GLYDE—an expressive XML standard for the representation of glycan structure

Sahoo, Satya S.; Thomas, Christopher; Sheth, Amit P.; Henson, Cory; York, William S.

doi:10.1016/j.carres.2005.09.019

Cited by 59 publications

(32 citation statements)

References 11 publications

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“…Glyde [70] is an XML-based standard for the representation of glycans as chemical structures. This format is based on connection tables at the level of atoms, and so, this format is particularly useful for chemistry-based applications and structural calculations.…”

Section: Glyde -Iimentioning

confidence: 99%

Informatics and Analytical Tools for Glycan Analysis and the Development of Biotherapeutics

Hayes¹,

Carta²,

Karlsson³

et al. 2015

Carbohydrate Chemistry: State of the Art and Challenges for Drug Development

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Section: Glyde -Iimentioning

confidence: 99%

Informatics and Analytical Tools for Glycan Analysis and the Development of Biotherapeutics

Hayes¹,

Carta²,

Karlsson³

et al. 2015

Carbohydrate Chemistry: State of the Art and Challenges for Drug Development

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“…We are currently working on annotating the experimental data using concepts from ProPreO and GlycO [28]. The annotation is at two levels, i.e., creation of metadata that is tied to each dataset and annotation of data itself.…”

Section: Semantically-mediated Implementation Of Glycoproteomics Workmentioning

confidence: 99%

“…We describe the use of GLYDE (GLYcan Data Exchange) [27] [28], an XML-based glycan data representation standard for populating GlycO. In case of ProPreO, we discuss our approach to populating a complex ontology with extremely large datasets using a dual-level instance base in which the experimental data (some having a size of 500MB), are stored in a separate location.…”

Section: Contributions and Outlinementioning

confidence: 99%

Knowledge modeling and its application in life sciences

Sahoo

Thomas

Sheth

et al. 2006

Proceedings of the 15th International Conference on World Wide Web

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High throughput glycoproteomics, similar to genomics and proteomics, involves extremely large volumes of distributed, heterogeneous data as a basis for identification and quantification of a structurally diverse collection of biomolecules. The ability to share, compare, query for and most critically correlate datasets using the native biological relationships are some of the challenges being faced by glycobiology researchers. As a solution for these challenges, we are building a semantic structure, using a suite of ontologies, which supports management of data and information at each step of the experimental lifecycle. This framework will enable researchers to leverage the large scale of glycoproteomics data to their benefit.In this paper, we focus on the design of these biological ontology schemas with an emphasis on relationships between biological concepts, on the use of novel approaches to populate these complex ontologies including integrating extremely large datasets (~500MB) as part of the instance base and on the evaluation of ontologies using OntoQA [38] metrics. The application of these ontologies in providing informatics solutions, for high throughput glycoproteomics experimental domain, is also discussed. We present our experience as a use case of developing two ontologies in one domain, to be part of a set of use cases, which are used in the development of an emergent framework for building and deploying biological ontologies.

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“…Since carbohydrate structures are described as so called hetero atoms within the HETATM records, all data assigned to the ATOM records (amino acids, nucleotides) are neglected. Sahoo et al, (2005) introduced GLYcan Data Exchange (GLYDE) standard as an XML-based representation format to enable interoperability and exchange of glycomics data. An online tool for the conversion of other representations to GLYDE format has been developed.…”

Section: Glycome Dbmentioning

confidence: 99%

Glycomics Data Mining

Rao¹,

Das²,

Umari³

2009

J Comput Sci Syst Biol

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The amount of glycomics data being generated is rapidly increasing as a result of improvements in analytical and computational methods. Correlation and analysis of this large, distributed data set requires an extensible and flexible representational standard that is also 'understood' by a wide range of software applications. An XML-based data representation standard that faithfully captures essential structural details of a glycan moiety along with additional information (such as data provenance) to aid the interpretation and usage of glycan data, will facilitate the exchange of glycomics data across the scientific community. We reviewed importance of data warehouse, showing a method of applying data mining techniques using XML, and some of the data issues, analysis problems, and results.

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GLYDE—an expressive XML standard for the representation of glycan structure

Cited by 59 publications

References 11 publications

Informatics and Analytical Tools for Glycan Analysis and the Development of Biotherapeutics

Informatics and Analytical Tools for Glycan Analysis and the Development of Biotherapeutics

Knowledge modeling and its application in life sciences

Glycomics Data Mining

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