Informatics tools to advance the biology of glycosaminoglycans and proteoglycans

Methods in Molecular Biology

Volumn 1229, Issue , 2015, Pages 271-287

  Frey, Lewis J ^a  

^a NONE

Author keywords

Data integration; Data representation; Glycosaminoglycan; Informatics; Machine learning; Proteoglycan

Indexed keywords

GLYCOSAMINOGLYCAN; PROTEOGLYCAN;

ARTICLE; BIOINFORMATICS; DATA BASE; GLYCOBIOLOGY; GLYCOSYLATION; KNOWLEDGE DISCOVERY; MACHINE LEARNING; PRIORITY JOURNAL; ARTIFICIAL INTELLIGENCE; BIOLOGY; CHEMICAL STRUCTURE; CHEMISTRY; PROCEDURES; SYSTEM ANALYSIS;

ARTIFICIAL INTELLIGENCE; COMPUTATIONAL BIOLOGY; GLYCOSAMINOGLYCANS; MODELS, MOLECULAR; PROTEOGLYCANS; SYSTEMS INTEGRATION;

EID: 84921793741     PISSN: 10643745     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-1-4939-1714-3_23     Document Type: Article

References (51)

1. Editorial (2005) Sweet collaborations. Nat Methods 2:799
2. National Research Council (US) Committee on Assessing the Importance and Impact of Glycomics and Glycosciences (2012) Transforming glycoscience: a roadmap for the future. National Academies Press, Washington, DC
3. Raman R, Venkataraman M, Ramakrishnan S, Lang W, Raguram S, Sasisekharan R (2006) Advancing glycomics: implementation strategies at the Consortium for Functional Glycomics. Glycobiology 16(5):82R-90R doi: 10.1093/glycob/cwj080
4. Esko JD, Kimata K, Lindahl U (2009) Proteoglycans and sulfated glycosaminoglycans. In: Varki A, Cummings RD, Esko JD et al (eds) Essentials of glycobiology, 2nd edn. Cold Spring Harbor Laboratory, Cold Spring Harbor, NY
5. Aoki-kinoshita KF (2008) An introduction to bioinformatics for glycomics research. PLoS Comput Biol 4(5):1-7 doi: 10.1371/journal. pcbi.1000075
6. Raman R, Raguram S, Venkataraman G, Paulson JC, Sasisekharan R (2005) Glycomics: an integrated systems approach to structurefunction relationships of glycans. Nat Methods 2(11):817-824 doi: 10.1038/NMETH807
7. Sasisekharan R, Raman R, Prabhakar V (2006) Glycomics approach to structure-function relationships of glycosaminoglycans. Annu Rev Biomed Eng 8:181-231 doi: 10.1146/ annurev.bioeng.8.061505.095745
8. Perez S, Mulloy B (2005) Prospects for glycoinformatics. Curr Opin Struct Biol 15:517-524
9. International Union of Pure and Applied Chemistry (1997) Compendium of analytical nomenclature, 3rd edn. Blackwell Science, Oxford, UK, http://www.chem.qmul.ac.uk/ iupac/2carb/38.html. ISBN 86542-6155
10. Bohne-lang A, Lang E, Fo T (2001) LINUCS: linear notation for unique description of carbohydrate sequences. Carbohydr Res 336:1-11
11. Aoki-kinoshita K, Yamaguchi A, Ueda N, Akutsu T, Mamitsuka H, Goto S, Kanehisa M (2004) KCaM (KEGG carbohydrate matcher): a software tool for analyzing the structures of carbohydrate sugar chains. Nucleic Acids Res 32:W267-W272
12. Sahoo SS, Thomas C, Sheth A, Henson C, York WS (2005) GLYDE-an expressive XML standard for the representation of glycan structure. Carbohydr Res 340:2802-2807 doi: 10.1016/j.carres.2005.09.019
13. York WS, Kochut KJ, Miller JA, Sahoo S, Thomas C, Henson C (2007) GLYDE-II-GLYcan structural data exchange using connection tables. University of Georgia Technical Report
