Design and Implementation of Web APIs for Supporting Data Product Visualization and Dissemination In Science Gateways

In the pursuit to develop an online data portal for visualizing and downloading climatological data from around Hawaiʻi, a need to compile and generate large amounts of data was identified. While some tools are available for handling and distributing this data, they were not sufficient for several core features required of the project, including generating and emailing users zipped packages of requested data. To fulfill the requirements of this project and provide programmatic access to the data, an API was developed. This paper will introduce the endpoints and functions made available through this API and describe its implementation and potential for adoption by other projects

A Decentralized Authorization and Security Framework for Distributed Research Workflows

Research challenges such as climate change and the search for habitable planets increasingly use academic and commercial computing resources distributed across different institutions and physical sites. Furthermore, such analyses often require a level of automation that precludes direct human interaction, and securing these workflows involves adherence to security policies across institutions. In this paper, we present a decentralized authorization and security framework that enables researchers to utilize resources across different sites while allowing service providers to maintain autonomy over their secrets and authorization policies. We describe this framework as part of the Tapis platform, a web-based, hosted API used by researchers from multiple institutions, and we measure the performance of various authorization and security queries, including cross-site queries. We conclude with two use case studies -- a project at the University of Hawaii to study climate change and the NASA NEID telescope project that searches the galaxy for exoplanets.Comment: 10 pages. Short version of this paper to be published on COMPSAC 2023 proceeding

A Bioinformatics Approach to the Structure, Function, and Evolution of the Nucleoprotein of the Order Mononegavirales

The goal of this Bioinformatic study is to investigate sequence conservation in relation to evolutionary function/structure of the nucleoprotein of the order Mononegavirales. In the combined analysis of 63 representative nucleoprotein (N) sequences from four viral families (Bornaviridae, Filoviridae, Rhabdoviridae, and Paramyxoviridae) we predict the regions of protein disorder, intra-residue contact and co-evolving residues. Correlations between location and conservation of predicted regions illustrate a strong division between families while high- lighting conservation within individual families. These results suggest the conserved regions among the nucleoproteins, specifically within Rhabdoviridae and Paramyxoviradae, but also generally among all members of the order, reflect an evolutionary advantage in maintaining these sites for the viral nucleoprotein as part of the transcription/replication machinery. Results indicate conservation for disorder in the C-terminus region of the representative proteins that is important for interacting with the phosphoprotein and the large subunit polymerase during transcription and replication. Additionally, the C-terminus region of the protein preceding the disordered region, is predicted to be important for interacting with the encapsidated genome. Portions of the N-terminus are responsible for N∶N stability and interactions identified by the presence or lack of co-evolving intra-protein contact predictions. The validation of these prediction results by current structural information illustrates the benefits of the Disorder, Intra-residue contact and Compensatory mutation Correlator (DisICC) pipeline as a method for quickly characterizing proteins and providing the most likely residues and regions necessary to target for disruption in viruses that have little structural information available

A Vision for Science Gateways: Bridging the Gap and Broadening the Outreach

The future for science gateways warrants exploration as we consider the possibilities that extend well beyond science and high performance computing into new interfaces, applications and user communities. In this paper, we look retrospectively at the successes of representative gateways thus far. This serves to highlight existing gaps gateways need to overcome in areas such as accessibility, usability and interoperability, and in the need for broader outreach by drawing insights from technology adoption research. We explore two particularly promising opportunities for gateways - computational social sciences and virtual reality – and make the case for the gateway community to be more intentional in engaging with users to encourage adoption and implementation, especially in the area of educational usage. We conclude with a call for focused attention on legal hurdles in order to realize the full future potential of science gateways. This paper serves as a roadmap for a vision of science gateways in the next ten years

Sustainability in the Tapis Framework

As more research depends fundamentally on software, sustainability becomes increasingly critical. Nevertheless, despite valiant efforts from a growing number of researchers and practitioners, a basic understanding of best-practices for sustainable software remains elusive. In this paper, we review the specific practices and strategies that have helped to sustain Tapis, a cyberinfastructure project that has been in use for over a decade. The Tapis framework is an open-source, software-as-a-service Application Programming Interface (API) for collaborative, automated, reproducible computational research which began as the Foundation API for the iPlant Collaborative Project in 2008, and today is used by tens of thousands of individuals across more than a dozen active projects. This paper describes our multi-faceted approach to sustaining an increasingly complex ecosystem of software, documentation and other digital assets, including both technical and organizational strategies for minimizing the cost of sustainment while maximizing available resources for sustainment activities

Molecular hydrogen and catalytic combustion in the production of hyperpolarized 83Kr and 129Xe MRI contrast agents

