| 1. |
- Kuhn, Thomas, et al.
(författare)
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CDK-Taverna : an open workflow environment for cheminformatics
- 2010
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Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 11, s. 159-
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Tidskriftsartikel (refereegranskat)abstract
- Background Small molecules are of increasing interest for bioinformatics in areas such as metabolomics and drug discovery. The recent release of large open access chemistry databases generates a demand for flexible tools to process them and discover new knowledge. To freely support open science based on these data resources, it is desirable for the processing tools to be open-source and available for everyone. Results Here we describe a novel combination of the workflow engine Taverna and the cheminformatics library Chemistry Development Kit (CDK) resulting in a open source workflow solution for cheminformatics. We have implemented more than 160 different workers to handle specific cheminformatics tasks. We describe the applications of CDK-Taverna in various usage scenarios. Conclusions The combination of the workflow engine Taverna and the Chemistry Development Kit provides the first open source cheminformatics workflow solution for the biosciences. With the Taverna-community working towards a more powerful workflow engine and a more user-friendly user interface, CDK-Taverna has the potential to become a free alternative to existing proprietary workflow tools.
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| 2. |
- Kyle, Jennifer E., et al.
(författare)
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Interpreting the lipidome : bioinformatic approaches to embrace the complexity
- 2021
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Ingår i: Metabolomics. - : Springer-Verlag New York. - 1573-3882 .- 1573-3890. ; 17:6
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Forskningsöversikt (refereegranskat)abstract
- BACKGROUND: Improvements in mass spectrometry (MS) technologies coupled with bioinformatics developments have allowed considerable advancement in the measurement and interpretation of lipidomics data in recent years. Since research areas employing lipidomics are rapidly increasing, there is a great need for bioinformatic tools that capture and utilize the complexity of the data. Currently, the diversity and complexity within the lipidome is often concealed by summing over or averaging individual lipids up to (sub)class-based descriptors, losing valuable information about biological function and interactions with other distinct lipids molecules, proteins and/or metabolites.AIM OF REVIEW: To address this gap in knowledge, novel bioinformatics methods are needed to improve identification, quantification, integration and interpretation of lipidomics data. The purpose of this mini-review is to summarize exemplary methods to explore the complexity of the lipidome.KEY SCIENTIFIC CONCEPTS OF REVIEW: Here we describe six approaches that capture three core focus areas for lipidomics: (1) lipidome annotation including a resolvable database identifier, (2) interpretation via pathway- and enrichment-based methods, and (3) understanding complex interactions to emphasize specific steps in the analytical process and highlight challenges in analyses associated with the complexity of lipidome data.
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| 3. |
- Mohammed Taha, Hiba, et al.
(författare)
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The NORMAN Suspect List Exchange (NORMAN-SLE) : facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry
- 2022
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Ingår i: Environmental Sciences Europe. - : Springer. - 2190-4707 .- 2190-4715. ; 34:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: The NORMAN Association (https://www.norman-network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for “suspect screening” lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide.Results: The NORMAN-SLE contains 99 separate suspect list collections (as of May 2022) from over 70 contributors around the world, totalling over 100,000 unique substances. The substance classes include per- and polyfluoroalkyl substances (PFAS), pharmaceuticals, pesticides, natural toxins, high production volume substances covered under the European REACH regulation (EC: 1272/2008), priority contaminants of emerging concern (CECs) and regulatory lists from NORMAN partners. Several lists focus on transformation products (TPs) and complex features detected in the environment with various levels of provenance and structural information. Each list is available for separate download. The merged, curated collection is also available as the NORMAN Substance Database (NORMAN SusDat). Both the NORMAN-SLE and NORMAN SusDat are integrated within the NORMAN Database System (NDS). The individual NORMAN-SLE lists receive digital object identifiers (DOIs) and traceable versioning via a Zenodo community (https://zenodo.org/communities/norman-sle), with a total of > 40,000 unique views, > 50,000 unique downloads and 40 citations (May 2022). NORMAN-SLE content is progressively integrated into large open chemical databases such as PubChem (https://pubchem.ncbi.nlm.nih.gov/) and the US EPA’s CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard/), enabling further access to these lists, along with the additional functionality and calculated properties these resources offer. PubChem has also integrated significant annotation content from the NORMAN-SLE, including a classification browser (https://pubchem.ncbi.nlm.nih.gov/classification/#hid=101).Conclusions: The NORMAN-SLE offers a specialized service for hosting suspect screening lists of relevance for the environmental community in an open, FAIR manner that allows integration with other major chemical resources. These efforts foster the exchange of information between scientists and regulators, supporting the paradigm shift to the “one substance, one assessment” approach. New submissions are welcome via the contacts provided on the NORMAN-SLE website (https://www.norman-network.com/nds/SLE/).
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| 4. |
- O'Boyle, Noel, et al.
