FAIR Assessments
Presentation on Findable Accessible Interoperable and Reusable (FAIR) Assessment approaches for data.
FAIR↗
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Impact of the International Space Station Research Results
The International Space Station (ISS) facilitates research that benefits human lives on Earth and serves as the primary testing ground for technology development to sustain life in the extreme environment of space. To date, investigators have published a wide range of ISS science results, from improved theories about the creation of stars to the outcome of data mining “omics” repositories of previously completed ISS investigations. Because of the unique microgravity environment of the ISS laboratory and the multidisciplinary and international nature of the research, analyzing ISS scientific impacts is an exceptional challenge. As a result, the ISS Program Science Forum (PSF), made up of senior science representatives across the ISS international partnership, uses various methods to describe the impacts of ISS research activities. For the most part, past papers written by PSF members to assess the overall ISS research impact have focused on exhibiting ISS research impact by quantifying ISS research output or its perceived benefits for humanity. This paper proposes a new assessment of ISS impact from the perspective of the end users’ needs. To that end, the authors use visualizations and metrics of scientific publication data to show the ISS research influence on traditional scientific fields, its global reach and the benefits to people across the globe.
Diallo, Ousmane N.↗
Machine Learning Approaches to Increasing Value of Spaceflight Omics Databases
The number of spaceflight bioscience mission opportunities is too small to allow all relevant biological and environmental parameters to be experimentally identified. Simulated spaceflight experiments in ground-based facilities (GBFs), such as clinostats, are each suitable only for particular investigations -- a rotating-wall vessel may be 'simulated microgravity' for cell differentiation (hours), but not DNA repair (seconds) -- and introduce confounding stimuli, such as motor vibration and fluid shear effects. This uncertainty over which biological mechanisms respond to a given form of simulated space radiation or gravity, as well as its side effects, limits our ability to baseline spaceflight data and validate mission science. Machine learning techniques autonomously identify relevant and interdependent factors in a data set given the set of desired metrics to be evaluated: to automatically identify related studies, compare data from related studies, or determine linkages between types of data in the same study. System-of-systems (SoS) machine learning models have the ability to deal with both sparse and heterogeneous data, such as that provided by the small and diverse number of space biosciences flight missions; however, they require appropriate user-defined metrics for any given data set. Although machine learning in bioinformatics is rapidly expanding, the need to combine spaceflight/GBF mission parameters with omics data is unique. This work characterizes the basic requirements for implementing the SoS approach through the System Map (SM) technique, a composite of a dynamic Bayesian network and Gaussian mixture model, in real-world repositories such as the GeneLab Data System and Life Sciences Data Archive. The three primary steps are metadata management for experimental description using open-source ontologies, defining similarity and consistency metrics, and generating testing and validation data sets. Such approaches to spaceflight and GBF omics data may soon enable unique insight into which measured phenomena correlate to biological mechanisms that are truly affected by spaceflight conditions; which are most likely to be confounded by other variables; and which are insufficiently characterized, significantly increasing existing and future science return from ISS and spaceflight missions.
Gentry, Diana↗
Open Science for Plants in Space: Data Sharing, Standards, and Informatics for Reuse and Knowledge Discovery
Upcoming deep space missions will rely on plants for crew and ecosystem health. Open access space biology data enables scientists to examine the biological responses of plants to ionizing radiation, altered gravity, low atmospheric pressure, elevated CO2, altered photoperiods and many other abiotic stressors. Open Science is the practice of making research available to all, while respecting diverse cultures, and fostering collaborations with equity. 2023 is the ‘Year of Open Science’, and NASA has a 5-year Transform to Open Science (TOPS) initiative designed to rapidly transform the agency toward an inclusive culture of open science. NASA’s Open Science Data Repository (OSDR) within NASA’s Biological and Physical Sciences Division provides access to data from space-relevant biological experiments. OSDR combines two databases, GeneLab and Ames Life Sciences Data Archive (ALSDA) to maximize access to standardized ‘omics (e.g., transcriptomics, proteomics) and phenotypic data (e.g., microscopy, biomass), respectively. GeneLab started in 2014 with the creation of the first space-relevant FAIR (Findable, Accessible, Interoperable, Reusable) biological ‘omics repository, providing detailed metadata on investigation, sample, and assay levels. The addition of ALSDA to OSDR expands plant data analysis capabilities across both phenotypic and ‘omics data. Today, OSDR hosts 62+ plant datasets and has enabled 58 peer-reviewed publications. Most of these publications were collaboration efforts under the OSDR Analysis Working Groups (AWGs). AWGs provide great opportunities for investigators to collaborate and set new standards for space-relevant data and metadata. The AWGs welcome any ASPB members interested in contributing plant expertise for space biology, and to serve as subject matter experts as we establish the framework for modern plant data archiving. Investigators are invited to submit their space-relevant plant datasets to OSDR and visit the site to learn about the tools OSDR has to offer (osdr.nasa.gov/bio).
