharing

space biology↗

Fluid Interfaces of Triangular Containers in Reduced Gravity Environments

Capillary dominated fluid dynamics will be examined in a reduced-gravity environment onboard the KC-135; in particular, the behavior of the lower portion of the meniscus in triangular tank geometries. Seven clear acrylic tanks were constructed to view seven angles of the four geometries. Silicon oil with two different viscosities, 2cs and 5cs silicon oil, were used on different days of the flight. Six tanks and one control tank are filled with a certain viscosity fluid for each flight day. During each parabola, three tanks are tested at time. The experimental tanks are exchanged between parabola sets on the KC-135. The 60deg -60deg -60deg control tank is viewed throughout the flight. To gather data, two digital video cameras and one digital still camera are placed perpendicular the viewing surface. To provide a greater contrast in the meniscus, an EL backlighting sheet was used to backlight the tanks. These images and video are then digitized, passed through NASA's mini-tracker software, and compared to a theory published my M. M. Weislogel, "Fluid Interface Phenomena in a Low-Gravity Environment: Recent Results from Drop Tower Experimentation." By focusing on a lower portion of the meniscus and using longer periods of reduced gravity, this experiment may confirm that a stationary point exists on the fluid surface. This information will enable better designing of propellant management devices, especially satellite propellant refilling and gas venting. Also, biological and material processing systems in reduced gravity environments will benefit from this data.

Guttromson, Jayleen↗

Neural network for processing both spatial and temporal data with time based back-propagation

Neural networks are computing systems modeled after the paradigm of the biological brain. For years, researchers using various forms of neural networks have attempted to model the brain's information processing and decision-making capabilities. Neural network algorithms have impressively demonstrated the capability of modeling spatial information. On the other hand, the application of parallel distributed models to the processing of temporal data has been severely restricted. The invention introduces a novel technique which adds the dimension of time to the well known back-propagation neural network algorithm. In the space-time neural network disclosed herein, the synaptic weights between two artificial neurons (processing elements) are replaced with an adaptable-adjustable filter. Instead of a single synaptic weight, the invention provides a plurality of weights representing not only association, but also temporal dependencies. In this case, the synaptic weights are the coefficients to the adaptable digital filters. Novelty is believed to lie in the disclosure of a processing element and a network of the processing elements which are capable of processing temporal as well as spacial data.

Villarreal, James A.↗

Methods for the development of a bioregenerative life support system

Presented here is a rudimentary approach to designing a life support system based on the utilization of plants and animals. The biggest stumbling block in the initial phases of developing a bioregenerative life support system is encountered in collecting and consolidating the data. If a database existed for the systems engineer so that he or she may have accurate data and a better understanding of biological systems in engineering terms, then the design process would be simplified. Also addressed is a means of evaluating the subsystems chosen. These subsystems are unified into a common metric, kilograms of mass, and normalized in relation to the throughput of a few basic elements. The initial integration of these subsystems is based on input/output masses and eventually balanced to a point of operation within the inherent performance ranges of the organisms chosen. At this point, it becomes necessary to go beyond the simplifying assumptions of simple mass relationships and further define for each organism the processes used to manipulate the throughput matter. Mainly considered here is the fact that these organisms perform input/output functions on differing timescales, thus establishing the need for buffer volumes or appropriate subsystem phasing. At each point in a systematic design it is necessary to disturb the system and discern its sensitivity to the disturbance. This can be done either through the introduction of a catastrophic failure or by applying a small perturbation to the system. One example is increasing the crew size. Here the wide range of performance characteristics once again shows that biological systems have an inherent advantage in responding to systemic perturbations. Since the design of any space-based system depends on mass, power, and volume requirements, each subsystem must be evaluated in these terms.

Goldman, Michelle↗

Understanding the Radiant Scattering Behavior of Vegetated Scenes

Knowledge of the physics of the scattering behavior of vegetation will ultimately serve the remote sensing and earth science community in many ways. For example, it will provide: (1) insight and guidance in developing new extraction techniques of canopy characteristics, (2) a basis for better interpretation of off-nadir satellite and aircraft data, (3) a basis for defining specifications of future earth observing sensor systems, and (4) a basis for defining important aspects of physical and biological processes of the plant system. The overall objective of the three-year study is to improve our fundamental understanding of the dynamics of directional scattering properties of vegetation canopies through analysis of field data and model simulation data. The specific objectives are to: (1) collect directional reflectance data covering the entire exitance hemisphere for several common vegetation canopies with various geometric structure (both homogeneous and row crop structures), (2) develop a scene radiation model with a general mathematical framework which will treat 3-D variability in heterogeneous scenes and account for 3-D radiant interactions within the scene, (3) conduct validations of the model on collected data sets, and (4) test and expand proposed physical scattering mechanisms involved in reflectance distribution dynamics by analyzing both field and modeling data.

Kimes, D. S.↗

Cross Kingdom Analysis of Data Within the GeneLab Repository Identifies a Potential Conserved Response of Life to the Stress Associated with Spaceflight

It is important to determine the health risks and potential survival for astronauts associated with long-term space missions. This entails not only understanding the impact the space environment will have on humans, but also how it will affect other organisms needed for humans to survive in space such as plants. In addition, it has been reported in the literature that hundreds of genes seem to be conserved and/or transferred between different organisms from bacteria, archaea, fungi, microorganisms, and plants to animals. Since space travel involves humans in a closed environment over a long period of time, we hypothesize that potential conserved biological factors will occur between the different organisms in that environment possibly due to transfer of genes. Determining the conserved factors that are commonly being regulated in space can shed insight into possible universal master regulators and also determine the symbiotic relationship between the organisms in space. Utilizing NASA's GeneLab Data Repository (a rapidly expanding, curated clustering of spaceflight-related ‘omics-level datasets for all organisms), we were able to uncover a novel pathway and factors that were commonly shared between humans, mice, plants, C. Elegans, and drosophilas. Through ChIP-Seq enrichment analysis techniques utilizing various GeneLab datasets from each species that were flown in space, we found the following factors to be conserved across all species: oxidative stress, DNA damage (through GABPA/NRFs and NFY), SIX5, GTF2B and glutamine synthetase. Such commonalities would likely reflect the effects of factors such as microgravity and the increased radiation exposure inherent in spaceflight on basic physical processes shared by all biological systems at the cellular level. Differences between organismal responses revealed by GeneLab's data should also help understand the unique reactions to life in space that arise from the very different lifestyles of microbes, animals and plants.

Barker, Richard↗