14. Herget S, Ranzinger R, Maass K (2008) GlycoCT-a unifying sequence format for carbohydrates. Carbohydr Res 343:2162-2171 doi: 10.1016/j.carres.2008.03.011
15. Doubet S, Albersheim P (1992) CarbBank. Glycobiology 2(6):505
16. Doubet S, Bock K, Smith D, Darvill A, Albersheim P (1989) The complex carbohydrate structure database. Trends Biochem Sci 14(12):475-477
17. Consortium for Functional Glycomics (2013) http://www.functionalglycomics.org/glycomics/ molecule/jsp/carbohydrate/carb-MoleculeHome.jsp. Accessed 23 Dec 2013
18. Consortium for Functional Glycomics Binding Proteins (2013) http://www.functionalglycomics.org/glycomics/molecule/jsp/gbpMoleculehome. jsp. Accessed 23 Dec 2013
19. Lütteke T, Bohne-lang A, Loss A, Goetz T, Frank M, Lieth CW (2006) GLYCOSCIENCES. de: an Internet portal to support glycomics and glycobiology research. Glycobiology 16(5):71-81 doi: 10.1093/gly cob/cwj049
20. Glycoscience.de database (2013) http://www. glycosciences.de/tools/linucs/input.php. Accessed 23 Dec 2013
21. Hashimoto K, Goto S, Kawano S, Aokikinoshita KF, Ueda N, Hamajima M et al (2006) REVIEW KEGG as a glycome informatics resource. Glycobiology 16(5):63-70 doi: 10.1093/glycob/cwj010
22. KEGG GenomeNet (2013) http://www. genome.jp. Accessed 23 Dec 2013
23. Ranzinger R, Herget S, Wetter T, Lieth CW (2008) GlycomeDB: an integration of openaccess carbohydrate structure databases. BMC Bioinformatics 13:1-13 doi: 10.1186/1471-2105-9-384
24. GlycomeDB (2013) http://www.glycome-db. org/showMenu.action?major=downloads. Accessed 23 Dec 2013
25. Ceroni A, Dell A, Haslam SM (2007) The GlycanBuilder: a fast, intuitive and fl exible software tool for building and displaying glycan structures. Source Code Biol Med 13:1-13 doi: 10.1186/1751-0473-2-3
26. Ceroni A, Dell A, Haslam SM (2007) GlycanBuilder. http://www.ncbi.nlm.nih. gov/pmc/articles/PMC1994674/bin/ 1751-0473-2-3-S1.zip. Accessed 23 Dec 2013
27. GlycosWorkbench (2013) http://code.google. com/p/glycoworkbench/. Accessed 23 Dec 2013
28. IBM Watson (2013) http://www.research. ibm.com/labs/watson/index.shtml. Accessed 23 Dec 2013
29. Murdoch TB, Detsky AS (2013) The inevitable application of big data to health care. JAMA 309(13):5-6
30. Aoki-kinoshita KF (2003) Effi cient treematching methods for accurate carbohydrate database queries. Genome Inform 143: 134-143
31. Smith TF, Waterman MS (1981) Identifi cation of common molecular subsequences. J Mol Biol 147:195-197
32. Ueda N, Aoki-kinoshita KF, Yamaguchi A, Akutsu T (2005) A probabilistic model for mining labeled ordered trees: capturing patterns in carbohydrate sugar chains. IEEE Trans Knowl Data Eng 17(8):1051-1064
33. Aoki-kinoshita KF, Ueda N, Mamitsuka H, Kanehisa M (2006) Profi lePSTMM: capturing tree-structure motifs in carbohydrate sugar chains. Bioinformatics 22(14):25-34 doi: 10.1093/bioinformatics/btl244
34. Kawano S, Hashimoto K, Miyama T, Goto S, Kanehisa M (2005) Prediction of glycan structures from gene expression data based on glycosyltransferase reactions. Bioinformatics 21: 3976-3982