FAIR↗
Open Science for Plants in Space: Data Sharing, Standards, and Informatics for Reuse and Knowledge Discovery
Upcoming deep space missions will rely on plants for crew and ecosystem health. Open access space biology data enables scientists to examine the biological responses of plants to ionizing radiation, altered gravity, low atmospheric pressure, elevated CO2, altered photoperiods and many other abiotic stressors. Open Science is the practice of making research available to all, while respecting diverse cultures, to foster collaborations with equity. NASA has declared 2023 as the ‘Year of Open Science’ and created a 5-year Transform to Open Science (TOPS) initiative designed to rapidly transform the agency toward an inclusive culture of open science. NASA’s Open Science Data Repository (OSDR) within the Biological and Physical Sciences Division provides access to data from space-relevant biological experiments. OSDR combines two databases, GeneLab and Ames Life Sciences Data Archive (ALSDA) to maximize access to standardized ‘omics (e.g., transcriptomics, proteomics) and phenotypic data (e.g., microscopy, biomass), respectively. GeneLab started in 2014 with the creation of the first space-relevant FAIR (Findable, Accessible, Interoperable, Reusable) biological ‘omics repository, providing detailed metadata on investigation, sample, and assay levels. The addition of ALSDA to OSDR expands plant data analysis capabilities across both phenotypic and ‘omics data. Today, OSDR hosts 62+ plant datasets and has enabled 58 peer-reviewed publications. Most of these publications were collaboration efforts under the OSDR Analysis Working Groups (AWGs). AWGs provide great opportunities for investigators to collaborate with community members and set new standards for space-relevant data and metadata. The AWGs welcome any ASGSR members interested in contributing plant expertise for space biology, and to serve as subject matter experts as we establish the framework for modern plant data archiving. Investigators are encouraged to submit their space-relevant plant datasets to OSDR and visit the site to learn about the tools OSDR has to offer (osdr.nasa.gov/bio).
FAIR↗
Biological Data for Deep Space Mission Support
Increased biomedical risks and challenges associated with deep space missions (cis-Lunar, Mars transit, Mars surface) require new knowledge discovery and development of novel ecosystem and biomedical support capabilities. This paradigm shift supporting distant and long-duration missions requires biological data to be findable, accessible, interoperable, reusable (FAIR), and maximally open-access (i.e., there is a data governance continuum from closed to mediated to embargoed to open). The NASA “Open Science Data Repositories” (OSDR) aims to meet scientific, technical, and operational spaceflight needs, and offers the ability to upload, download, search, share, analyze, and visualize data across physiological, behavioral, ‘omics, and environmental monitoring telemetry datasets. OSDR includes NASA GeneLab, NASA Ames Life Sciences Data Archive (ALSDA), and NASA Biological Institutional Scientific Collection (NBISC). In the past year, ALSDA has undergone a transformation in its data collection, curation, and architecture methods. Standardizing non-genomic (phenotypic) datasets was, and will continue to be, a challenge because of their diverse nature (e.g., molecular, cellular, tissue, whole organism behavior; micro-computed tomography, intraocular pressure, fluorescence microscopy, western blot, ultrasonography; tabular, images, video). This year ALSDA, alongside GeneLab, introduced the Biological Data Management Environment (BDME) with the purpose to accept submission of data from space relevant experiments including spaceflight, radiation, simulated gravity, gravitropism, isolation and confinement, hostile closed environments and/or distance from Earth. In addition to bringing together omics, phenotypic, physiological, bioimaging, and behavioral data into one repository. By integrating with GeneLab a multi-project submission portal aims to reduce the burden on PIs submitting data and enabling the discovery of both omics and phenotypic data. The purpose of ALSDA is to collect, curate, and make all non-human space-relevant biological data maximally findable, accessible, interoperable, and reusable (FAIR). These scope of ALSDA data collected and submitted by PIs include study design metadata, subject metadata, assay metadata (parameters), raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). In 2021, a community of researchers rallied to form the ALSDA Analysis Working Group (AWG) and provided scientific consensus on dataset sample and assay metadata. The community and excitement around the ALSDA/OSDR system has already led to several data reuse studies, demonstrating value using machine learning (ML), knowledge graphs, and meta-analysis approaches.
