scholarly journals The ELIXIR Core Data Resources: fundamental infrastructure for the life sciences

2019 ◽  
Author(s):  
Rachel Drysdale ◽  
Charles E. Cook ◽  
Robert Petryszak ◽  
Vivienne Baillie-Gerritsen ◽  
Mary Barlow ◽  
...  
Keyword(s):  
Life Science ◽  
Life Sciences ◽  
Health Sector ◽  
Biological Data ◽  
Supplementary Information ◽  
Science Data ◽  
Data Infrastructure ◽  
Data Resource ◽  
Core Data ◽  
The Core

AbstractMotivationLife science research in academia, industry, agriculture, and the health sector depends critically on free and open data resources. ELIXIR (www.elixir-europe.org), the European Research Infrastructure for life sciences data, has identified a set of Core Data Resources within Europe that are of most fundamental importance for the long-term preservation of biological data. We explore characteristics of their usage, impact and assured funding horizon to assess their value and importance as an infrastructure, to understand sustainability of the infrastructure, and to demonstrate a model for assessing Core Data Resources worldwide.ResultsThe nineteen resources currently designated ELIXIR Core Data Resources form a data infrastructure in Europe which is a subset of the worldwide open life science data infrastructure. We show that, from 2014 to 2018, data managed by the Core Data Resources more than tripled while staff numbers increased by less than a tenth. Additionally, support for the Core Data Resources is precarious: together they have assured funding for less than a third of current staff after four years.Our findings demonstrate the importance of the ELIXIR Core Data Resources as repositories for research data and knowledge, while also demonstrating the uncertain nature of the funding environment for this infrastructure. ELIXIR is working towards longer-term support for the Core Data Resources and, through the Global Biodata Coalition, aims to ensure support for the worldwide life science data resource infrastructure of which the ELIXIR Core Data Resources are a [email protected] informationSupplementary data are available at Bioinformatics online.

scholarly journals Identifying ELIXIR Core Data Resources

F1000Research ◽  
2017 ◽  
Vol 5 ◽  
pp. 2422 ◽  
Author(s):  
Christine Durinx ◽  
Jo McEntyre ◽  
Ron Appel ◽  
Rolf Apweiler ◽  
Mary Barlow ◽  
...  
Keyword(s):  
Life Science ◽  
Life Sciences ◽  
Life Cycles ◽  
Biological Data ◽  
Biological Information ◽  
Biological Research ◽  
Scientific Quality ◽  
Data Resource ◽  
Core Data

The core mission of ELIXIR is to build a stable and sustainable infrastructure for biological information across Europe. At the heart of this are the data resources, tools and services that ELIXIR offers to the life-sciences community, providing stable and sustainable access to biological data. ELIXIR aims to ensure that these resources are available long-term and that the life-cycles of these resources are managed such that they support the scientific needs of the life-sciences, including biological research. ELIXIR Core Data Resources are defined as a set of European data resources that are of fundamental importance to the wider life-science community and the long-term preservation of biological data. They are complete collections of generic value to life-science, are considered an authority in their field with respect to one or more characteristics, and show high levels of scientific quality and service. Thus, ELIXIR Core Data Resources are of wide applicability and usage. This paper describes the structures, governance and processes that support the identification and evaluation of ELIXIR Core Data Resources. It identifies key indicators which reflect the essence of the definition of an ELIXIR Core Data Resource and support the promotion of excellence in resource development and operation. It describes the specific indicators in more detail and explains their application within ELIXIR’s sustainability strategy and science policy actions, and in capacity building, life-cycle management and technical actions. The identification process is currently being implemented and tested for the first time. The findings and outcome will be evaluated by the ELIXIR Scientific Advisory Board in March 2017. Establishing the portfolio of ELIXIR Core Data Resources and ELIXIR Services is a key priority for ELIXIR and publicly marks the transition towards a cohesive infrastructure.