35. Suga A, Yamanishi Y, Hashimoto K, Goto S, Kanehisa M (2007) An improved scoring scheme for predicting glycan structures from gene expression data. Genome Inform 18:237-246
36. Venkataraman G, Shriver Z, Raman R, Sasisekharan R (1999) Sequencing complex polysaccharides. Science 286:537-542
37. Shriver Z, Raman R, Venkataraman G, Drummond K, Turnbull J et al (2000) Sequencing of 3-O sulfate containing heparin decasaccharides with a partial antithrombin III binding site. Proc Natl Acad Sci U S A 97: 10359-10364
38. Guerrini M, Raman R, Venkataraman G, Torri G, Sasisekharan R, Casu B (2002) A novel computational approach to integrate NMR spectroscopy and capillary electrophoresis for structure assignment of heparin and heparan sulfate oligosaccharides. Glycobiology 12:713-719
39. Maxwell E, Tan Y, Tan Y, Hu H, Benson G, Aizikov K et al (2012) GlycReSoft: a software package for automated recognition of glycans from LC/MS data. PLoS One 7(9):e45474 doi: 10.1371/journal.pone.0045474
40. Li L, Zhang F, Zaia J, Linhardt RJ (2012) Top-down approach for the direct characterization of low molecular weight heparins using LC-FT-MS. Anal Chem 84:8822-8829
41. Lieth CW, Bohne-Lang A, Lohmann KK, Frank M (2004) Bioinformatics for glycomics: status, methods, requirements, and perspectives. Brief Bioinform 5:164-178
42. Lieth CW, Lutteke T, Frank M (2006) The role of informatics in glycobiology research with special emphasis on automatic interpretation of MS spectra. Biochim Biophys Acta 1760:568-577
43. Lütteke T, Frank M, von der Lieth CW (2005) Carbohydrate structure suite (CSS): analysis of carbohydrate 3D structures derived from the PDB. Nucleic Acids Res 33:D242-D246
44. Wang H, Julenius K, Hryhorenko J et al (2007) Systematic analysis of proteoglycan modifi cation sites in caenorhabditis elegans by scanning mutagenesis. J Biol Chem doi: 10.1074/jbc.M609193200
45. Shao C, Shi X, White M, Huang Y, Hartshorn K, Zaia J (2013) Comparative glycomics of leukocyte glycosaminoglycans. FEBS J 280: 2447-2461 doi: 10.1111/febs.12231
46. Konishi Y, Aoki-kinoshita KF (2012) The GlycomeAtlas tool for visualizing and querying glycome data. Bioinformatics 28(21):2849-2850 doi: 10.1093/bioinformatics/ bts516
47. Shi X, Zaia J (2009) Organ-specifi c heparan sulfate structural phenotypes. J Biol Chem 284:11806-11814
48. Smetsers TFCM, Westerlo EMA, Dam GB et al (2003) Localization and characterization of melanoma-associated glycosaminoglycans: differential expression of chondroitin and heparan sulfate epitopes in melanoma localization and characterization of melanoma-associated glycosaminoglycans. Cancer Res 63:2965-2970
49. Suarez ER, Paredes-gamero EJ, Giglio AD, Luis I, Nader HB, Aparecida M et al (2013) Heparan sulfate mediates trastuzumab effect in breast cancer cells. BMC Cancer 13(1):444 doi: 10.1186/1471-2407-13-444
50. Gomes AM, Stelling MP, Pavao MSG (2013) Heparan sulfate and heparanase as modulators of breast cancer progression. Biomed Res Int. 11 pgs. http://dx.doi.org/ 10.1155/2013/852093
51. Packer NH, von der Lieth CW, Aoki-Kinoshita KF, Lebrilla CB, Paulson JC et al (2008) Frontiers in glycomics: bioinformatics and biomarkers in disease. Proteomics 8:8-20