Hyperpolarized (hp) 83Kr is a promising MRI contrast agent for the diagnosis of pulmonary diseases affecting the surface of the respiratory zone. However, the distinct physical properties of 83Kr that enable unique MRI contrast also complicate the production of hp 83Kr. This work presents a radically new approach in the generation of hp 83Kr that can likewise be utilized for the production of hp 129Xe. Molecular nitrogen, typically used as buffer gas in spin exchange optical pumping (SEOP), was replaced by molecular hydrogen without penalty for the achievable hyperpolarization. In this particular study, the highest obtained nuclear spin polarizations were P = 29 % for 83Kr and P = 63 % for 129Xe. The results were reproduced over many SEOP cycles despite the laser induced on-resonance formation of rubidium hydride (RbH). Following SEOP, the H2 was reactively removed via catalytic combustion without measurable losses in hyperpolarized spin state of either 83Kr or 129Xe. Highly spin polarized 83Kr can now be purified for the first time to provide high signal intensity for the advancement of in vivo hp 83Kr MRI. More generally, a chemical reaction appears as a viable alternative to the cryogenic separation process, the primary purification method of hp 129Xe for the past 2 . decades. The inherent simplicity of the combustion process will facilitate hp 129Xe production and should allow for on-demand continuous flow of purified and highly spin polarized 129Xe

A Vision for Science Gateways: Bridging the Gap and Broadening the Outreach

The future for science gateways warrants exploration as we consider the possibilities that extend well beyond science and high performance computing into new interfaces, applications and user communities. In this paper, we look retrospectively at the successes of representative gateways thus far. This serves to highlight existing gaps gateways need to overcome in areas such as accessibility, usability and interoperability, and in the need for broader outreach by drawing insights from technology adoption research. We explore two particularly promising opportunities for gateways - computational social sciences and virtual reality – and make the case for the gateway community to be more intentional in engaging with users to encourage adoption and implementation, especially in the area of educational usage. We conclude with a call for focused attention on legal hurdles in order to realize the full future potential of science gateways. This paper serves as a roadmap for a vision of science gateways in the next ten years

Science Gateways and AI/ML: How Can Gateway Concepts and Solutions Meet the Needs in Data Science?

Science gateways are a crucial component of critical infrastructure as they provide the means for users to focus on their topics and methods instead of the technical details of the infrastructure. They are defined as end-to-end solutions for accessing data, software, computing services, sensors, and equipment specific to the needs of a science or engineering discipline and their goal is to hide the complexity of the underlying infrastructure. Science gateways are often called Virtual Research Environments in Europe and Virtual Labs in Australasia; we consider these two terms to be synonymous with science gateways. Over the past decade, artificial intelligence (AI) and machine learning (ML) have found applications in many different fields in private industry, and private industry has reaped the benefits. Likewise, in the academic realm, large-scale data science applications have also learned to apply public high-performance computing resources to make use of this technology. However, academic and research science gateways have yet to fully adopt the tools of AI. There is an opportunity in the gateways space, both to increase the visibility and accessibility to AI/ML applications and to enable researchers and developers to advance the field of science gateway cyberinfrastructure itself. Harnessing AI/ML is recognized as a high priority by the science gateway community. It is, therefore, critical for the next generation of science gateways to adapt to support the AI/ML that is already transforming many scientific fields. The goal is to increase collaborations between the two fields and to ensure that gateway services are used and are valuable to the AI/ML community. This chapter presents state-of-the-art examples and areas of opportunity for the science gateways community to pursue in relation to AI/ML and some vision of where these new capabilities might impact science gateways and support scientific research

Genetic variation in insulin-like growth factor signaling genes and breast cancer risk among BRCA1 and BRCA2 carriers

Abstract Introduction Women who carry mutations in BRCA1 and BRCA2 have a substantially increased risk of developing breast cancer as compared with the general population. However, risk estimates range from 20 to 80%, suggesting the presence of genetic and/or environmental risk modifiers. Based on extensive in vivo and in vitro studies, one important pathway for breast cancer pathogenesis may be the insulin-like growth factor (IGF) signaling pathway, which regulates both cellular proliferation and apoptosis. BRCA1 has been shown to directly interact with IGF signaling such that variants in this pathway may modify risk of cancer in women carrying BRCA mutations. In this study, we investigate the association of variants in genes involved in IGF signaling and risk of breast cancer in women who carry deleterious BRCA1 and BRCA2 mutations. Methods A cohort of 1,665 adult, female mutation carriers, including 1,122 BRCA1 carriers (433 cases) and 543 BRCA2 carriers (238 cases) were genotyped for SNPs in IGF1, IGF1 receptor (IGF1R), IGF1 binding protein (IGFBP1, IGFBP2, IGFBP5), and IGF receptor substrate 1 (IRS1). Cox proportional hazards regression was used to model time from birth to diagnosis of breast cancer for BRCA1 and BRCA2 carriers separately. For linkage disequilibrium (LD) blocks with multiple SNPs, an additive genetic model was assumed; and for single SNP analyses, no additivity assumptions were made. Results Among BRCA1 carriers, significant associations were found between risk of breast cancer and LD blocks in IGF1R (global P = 0.011 for LD block 2 and global P = 0.012 for LD block 11). Among BRCA2 carriers, an LD block in IGFBP2 (global P = 0.0145) was found to be associated with the time to breast cancer diagnosis. No significant LD block associations were found for the other investigated genes among BRCA1 and BRCA2 carriers. Conclusions This is the first study to investigate the role of genetic variation in IGF signaling and breast cancer risk in women carrying deleterious mutations in BRCA1 and BRCA2. We identified significant associations in variants in IGF1R and IRS1 in BRCA1 carriers and in IGFBP2 in BRCA2 carriers. Although there is known to be interaction of BRCA1 and IGF signaling, further replication and identification of causal mechanisms are needed to better understand these associations