scholarly journals Identifying ELIXIR Core Data Resources

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 2422 ◽  
Author(s):  
Christine Durinx ◽  
Jo McEntyre ◽  
Ron Appel ◽  
Rolf Apweiler ◽  
Mary Barlow ◽  
...  
Keyword(s):  
Life Science ◽  
Life Sciences ◽  
Life Cycles ◽  
Biological Data ◽  
Biological Information ◽  
Biological Research ◽  
Scientific Quality ◽  
Data Resource ◽  
Core Data

The core mission of ELIXIR is to build a stable and sustainable infrastructure for biological information across Europe. At the heart of this are the data resources, tools and services that ELIXIR offers to the life-sciences community, providing stable and sustainable access to biological data. ELIXIR aims to ensure that these resources are available long-term and that the life-cycles of these resources are managed such that they support the scientific needs of the life-sciences, including biological research. ELIXIR Core Data Resources are defined as a set of European data resources that are of fundamental importance to the wider life-science community and the long-term preservation of biological data. They are complete collections of generic value to life-science, are considered an authority in their field with respect to one or more characteristics, and show high levels of scientific quality and service. Thus, ELIXIR Core Data Resources are of wide applicability and usage. This paper describes the structures, governance and processes that support the identification and evaluation of ELIXIR Core Data Resources. It identifies key indicators which reflect the essence of the definition of an ELIXIR Core Data Resource and support the promotion of excellence in resource development and operation. It describes the specific indicators in more detail and explains their application within ELIXIR’s sustainability strategy and science policy actions, and in capacity building, life-cycle management and technical actions. Establishing the portfolio of ELIXIR Core Data Resources and ELIXIR Services is a key priority for ELIXIR and publicly marks the transition towards a cohesive infrastructure.

scholarly journals UniBioDicts: Unified access to Biological Dictionaries

2020 ◽  
Author(s):  
John Zobolas ◽  
Vasundra Touré ◽  
Martin Kuiper ◽  
Steven Vercruysse
Keyword(s):  
User Interface ◽  
Life Science ◽  
Biological Data ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Query Interface ◽  
Controlled Vocabularies ◽  
Search String ◽  
Software Packages ◽  
The Right

Abstract Summary We present a set of software packages that provide uniform access to diverse biological vocabulary resources that are instrumental for current biocuration efforts and tools. The Unified Biological Dictionaries (UniBioDicts or UBDs) provide a single query-interface for accessing the online API services of leading biological data providers. Given a search string, UBDs return a list of matching term, identifier and metadata units from databases (e.g. UniProt), controlled vocabularies (e.g. PSI-MI) and ontologies (e.g. GO, via BioPortal). This functionality can be connected to input fields (user-interface components) that offer autocomplete lookup for these dictionaries. UBDs create a unified gateway for accessing life science concepts, helping curators find annotation terms across resources (based on descriptive metadata and unambiguous identifiers), and helping data users search and retrieve the right query terms. Availability and implementation The UBDs are available through npm and the code is available in the GitHub organisation UniBioDicts (https://github.com/UniBioDicts) under the Affero GPL license. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Reconstruction of biological networks based on life science data integration

2010 ◽  
Vol 7 (2) ◽  
Author(s):  
Benjamin Kormeier ◽  
Klaus Hippe ◽  
Patrizio Arrigo ◽  
Thoralf Töpel ◽  
Sebastian Janowski ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Data Integration ◽  
Biological Networks ◽  
Life Science ◽  
Biological Network ◽  
Network Models ◽  
Biological Data ◽  
Science Data ◽  
Biological Data Integration

SummaryFor the implementation of the virtual cell, the fundamental question is how to model and simulate complex biological networks. Therefore, based on relevant molecular database and information systems, biological data integration is an essential step in constructing biological networks. In this paper, we will motivate the applications BioDWH - an integration toolkit for building life science data warehouses, CardioVINEdb - a information system for biological data in cardiovascular-disease and VANESA- a network editor for modeling and simulation of biological networks. Based on this integration process, the system supports the generation of biological network models. A case study of a cardiovascular-disease related gene-regulated biological network is also presented.