space biology↗
Biological Data for Deep Space Mission Support
Increased biomedical risks and challenges associated with deep space missions (cis-Lunar, Mars transit, Mars surface) require new knowledge discovery and development of novel ecosystem and biomedical support capabilities. This paradigm shift supporting distant and long-duration missions requires biological data to be findable, accessible, interoperable, reusable (FAIR), and maximally open-access (i.e., there is a data governance continuum from closed to mediated to embargoed to open). The NASA “Open Science Data Repositories” (OSDR) aims to meet scientific, technical, and operational spaceflight needs, and offers the ability to upload, download, search, share, analyze, and visualize data across physiological, behavioral, ‘omics, and environmental monitoring telemetry datasets. OSDR includes NASA GeneLab, NASA Ames Life Sciences Data Archive (ALSDA), and NASA Biological Institutional Scientific Collection (NBISC). In the past year, ALSDA has undergone a transformation in its data collection, curation, and architecture methods. Standardizing non-genomic (phenotypic) datasets was, and will continue to be, a challenge because of their diverse nature (e.g., molecular, cellular, tissue, whole organism, behavior; micro-computed tomography, intraocular pressure, fluorescence microscopy, western blot, ultrasonography; tabular, images, video). This year ALSDA, alongside GeneLab, introduced the Biological Data Management Environment (BDME) with the purpose to accept submission of data from space relevant experiments including spaceflight, radiation, simulated gravity, gravitropism, isolation and confinement, hostile closed environments and/or distance from Earth. In addition to bringing together omics, phenotypic, physiological, bioimaging, and behavioral data into one repository. By integrating with GeneLab a multi-project submission portal aims to reduce the burden on PIs submitting data and enabling the discovery of both omics and phenotypic data. The purpose of ALSDA is to collect, curate, and make all non-human space-relevant biological data maximally findable, accessible, interoperable, and reusable (FAIR). These scope of ALSDA data collected and submitted by PIs include study design metadata, subject metadata, assay metadata (parameters), raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). In 2021, a community of researchers rallied to form the ALSDA Analysis Working Group (AWG) and provided scientific consensus on dataset sample and assay metadata. The community and excitement around the ALSDA/OSDR system has already led to several data reuse studies, demonstrating value using machine learning (ML), knowledge graphs, and meta-analysis approaches.
space biology↗
Open Science for Life in Space: Bioimaging, Data Sharing, and Tools for Knowledge Discovery
Precious space-flown biological experiments have both multi-omic and phenotypic data which NASA strives to make maximally open access for reuse. Currently a number of these space-relevant bioimaging datasets are being reused for AI/ML approaches. NASA Ames Life Science Data Archive and NASA GeneLab are working to make all current and future bioimaging data even more accessible and reusable. Standards for collection and curation are being implemented to enable scientists worldwide access to these data for further discovery and use.
data science↗
Not Just Omics: The Space Biology Open Science Data Repository (OSDR) Enables Access to High Quality Space Life Sciences Phenotypic Data from Microbes to Humans
Explore the source record for details and available documents.
Rachel Gilbert↗
GeneLab Analysis Working Group Kick-Off Meeting
Goals to achieve for GeneLab AWG - GL vision - Review of GeneLab AWG charter Timeline and milestones for 2018 Logistics - Monthly Meeting - Workshop - Internship - ASGSR Introduction of team leads and goals of each group Introduction of all members Q/A Three-tier Client Strategy to Democratize Data Physiological changes, pathway enrichment, differential expression, normalization, processing metadata, reproducibility, Data federation/integration with heterogeneous bioinformatics external databases The GLDS currently serves over 100 omics investigations to the biomedical community via open access. In order to expand the scope of metadata record searches via the GLDS, we designed a metadata warehouse that collects and updates metadata records from external systems housing similar data. To demonstrate the capabilities of federated search and retrieval of these data, we imported metadata records from three open-access data systems into the GLDS metadata warehouse: NCBI's Gene Expression Omnibus (GEO), EBI's PRoteomics IDEntifications (PRIDE) repository, and the Metagenomics Analysis server (MG-RAST). Each of these systems defines metadata for omics data sets differently. One solution to bridge such differences is to employ a common object model (COM) to which each systems' representation of metadata can be mapped. Warehoused metadata records are then transformed at ETL to this single, common representation. Queries generated via the GLDS are then executed against the warehouse, and matching records are shown in the COM representation (Fig. 1). While this approach is relatively straightforward to implement, the volume of the data in the omics domain presents challenges in dealing with latency and currency of records. Furthermore, the lack of a coordinated has been federated data search for and retrieval of these kinds of data across other open-access systems, so that users are able to conduct biological meta-investigations using data from a variety of sources. Such meta-investigations are key to corroborating findings from many kinds of assays and translating them into systems biology knowledge and, eventually, therapeutics.