(författare)
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Open Data, Open Source and Open Standards in chemistry : The Blue Obelisk five years on
- 2011
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Ingår i: Journal of Cheminformatics. - : BioMed Central. - 1758-2946. ; 3, s. 37-
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Tidskriftsartikel (refereegranskat)abstract
- Background: The Blue Obelisk movement was established in 2005 as a response to the lack of Open Data,Open Standards and Open Source (ODOSOS) in chemistry. It aims to make it easier to carry out chemistryresearch by promoting interoperability between chemistry software, encouraging cooperation between OpenSource developers, and developing community resources and Open Standards. Results: This contribution looks back on the work carried out by the Blue Obelisk in the past 5 years and surveysprogress and remaining challenges in the areas of Open Data, Open Standards, and Open Source in chemistry. Conclusions: We show that the Blue Obelisk has been very successful in bringing together researchers anddevelopers with common interests in ODOSOS, leading to development of many useful resources freely availableto the chemistry community
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| 5. |
- Spjuth, Ola, 1977-, et al.
(författare)
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A novel infrastructure for chemical safety predictions with focus on human health
- 2012
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Ingår i: Toxicology Letters. - : Elsevier BV. - 0378-4274 .- 1879-3169. ; 211:Supplm, s. S59-
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Tidskriftsartikel (refereegranskat)abstract
- A major objective of Computational Toxicology is to provide reliable and useful estimates in silico of (potentially) harmful actions of chemicals in humans. Predictive models are commonly based on in vitro and in vivo data, and aims at supporting risk assessment in various areas, including the environmental protection, food, and pharmaceutical sectors. The field is however hampered by the lack of standards, access to high quality data, validated predictive models, as well as means to connect toxicity data to genomics data.We present a framework and roadmap for a novel public infrastructure for predictive computational toxicology and chemical safety assessment, consisting of: (1) a repository capable of aggregating high quality toxicity data with gene expression data, (2) a repository where scientists can share and download predictive models for chemical safety, and (3) a user-friendly platform which makes the services and resources accessible for the scientific community. Databases under the framework will adhere to open standards and use standardized open exchange formats in order to interoperate with emerging international initiatives, such as the FP7-funded OpenTox and ToxBank projects.The infrastructure will strengthen and facilitate already ongoing activities within in silico toxicology, open up new possibilities for incorporating genomics data in chemicals safety modeling (toxicogenomics), as well as deepen the exploitation of signal transduction networks. The initiative will lay the foundation needed to boost decision support in risk assessment in a wide range of fields, including drug discovery, food safety, as well as agricultural and ecological safety assessment.
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| 6. |
- Spjuth, Ola, 1977-, et al.
(författare)
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Applications of the InChI in cheminformatics with the CDK and Bioclipse
- 2013
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Ingår i: Journal of Cheminformatics. - : Springer Science and Business Media LLC. - 1758-2946. ; 5:14
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundThe InChI algorithms are written in C++ and not available as Java library. Integration into softwarewritten in Java therefore requires a bridge between C and Java libraries, provided by the Java NativeInterface (JNI) technology.ResultsWe here describe how the InChI library is used in the Bioclipse workbench and the Chemistry Development Kit (CDK) cheminformatics library. To make this possible, a JNI bridge to the InChIlibrary was developed, JNI-InChI, allowing Java software to access the InChI algorithms. By usingthis bridge, the CDK project packages the InChI binaries in a module and offers easy access fromJava using the CDK API. The Bioclipse project packages and offers InChI as a dynamic OSGi bundlethat can easily be used by any OSGi-compliant software, in addition to the regular Java Archive andMaven bundles. Bioclipse itself uses the InChI as a key component and calculates it on the fly whenvisualizing and editing chemical structures. We demonstrate the utility of InChI with various applications in CDK and Bioclipse, such as decision support for chemical liability assessment, tautomergeneration, and for knowledge aggregation using a linked data approach.ConclusionsThese results show that the InChI library can be used in a variety of Java library dependency solutions, making the functionality easily accessible by Java software, such as in the CDK. The applications show various ways the InChI has been used in Bioclipse, to enrich its functionality.
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| 7. |
- Spjuth, Ola, 1977-, et al.