scholarly journals Identifiers.org: Compact Identifier services in the cloud

2020 ◽  
Author(s):  
Manuel Bernal-Llinares ◽  
Javier Ferrer-Gómez ◽  
Nick Juty ◽  
Carole Goble ◽  
Sarala M Wimalaratne ◽  
...  
Keyword(s):  
Life Science ◽  
Life Sciences ◽  
High Availability ◽  
Third Party ◽  
Low Latency ◽  
Cloud Environment ◽  
Science Data ◽  
High Quality ◽  
Front End ◽  
Readable Text

Abstract Motivation Since its launch in 2010, Identifiers.org has become an important tool for the annotation and cross-referencing of Life Science data. In 2016, we established the Compact Identifier (CID) scheme (prefix: accession) to generate globally unique identifiers for data resources using their locally assigned accession identifiers. Since then, we have developed and improved services to support the growing need to create, reference and resolve CIDs, in systems ranging from human readable text to cloud-based e-infrastructures, by providing high availability and low-latency cloud-based services, backed by a high-quality, manually curated resource. Results We describe a set of services that can be used to construct and resolve CIDs in Life Sciences and beyond. We have developed a new front end for accessing the Identifiers.org registry data and APIs to simplify integration of Identifiers.org CID services with third-party applications. We have also deployed the new Identifiers.org infrastructure in a commercial cloud environment, bringing our services closer to the data. Availabilityand implementation https://identifiers.org.

scholarly journals ISA API: An open platform for interoperable life science experimental metadata

2020 ◽  
Author(s):  
David Johnson ◽  
Keeva Cochrane ◽  
Robert P. Davey ◽  
Anthony Etuk ◽  
Alejandra Gonzalez-Beltran ◽  
...  
Keyword(s):  
Data Model ◽  
Life Science ◽  
Life Sciences ◽  
Common Data Model ◽  
Science Data ◽  
Software Suite ◽  
Early Adopters ◽  
Open Platform ◽  
Data Formats ◽  
Common Interface

AbstractBackgroundThe Investigation/Study/Assay (ISA) Metadata Framework is an established and widely used set of open-source community specifications and software tools for enabling discovery, exchange and publication of metadata from experiments in the life sciences. The original ISA software suite provided a set of user-facing Java tools for creating and manipulating the information structured in ISA-Tab – a now widely used tabular format. To make the ISA framework more accessible to machines and enable programmatic manipulation of experiment metadata, a JSON serialization ISA-JSON was developed.ResultsIn this work, we present the ISA API, a Python library for the creation, editing, parsing, and validating of ISA-Tab and ISA-JSON formats by using a common data model engineered as Python class objects. We describe the ISA API feature set, early adopters and its growing user community.ConclusionsThe ISA API provides users with rich programmatic metadata handling functionality to support automation, a common interface and an interoperable medium between the two ISA formats, as well as with other life science data formats required for depositing data in public databases.

scholarly journals The ELIXIR Core Data Resources: fundamental infrastructure for the life sciences

2020 ◽  
Vol 36 (8) ◽  
pp. 2636-2642 ◽  
Author(s):  
Rachel Drysdale ◽  
Charles E Cook ◽  
Robert Petryszak ◽  
Vivienne Baillie-Gerritsen ◽  
Mary Barlow ◽  
...  
Keyword(s):  
Life Sciences ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Core Data

Abstract Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Bridging Data Management and Knowledge Discovery in the Life Sciences

2008 ◽  
Vol 2 (1) ◽  
pp. 28-36 ◽  
Author(s):  
Karl Kugler ◽  
Maria Mercedes Tejada ◽  
Christian Baumgartner ◽  
Bernhard Tilg ◽  
Armin Graber ◽  
...  
Keyword(s):  
Data Mining ◽  
Knowledge Discovery ◽  
Data Warehouse ◽  
Life Science ◽  
Life Sciences ◽  
Relevant Information ◽  
Biomedical Data ◽  
Science Data ◽  
New Knowledge ◽  
Discovery Algorithms