GeneLab↗
Systemic Microgravity Response: Utilizing GeneLab to Develop Hypotheses for Spaceflight Risks
Biological risks associated with microgravity is a major concern for space travel. Although determination of risk has been a focus for NASA research, data examining systemic (i.e., multi- or pan-tissue) responses to space flight are sparse. The overall goal of our work is to identify potential master regulators responsible for such responses to microgravity conditions. To do this we utilized the NASA GeneLab database which contains a wide array of omics experiments, including data from: 1) different flight conditions (space shuttle (STS) missions vs. International Space Station (ISS); 2) different tissues; and 3) different types of assays that measure epigenetic, transcriptional, and protein expression changes. We have performed meta-analysis identifying potential master regulators involved with systemic responses to microgravity. The analysis used 7 different murine and rat data sets, examining the following tissues: liver, kidney, adrenal gland, thymus, mammary gland, skin, and skeletal muscle (soleus, extensor digitorum longus, tibialis anterior, quadriceps, and gastrocnemius). Using a systems biology approach, we were able to determine that p53 and immune related pathways appear central to pan-tissue microgravity responses. Evidence for a universal response in the form of consistency of change across tissues in regulatory pathways was observed in both STS and ISS experiments with varying durations; while degree of change in expression of these master regulators varied across species and strain, some change in these master regulators was universally observed. Interestingly, certain skeletal muscle (gastrocnemius and soleus) show an overall down-regulation in these genes, while in other types (extensor digitorum longus, tibialis anterior and quadriceps) they are up-regulated, suggesting certain muscle tissues may be compensating for atrophy responses caused by microgravity. Studying these organtissue-specific perturbations in molecular signaling networks, we demonstrate the value of GeneLab in characterizing potential master regulators associated with biological risks for spaceflight.
Microgravity↗
GeneLab: A Systems Biology Platform for Omics Analysis
NASA's GeneLab includes an open-access repository of some 200+ omics datasets generated by biological experiments relevant to spaceflight (including simulated cosmic radiation and microgravity). In order to maximize the intelligibility of these data, particularly for users with limited bioinformatics knowledge, GeneLab is now transforming the data in the repository into actual biological and physiological knowledge of the genetic and proteomic signatures found in these samples. This processed data is being derived by establishing standard data analysis workflows vetted by 114 scientists who are members of the four GeneLab Analysis Working Groups (Animal AWG, Plant AWG, Microbe AWG, Multi-Omics AWG). AWG members from institutes spanning the U.S. and four other countries participate on a voluntary basis. The AWGs meet monthly to discuss data mining, compare results and interpretations, and test forthcoming releases of the GeneLab Data Systems (GLDS). GLDS version 3.0 has been available to the general public since October 1st 2018, and has been providing a professional state-of-the-art bioinformatics platform for everyone in the space biology community to upload their data into a space biology omics data commons, to process their data with vetted standard workflows and to compare to existing analyses. The user interface for the platform is being designed to be accessible to a broad variety of users including those with limited bioinformatics experience, including high school and college students who can use it to learn about omics data analysis and space biology. As such, Genelab will constitute a powerful general public outreach capability of NASA and the Space Biology community at large. Data mining of the GeneLab database by the AWG has already started generating very interesting findings, including reports linking specific spaceflight conditions such as radiation, microgravity or carbon dioxide levels to molecular changes seen across various species. In this presentation, we will report on the current and future objectives for GeneLab, and review recent studies reported by the various AWGs relating molecular changes observed in various animal models and tissue with microgravity, radiation, circadian rhythm, hydration and carbon dioxide conditions.