(författare)
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Bioclipse 2: A scriptable integration platform for the life sciences
- 2009
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Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 10, s. 397-
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Tidskriftsartikel (refereegranskat)abstract
- Background: Contemporary biological research integrates neighboring scientific domains to answer complex ques- tions in fields such as systems biology and drug discovery. This calls for tools that are intuitive to use, yet flexible to adapt to new tasks. Results: Bioclipse is a free, open source workbench with advanced features for the life sciences. Version 2.0 constitutes a complete rewrite of Bioclipse, and delivers a stable, scalable integration platform for developers and an intuitive workbench for end users. All functionality is available both from the graphical user interface and from a built-in novel domain-specific language, supporting the scientist in interdisciplinary research and reproducible analyses through advanced visualization of the inputs and the results. New components for Bioclipse 2 include a rewritten editor for chemical structures, a table for multiple molecules that supports gigabyte-sized files, as well as a graphical editor for sequences and alignments. Conclusions: Bioclipse 2 is equipped with advanced tools required to carry out complex analysis in the fields of bio- and cheminformatics. Developed as a Rich Client based on Eclipse, Bioclipse 2 leverages on today’s powerful desktop computers for providing a responsive user interface, but also takes full advantage of the Web and networked (Web/Cloud) services for more demanding calculations or retrieval of data. That Bioclipse 2 is based on an advanced and widely used service platform ensures wide extensibility, and new algorithms, visualizations as well as scripting commands can easily be added. The intuitive tools for end users and the extensible architecture make Bioclipse 2 ideal for interdisciplinary and integrative research. Bioclipse 2 is released under the Eclipse Public License (EPL), a flexible open source license that allows additional plugins to be of any license. Bioclipse 2 is implemented in Java and supported on all major platforms; Source code and binaries are freely available at http://www.bioclipse.net.
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| 8. |
- Spjuth, Ola, 1977-, et al.
(författare)
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Bioclipse-R : Integrating management and visualization of life science data with statistical analysis
- 2013
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Ingår i: Bioinformatics. - : Oxford University Press. - 1367-4803 .- 1367-4811. ; 29:2, s. 286-289
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Tidskriftsartikel (refereegranskat)abstract
- Bioclipse, a graphical workbench for the life sciences, provides functionality for managing and visualizing life science data. We introduce Bioclipse-R, which integrates Bioclipse and the statistical programming language R. The synergy between Bioclipse and R is demonstrated by the construction of a decision support system for anticancer drug screening and mutagenicity prediction, which shows how Bioclipse-R can be used to perform complex tasks from within a single software system.
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| 9. |
- Spjuth, Ola, 1977-, et al.
(författare)
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Open source drug discovery with Bioclipse
- 2012
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Ingår i: Current Topics in Medicinal Chemistry. - : Bentham Science Publishers Ltd.. - 1568-0266 .- 1873-4294. ; 12:18, s. 1980-1986
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Forskningsöversikt (refereegranskat)abstract
- We present the open source components for drug discovery that has been developed and integrated into the graphical workbench Bioclipse. Building on a solid open source cheminformatics core, Bioclipse has advanced functionality for managing and visualizing chemical structures and related information. The features presented here include QSAR/QSPR modeling, various predictive solutions such as decision support for chemical liability assessment, site-of-metabolism prediction, virtual screening, and knowledge discovery and integration. We demonstrate the utility of the described tools with examples from computational pharmacology, toxicology, and ADME. Bioclipse is used in both academia and industry, and is a good example of open source leading to new solutions for drug discovery.
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| 10. |
- Spjuth, Ola, 1977-, et al.
(författare)
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Towards interoperable and reproducible QSAR analyses : Exchange of data sets
- 2010
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Ingår i: Journal of Cheminformatics. - : BioMed Central. - 1758-2946. ; 2
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: QSAR/QSPR is a widely used method to relate chemical structures and responses based on ex- perimental observations. In QSAR, chemical structures are expressed as descriptors, which are mathematical representations like calculated properties or enumerated fragments. Many existing QSAR data sets are based on a combination of different software tools mixed with in-house developed solutions, with datasets manually assembled in spreadsheets. Currently there exists no agreed-upon definition of descriptors and no standard for exchanging data sets in QSAR, which together with numerous different descriptor implementations makes it a virtually impossible task to reproduce and validate analyses, and significantly hinders collaborations and re-use of data.RESULTS: We present a step towards standardizing QSAR analyses by defining interoperable and reproducible QSAR/QSPR data sets, comprising an open XML format (QSAR-ML) and an open extensible descriptor ontology (Blue Obelisk Descriptor Ontology). The ontology provides an extensible way of uniquely defining descriptors for use in QSAR experiments, and the exchange format supports multiple versioned implementations of these descriptors. Hence, a data set described by QSAR-ML makes its setup completely reproducible. We also provide an implementation as a set of plugins for Bioclipse that simplifies QSAR data set formation, and allows for exporting in QSAR-ML as well as traditional CSV formats. The implementation facilitates addition of new descriptor implementations, from locally installed software and remote Web services; the latter is demonstrated with REST and XMPP Web services.CONCLUSIONS: Standardized QSAR data sets opens up new ways to store, query, and exchange data for subsequent analyses. QSAR-ML supports completely reproducible dataset formation, solving the problems of defining which software components were used, their versions, and the case of multiple names for the same descriptor. This makes is easy to join, extend, combine data sets and also to work collectively. The presented Bioclipse plugins equip scientists with intuitive tools that make QSAR-ML widely available for the community.
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