Literature DB >> 34626414

Informatics Ecosystems to Advance the Biology of Glycans.

Lewis J Frey1.   

Abstract

Glycomics researchers have identified the need for integrated database systems for collecting glycomics information in a consistent format. The goal is to create a resource for knowledge discovery and dissemination to wider research communities. This has the potential and has exhibited initial success, to extend the research community to include biologists, clinicians, chemists, and computer scientists. This chapter discusses the technology and approach needed to create integrated data resources and informatics ecosystems to empower the broader community to leverage extant glycomics data. The focus is on glycosaminoglycan (GAGs) and proteoglycan research, but the approach can be generalized. The methods described span the development of glycomics standards from CarbBank to Glyco Connection Tables. Integrated data sets provide a foundation for novel methods of analysis such as machine learning and deep learning for knowledge discovery. The implications of predictive analysis are examined in relation to disease biomarker to expand the target audience of GAG and proteoglycan research.
© 2022. Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Data integration; Data representation; Deep learning; Glycosaminoglycan; Informatics; Machine learning; Proteoglycan

Mesh:

Substances:

Year:  2022        PMID: 34626414     DOI: 10.1007/978-1-0716-1398-6_50

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  52 in total

Review 1.  Advancing glycomics: implementation strategies at the consortium for functional glycomics.

Authors:  Rahul Raman; Maha Venkataraman; Subu Ramakrishnan; Wei Lang; S Raguram; Ram Sasisekharan
Journal:  Glycobiology       Date:  2006-02-14       Impact factor: 4.313

Review 2.  Data integration strategies for predictive analytics in precision medicine.

Authors:  Lewis J Frey
Journal:  Per Med       Date:  2018-11-02       Impact factor: 2.512

Review 3.  Glycomics approach to structure-function relationships of glycosaminoglycans.

Authors:  Ram Sasisekharan; Rahul Raman; Vikas Prabhakar
Journal:  Annu Rev Biomed Eng       Date:  2006       Impact factor: 9.590

Review 4.  Glycomics: an integrated systems approach to structure-function relationships of glycans.

Authors:  Rahul Raman; S Raguram; Ganesh Venkataraman; James C Paulson; Ram Sasisekharan
Journal:  Nat Methods       Date:  2005-11       Impact factor: 28.547

Review 5.  Prospects for glycoinformatics.

Authors:  Serge Pérez; Barbara Mulloy
Journal:  Curr Opin Struct Biol       Date:  2005-10       Impact factor: 6.809

6.  GLYDE-an expressive XML standard for the representation of glycan structure.

Authors:  Satya S Sahoo; Christopher Thomas; Amit Sheth; Cory Henson; William S York
Journal:  Carbohydr Res       Date:  2005-10-20       Impact factor: 2.104

7.  LINUCS: linear notation for unique description of carbohydrate sequences.

Authors:  A Bohne-Lang; E Lang; T Förster; C W von der Lieth
Journal:  Carbohydr Res       Date:  2001-11-01       Impact factor: 2.104

8.  GlycoCT-a unifying sequence format for carbohydrates.

Authors:  S Herget; R Ranzinger; K Maass; C-W V D Lieth
Journal:  Carbohydr Res       Date:  2008-03-13       Impact factor: 2.104

9.  KCaM (KEGG Carbohydrate Matcher): a software tool for analyzing the structures of carbohydrate sugar chains.

Authors:  Kiyoko F Aoki; Atsuko Yamaguchi; Nobuhisa Ueda; Tatsuya Akutsu; Hiroshi Mamitsuka; Susumu Goto; Minoru Kanehisa
Journal:  Nucleic Acids Res       Date:  2004-07-01       Impact factor: 16.971

Review 10.  An introduction to bioinformatics for glycomics research.

Authors:  Kiyoko F Aoki-Kinoshita
Journal:  PLoS Comput Biol       Date:  2008-05-30       Impact factor: 4.475

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