Omics↗
Open Science for Plants in Space: Data Sharing, Standards, and Informatics for Reuse and Knowledge Discovery
Upcoming deep space missions rely on plants and crops for crew and ecosystem health. Access to space plant data enables scientists to gain a deeper understanding of biological responses to ionizing radiation, altered gravity, low atmospheric pressure, elevated CO2, and altered photoperiods. Open Science is the practice of making research available to all, while respecting diverse cultures, fostering collaborations with equity. 2023 is the ‘Year of Open Science’, and NASA has a 5-year Transform to Open Science (TOPS) mission designed to rapidly transform the agency toward an inclusive culture of open science. NASA’s Open Science Data Repository (OSDR) developed by NASA’s Biological and Physical Sciences Division provides access to data from space-relevant biological experiments. OSDR combines two databases, GeneLab and Ames Life Sciences Data Archive (ALSDA) to maximize access to standardized ‘omics (e.g., transcriptomics, proteomics) and phenotypic data (e.g., microscopy, biomass), respectively. OSDR started in 2014 with the creation of the first space-relevant FAIR (Findable, Accessible, Interoperable, Reusable) biological ‘omics repository (GeneLab), providing detailed metadata on investigation, sample, and assay levels. Today, GeneLab hosts 62 plant datasets which have led to 5 published peer-reviewed meta-analysis publications. Most of these publications were collaboration efforts under the OSDR Analysis Working Groups (AWGs). AWGs provide great opportunities for investigators to collaborate and set new standards for space-relevant data and metadata. The AWGs are welcoming any ASPB members interested in providing plant expertise for space biology. The addition of ALSDA to OSDR is also expanding analysis capability beyond ‘omics. Now is the time to get involved as a Subject Matter Expert as we establish the framework for modern plant data archiving through the AWGs. Investigators are invited to submit their space-relevant plant datasets to OSDR and visit the site to learn about the tools OSDR has to offer (osdr.nasa.gov/bio).
FAIR↗
Unlocking the Secrets of Space Biology: From the Twin Study to Groundbreaking Open Science Discoveries
In this interdisciplinary lecture, we will delve into the fascinating world of Space Biology and the realm of Open Science at NASA. Join us as we explore the profound insights gained from the groundbreaking twin study, which was published several years ago and continues to shape our understanding of spaceflight's impact on human health. We will highlight the study's key findings and contextualize them alongside more recent research endeavors, including the remarkable Inspiration 4 mission and several comprehensive meta-analysis publications enabled by the NASA GeneLab Omics database and the Ames Life Science Data Archive for physiological and phenotypic data.
Omics↗
A Multi-Omics Approach Demonstrates that Spaceflight Leads to Lipid Accumulation in Mouse Livers
Spaceflight has several detrimental effects on the physiology of astronauts, many of which are recapitulated in rodent models. We analyzed liver transcriptomic and proteomic data from three mouse spaceflight experiments flown aboard the International Space Station (Rodent Research-1 NASA (RR-1 NASA), Rodent Research-1 CASIS (RR-1 CASIS), Rodent Research-3 (RR-3)), and one mouse experiment flown on the Space Shuttle (Commercial Biomedical Testing Module-3 (CBTM-3) aboard STS-135). Despite the differences in genetic background and time of exposure to microgravity it was shown through Oil Red staining and histology that increased lipid accumulation was occurring in the liver of all mice flown in space compared to the ground controls. This led to further pursue the existing GeneLab datasets related to liver omics data from these mice. We were able to discover key conserved pathways across all the mice independent of the flight conditions that were related to increased lipid metabolism, fatty acid metabolism, both lipid and fatty acid processing, lipid catabolic processing, and lipid localization. In addition, key upstream regulators were predicted to be commonly regulated across all conditions which include ESR1, GCG, and NR1I2 being inhibited and INS being activated. Interestingly, estrogen receptor alpha (ESR1) expression has been known to be heavily involved with lipoprotein metabolism. In addition, insulin (INS) is the primary driver for fat metabolism and increased INS has been associated with increased fatty acids in the liver. Through additional proteomic analysis we were able to identify the majority of the key proteins related to lipids for both the RR-1 and RR-3 rodents were being up-regulated in the livers when comparing flight to ground controls. This additional confirmation of the lipid associated activity also showed that the lipid related proteins are heavily involved with lipid metabolism, cholesterol binding, and cholesterol metabolism. Lastly, the analysis also revealed that the circadian clock related pathways in the liver are commonly being increased across all space flight conditions which has also been reported in the literature to potentially cause increased liver damage. The combination of the very strong lipid uptake in the liver and the transcriptomic/proteomic signatures (including the circadian clock pathways) following spaceflight are consistent with early onset of liver disease. Taken together, these data indicate that, activation of lipotoxic pathways could persist during longer duration spaceflight which might result in the development of liver disease