In this work we present an application for integrating and analyzing life science data using a biomedical data warehouse system and tools developed in-house enabling knowledge discovery tasks. Knowledge discovery is known as a process where different steps have to be coupled in order to solve a specified question. In order to create such a combination of steps, a data miner using our in-house developed knowledge discovery tool KD3 is able to assemble functional objects to a data mining workflow. The generated workflows can easily be used for ulterior purposes by only adding new data and parameterizing the functional objects in the process. Workflows guide the performance of data integration and aggregation tasks, which were defined and implemented using a public available open source tool. To prove the concept of our application, intelligent query models were designed and tested for the identification of genotype-phenotype correlations in Marfan Syndrome. It could be shown that by using our application, a data miner can easily develop new knowledge discovery algorithms that may later be used to retrieve medical relevant information by clinical researchers.

scholarly journals The Dutch Techcentre for Life Sciences: Enabling data-intensive life science research in the Netherlands

F1000Research ◽  
2016 ◽  
Vol 4 ◽  
pp. 33 ◽  
Author(s):  
Lars Eijssen ◽  
Chris T. Evelo ◽  
Ruben Kok ◽  
Barend Mons ◽  
Rob Hooft ◽  
...  
Keyword(s):  
The Netherlands ◽  
Life Science ◽  
Life Sciences ◽  
Academic Research ◽  
Science Research ◽  
Science Data ◽  
Data Intensive ◽  
For Profit ◽  
Data Stewardship ◽  
Research Organisations

We describe the Data programme of the Dutch Techcentre for Life Sciences (DTL, www.dtls.nl). DTL is a new national organisation in scientific research that facilitates life scientists with technologies and technological expertise in an era where new projects often are data-intensive, multi-disciplinary, and multi-site. It is run as a lean not-for-profit organisation with research organisations (both academic and industrial) as paying members. The small staff of the organisation undertakes a variety of tasks that are necessary to perform or support modern academic research, but that are not easily undertaken in a purely academic setting. DTL Data takes care of such tasks related to data stewardship, facilitating exchange of knowledge and expertise, and brokering access to e-infrastructure. DTL also represents the Netherlands in ELIXIR, the European infrastructure for life science data. The organisation is still being fine-tuned and this will continue over time, as it is crucial for this kind of organisation to adapt to a constantly changing environment. However, already being underway for several years, our experiences can benefit researchers in other fields or other countries setting up similar initiatives.

scholarly journals Spathial: an R package for the evolutionary analysis of biological data

2020 ◽  
Vol 36 (17) ◽  
pp. 4664-4667
Author(s):  
Erika Gardini ◽  
Federico M Giorgi ◽  
Sergio Decherchi ◽  
Andrea Cavalli
Keyword(s):  
Tumor Progression ◽  
R Package ◽  
Biological Data ◽  
Supplementary Information ◽  
Evolutionary Analysis ◽  
Biological Processes ◽  
Rna Seq ◽  
The Core ◽  
High Level ◽  
Primary Problem

Abstract Summary A primary problem in high-throughput genomics experiments is finding the most important genes involved in biological processes (e.g. tumor progression). In this applications note, we introduce spathial, an R package for navigating high-dimensional data spaces. spathial implements the Principal Path algorithm, which is a topological method for locally navigating on the data manifold. The package, together with the core algorithm, provides several high-level functions for interpreting the results. One of the analyses we propose is the extraction of the genes that are mainly involved in the progress from one state to another. We show a possible application in the context of tumor progression using RNA-Seq and single-cell datasets, and we compare our results with two commonly used algorithms, edgeR and monocle3, respectively. Availability and implementation The R package spathial is available on the Comprehensive R Archive Network (https://cran.r-project.org/web/packages/spathial/index.html) and on GitHub (https://github.com/erikagardini/spathial). It is distributed under the GNU General Public License (version 3). Supplementary information Supplementary data are available at Bioinformatics online.

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