Making Common Fund data more Findable: Catalyzing a Data Ecosystem

The Common Fund Data Ecosystem has created a flexible system of data federation that enables users to discover datasets from across the Common Fund without requiring the data owners to move, reformat, or rehost those data. The CFDEs federation system is centered on a metadata catalog that ingests metadata from individual Common Fund Program Data Coordination Centers into a uniform metadata model that can then be indexed and searched from a centralized portal. This uniform Crosscut Metadata Model (C2M2), supports the wide variety of data set types and metadata terms used by the individual and is designed to enable easy expansion to accommodate new datatypes.

Three Wishes for Sickle Cell Disease: Results from a multi-stakeholder vision-casting project in Tennessee

Although sickle cell disease (SCD) is one of the most common genetic disorders in the US, disparities in research and funding persist. To better understand stakeholder priorities, we conducted a virtual vision-casting session utilizing a graphic recorder and content analysis. Stakeholders responded to the question: “If you had three magic wishes for SCD in TN, what would they be?”. Wishes for SCD centered around information and data, care and policy, and community. Better patient-centered information about treatments and modernization of data were high priorities. Stakeholders identified a need for heath equity, starting with lifetime continuity of care and access to curative treatment for all persons with SCD. Key points concerning the community included better patient inclusion in research, increased awareness, and greater public knowledge. SCD patients expressed a desire for honesty, transparency, compassion, and trust. Key areas to address in SCD include better data coordination, more influence on health policy, broader access to care and more community awareness, with the ultimate goal of improving the lives of persons with SCD. Using data to improve care and address health disparities will require researchers listening to stakeholders and understanding multiple perspectives to form unified goals.

Integrative annotation of genomic features reveal functional elements and epigenetic landscapes in the developing zebrafish

Despite being a popular model for embryonic development and diseases, zebrafish have lacked systematic functional annotation programmes seen in other animal models. To address this, we formed the international DANIO-CODE consortium and created the first central repository to store and process zebrafish functional genomic data. Our Data Coordination Center (https://danio-code.zfin.org) combines a total of 1802 sets of unpublished and reanalysed published genomics data, with which we improve existing annotations and show its usefulness in experimental design. We define over 140,000 cis-regulatory elements and decribe novel classes with distinct features depending on time and space of activity. We delineate the difference between regulatory elements active during zygotic genome activation and those active during organogenesis, identifying new aspects of their relatedness. Finally, we match regulatory elements between zebrafish and mouse and predict functional relationships between them beyond sequence similarity, extending the utility of zebrafish developmental genomics to mammals.

Review Review of National Economic Recovery Program in Indonesia

The escalation of Covid-19 and the sharp economic slowdown and tremendous disruption in various aspects of life, especially health, social, economic and financial impacts must be mitigated on the public welfare through extraordinary policies. The Covid-19 response and economic recovery program is an extremely important program designed in an atmosphere of emergency / urgency. Speed ​​is very important, but on the other hand, accountability, transparency and good governance principles should not be ignored. In the midst of an emergency situation in handling Covid-19, especially the PEN program, many government programs in their implementation require very fast, urgent and massive handling, which of course must be followed by strengthening good governance, through the application of the principles of prudence, accountability and transparency. The results of the review show that in the implementation of the PEN program there are problems with regulations, budget, data, coordination and technical implementation, monitoring and evaluation, and information technology. These constraints are related to one another. Based on references to evaluations of governments, institutions, and best practices in countries that have successfully implemented the program, the authors present solutions related to these problems.

Prioritised Zoonotic Diseases of Nepal: A Review

World Organization for Animal Health (OIE) has estimated that 60% of infectious diseases and 75% of emerging and re-emerging diseases of humans have an animal origin. In Nepal there six zoonoses; Taeniasis/cysticercosis /Neurocysticercosis, Leptospirosis, Hydatidosis, Brucellosis; Toxoplasmosis and Avian Influenza are identified as priorities zoonotic diseases as they are found to have epidemic potential. Although they are prioritised, there is high prevalence of these diseases in both humans and animals with insufficient research and data. Coordination of multiple stakeholders of public and animal health and One Health collaboration are crucial to control and elimination zoonotic diseases in Nepal. Int. J. Appl. Sci. Biotechnol. Vol 9(1): 1-15

Research on Innovative Strategies of Accurate Development Model of Regional Agricultural Economy under Big Data Coordination

This article will analyze the correlation between big data and regional agricultural economic development on the basis of fully understanding the connotation and characteristics of big data technology. Then, we should use its concept and related technologies and operating models to realize the precise operation guidance of multiple links such as agricultural product planting, selection, planting, farm management, harvesting and storage, and marketing. Through the integration of big data and local advantageous agricultural resources, it is possible to build a fusion and innovation mechanism based on big data, and build an open, intelligent, and intensive precision agriculture development format. This can accelerate the realization of agricultural informatization and modernization, and promote the innovative development of regional agricultural economy.