Lipids↗
Open Science for Plants in Space: Improvements in NASA's Open Science Data Repository
Upcoming deep space missions will rely on plants for crew and ecosystem health. Open access space biology data enables scientists to examine the biological responses of plants to ionizing radiation, altered gravity, elevated CO2, and many other abiotic stressors. NASA has declared 2023 as the ‘Year of Open Science’ and created a 5-year Transform to Open Science (TOPS) initiative designed to rapidly transform the agency toward an inclusive culture of open science. NASA’s Open Science Data Repository (OSDR) combines two databases, GeneLab and Ames Life Sciences Data Archive (ALSDA) to maximize access to standardized ‘omics (e.g., transcriptomics, proteomics) and phenotypic data (e.g., microscopy, biomass), respectively. Current OSDR standards include the ISA (Investigation-Study-Assay) experiment model, assay metadata configurations, and standardized terminology and ontologies. In 2024 OSDR will include a new suite of features for improved FAIR compliance including downloadable plant metadata templates, data submission tools and overall improved AI-readiness of plant datasets. AI/ML methods can be helpful tools to overcome the inherent challenges of space biology research (small sample size, sparse and heterogeneous data etc.). However these methods are built on an assumption of normalized and well-curated data. OSDR’s new curation tools will improve users ability to leverage ML and AI methods to model space biology data and better understand the complex effects of spaceflight on living systems across hierarchical biological levels. We look forward to sharing our advances with the spaceflight community.
FAIR↗
Open Science for Life in Space: Data Sharing and Tools for Knowledge Discovery
Molecular-omics, physiological-phenotypic-behavioral, and environmental-radiation telemetry data from spaceflight biological and health studies are increasingly being made findable, accessible, interoperable, and reusable for the scientific public. These data, as well as space science-relevant biospecimens, are available through NASA’s Open Science Data Repository (OSDR), which is the new umbrella grouping of NASA GeneLab, the Ames Life Sciences Data Archive (ALSDA), and the NASA Biological Institutional Scientific Collection (NBISC). The quality of data is underpinned by datasets having rich metadata (determined through Analysis Working Group members), processing pipelines to enable data reuse standards, and ontologies specifying terminology semantics (e.g., the Radiation Biology Ontology).
space biology↗
NASA GeneLab Concept of Operations
NASA's GeneLab aims to greatly increase the number of scientists that are using data from space biology investigations on board ISS, emphasizing a systems biology approach to the science. When completed, GeneLab will provide the integrated software and hardware infrastructure, analytical tools and reference datasets for an assortment of model organisms. GeneLab will also provide an environment for scientists to collaborate thereby increasing the possibility for data to be reused for future experimentation. To maximize the value of data from life science experiments performed in space and to make the most advantageous use of the remaining ISS research window, GeneLab will apply an open access approach to conducting spaceflight experiments by generating, and sharing the datasets derived from these biological studies in space.Onboard the ISS, a wide variety of model organisms will be studied and returned to Earth for analysis. Laboratories on the ground will analyze these samples and provide genomic, transcriptomic, metabolomic and proteomic data. Upon receipt, NASA will conduct data quality control tasks and format raw data returned from the omics centers into standardized, annotated information sets that can be readily searched and linked to spaceflight metadata. Once prepared, the biological datasets, as well as any analysis completed, will be made public through the GeneLab Space Bioinformatics System webb as edportal. These efforts will support a collaborative research environment for spaceflight studies that will closely resemble environments created by the Department of Energy (DOE), National Center for Biotechnology Information (NCBI), and other institutions in additional areas of study, such as cancer and environmental biology. The results will allow for comparative analyses that will help scientists around the world take a major leap forward in understanding the effect of microgravity, radiation, and other aspects of the space environment on model organisms. These efforts will speed the process of scientific sharing, iteration, and discovery.
Space Life Science↗