HMPDACC: a Human Microbiome Project Multi-omic data resource

The Human Microbiome Project (HMP) explored microbial communities of the human body in both healthy and disease states. Two phases of the HMP (HMP and iHMP) together generated >48TB of data (public and controlled access) from multiple, varied omics studies of both the microbiome and associated hosts. The Human Microbiome Project Data Coordination Center (HMPDACC) was established to provide a portal to access data and resources produced by the HMP. The HMPDACC provides a unified data repository, multi-faceted search functionality, analysis pipelines and standardized protocols to facilitate community use of HMP data. Recent efforts have been put toward making HMP data more findable, accessible, interoperable and reusable. HMPDACC resources are freely available at www.hmpdacc.org.

The European Nucleotide Archive in 2020

The European Nucleotide Archive (ENA; https://www.ebi.ac.uk/ena), provided by the European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI), has for almost forty years continued in its mission to freely archive and present the world's public sequencing data for the benefit of the entire scientific community and for the acceleration of the global research effort. Here we highlight the major developments to ENA services and content in 2020, focussing in particular on the recently released updated ENA browser, modernisation of our release process and our data coordination collaborations with specific research communities.

Generalizable Layered Blockchain Architecture for Health Care Applications: Development, Case Studies, and Evaluation

Background Data coordination across multiple health care facilities has become increasingly important for many emerging health care applications. Distrust has been recognized as a key barrier to the success of such applications. Leveraging blockchain technology could provide potential solutions tobuild trust between data providers and receivers by taking advantage of blockchain properties such as security, immutability, anonymity, decentralization, and smart contracts. Many health technologies have empirically proven that blockchain designs fit well with the needs of health care applications with certain degrees of success. However, there is a lack of robust architecture to provide a practical framework for developers to implement applications and test the performance of stability, efficiency, and scalability using standard blockchain designs. A generalized blockchain model is needed for the health care community to adopt blockchain technology and develop applications in a timely fashion. Objective This study aimed at building a generalized blockchain architecture that provides data coordination functions, including data requests, permission granting, data exchange, and usage tracking, for a wide spectrum of health care application developments. Methods An augmented, 3-layered blockchain architecture was built on a private blockchain network. The 3 layers, from bottom to top, are as follows: (1) incorporation of fundamental blockchain settings and smart contract design for data collection; (2) interactions between the blockchain and health care application development environment using Node.js and web3.js; and (3) a flexible development platform that supports web technologies such as HTML, https, and various programing languages. Two example applications, health information exchange (HIE) and clinical trial recruitment, were developed in our design to demonstrate the feasibility of the layered architecture. Case studies were conducted to test the performance in terms of stability, efficiency, and scalability of the blockchain system. Results A total of 331,142 simulated HIE requests from accounts of 40,000 patients were successfully validated through this layered blockchain architecture with an average exchange time of 11.271 (SD 2.208) seconds. We also simulated a clinical trial recruitment scenario with the same set of patients and various recruitment criteria to match potential subjects using the same architecture. Potential subjects successfully received the clinical trial recruitment information and granted permission to the trial sponsors to access their health records with an average time of 3.07 seconds. Conclusions This study proposes a generalized layered blockchain architecture that offers health technology community blockchain features for application development without requiring developers to have extensive experience with blockchain technology. The case studies tested the performance of our design and empirically proved the feasibility of the architecture in 2 relevant health application domains.

Generalizable Layered Blockchain Architecture for Health Care Applications: Development, Case Studies, and Evaluation (Preprint)

BACKGROUND Data coordination across multiple health care facilities has become increasingly important for many emerging health care applications. Distrust has been recognized as a key barrier to the success of such applications. Leveraging blockchain technology could provide potential solutions tobuild trust between data providers and receivers by taking advantage of blockchain properties such as security, immutability, anonymity, decentralization, and smart contracts. Many health technologies have empirically proven that blockchain designs fit well with the needs of health care applications with certain degrees of success. However, there is a lack of robust architecture to provide a practical framework for developers to implement applications and test the performance of stability, efficiency, and scalability using standard blockchain designs. A generalized blockchain model is needed for the health care community to adopt blockchain technology and develop applications in a timely fashion. OBJECTIVE This study aimed at building a generalized blockchain architecture that provides data coordination functions, including data requests, permission granting, data exchange, and usage tracking, for a wide spectrum of health care application developments. METHODS An augmented, 3-layered blockchain architecture was built on a private blockchain network. The 3 layers, from bottom to top, are as follows: (1) incorporation of fundamental blockchain settings and smart contract design for data collection; (2) interactions between the blockchain and health care application development environment using Node.js and web3.js; and (3) a flexible development platform that supports web technologies such as HTML, https, and various programing languages. Two example applications, health information exchange (HIE) and clinical trial recruitment, were developed in our design to demonstrate the feasibility of the layered architecture. Case studies were conducted to test the performance in terms of stability, efficiency, and scalability of the blockchain system. RESULTS A total of 331,142 simulated HIE requests from accounts of 40,000 patients were successfully validated through this layered blockchain architecture with an average exchange time of 11.271 (SD 2.208) seconds. We also simulated a clinical trial recruitment scenario with the same set of patients and various recruitment criteria to match potential subjects using the same architecture. Potential subjects successfully received the clinical trial recruitment information and granted permission to the trial sponsors to access their health records with an average time of 3.07 seconds. CONCLUSIONS This study proposes a generalized layered blockchain architecture that offers health technology community blockchain features for application development without requiring developers to have extensive experience with blockchain technology. The case studies tested the performance of our design and empirically proved the feasibility of the architecture in 2 relevant health application domains.