1. |
- Almeida, A. M., et al.
(author)
-
Animal board invited review: advances in proteomics for animal and food sciences
- 2015
-
In: Animal. - : Cambridge University Press (CUP): STM Journals. - 1751-7311 .- 1751-732X. ; 9:1
-
Research review (peer-reviewed)abstract
- Animal production and health (APH) is an important sector in the world economy, representing a large proportion of the budget of all member states in the European Union and in other continents. APH is a highly competitive sector with a strong emphasis on innovation and, albeit with country to country variations, on scientific research. Proteomics (the study of all proteins present in a given tissue or fluid - i.e. the proteome) has an enormous potential when applied to APH. Nevertheless, for a variety of reasons and in contrast to disciplines such as plant sciences or human biomedicine, such potential is only now being tapped. To counter such limited usage, 6 years ago we created a consortium dedicated to the applications of Proteomics to APH, specifically in the form of a Cooperation in Science and Technology (COST) Action, termed FA1002 - Proteomics in Farm Animals: www.cost-faproteomics.org. In 4 years, the consortium quickly enlarged to a total of 31 countries in Europe, as well as Israel, Argentina, Australia and New Zealand. This article has a triple purpose. First, we aim to provide clear examples on the applications and benefits of the use of proteomics in all aspects related to APH. Second, we provide insights and possibilities on the new trends and objectives for APH proteomics applications and technologies for the years to come. Finally, we provide an overview and balance of the major activities and accomplishments of the COST Action on Farm Animal Proteomics. These include activities such as the organization of seminars, workshops and major scientific conferences, organization of summer schools, financing Short-Term Scientific Missions (STSMs) and the generation of scientific literature. Overall, the Action has attained all of the proposed objectives and has made considerable difference by putting proteomics on the global map for animal and veterinary researchers in general and by contributing significantly to reduce the East-West and North-South gaps existing in the European farm animal research. Future activities of significance in the field of scientific research, involving members of the action, as well as others, will likely be established in the future.
|
|
2. |
- Aoki-Kinoshita, K. F., et al.
(author)
-
GlycoBioinformatics
- 2021
-
In: Beilstein Journal of Organic Chemistry. - : Beilstein Institut. - 1860-5397. ; 17, s. 2726-2728
-
Journal article (peer-reviewed)
|
|
3. |
- Rojas-Macias, Miguel A., 1979, et al.
(author)
-
Towards a standardized bioinformatics infrastructure for N- and O-glycomics
- 2019
-
In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10
-
Journal article (peer-reviewed)abstract
- The mass spectrometry (MS)-based analysis of free polysaccharides and glycans released from proteins, lipids and proteoglycans increasingly relies on databases and software. Here, we review progress in the bioinformatics analysis of protein-released N- and O-linked glycans (N-and O-glycomics) and propose an e-infrastructure to overcome current deficits in data and experimental transparency. This workflow enables the standardized submission of MS-based glycomics information into the public repository UniCarb-DR. It implements the MIRAGE (Minimum Requirement for A Glycomics Experiment) reporting guidelines, storage of unprocessed MS data in the GlycoPOST repository and glycan structure registration using the GlyTouCan registry, thereby supporting the development and extension of a glycan structure knowledgebase.
|
|
4. |
- Alocci, D., et al.
(author)
-
GlyConnect: Glycoproteomics Goes Visual, Interactive, and Analytical
- 2019
-
In: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 18:2, s. 664-677
-
Journal article (peer-reviewed)abstract
- Knowledge of glycoproteins, their site-specific glycosylation patterns, and the glycan structures that they present to their recognition partners in health and disease is gradually being built on using a range of experimental approaches. The data from these analyses are increasingly being standardized and presented in various sources, from supplemental tables in publications to localized servers in investigator laboratories. Bioinformatics tools are now needed to collect these data and enable the user to search, display, and connect glycomics and glycoproteomics to other sources of related proteomics, genomics, and interactomics information. We here introduce GlyConnect (https://glyconnect.expasy.org/), the central platform of the Glycomics@ExPASy portal for glycoinformatics. GlyConnect has been developed to gather, monitor, integrate, and visualize data in a user-friendly way to facilitate the interpretation of collected glycoscience data. GlyConnect is designed to accommodate and integrate multiple data types as they are increasingly produced.
|
|
5. |
- Bojar, Daniel, et al.
(author)
-
Glycoinformatics in the Artificial Intelligence Era
- 2022
-
In: Chemical Reviews. - : American Chemical Society (ACS). - 0009-2665 .- 1520-6890. ; 122:20, s. 15971-15988
-
Research review (peer-reviewed)abstract
- Artificial intelligence (AI) methods have been and are now being increasingly integrated in prediction software implemented in bioinformatics and its glycoscience branch known as glycoinformatics. AI techniques have evolved in the past decades, and their applications in glycoscience are not yet widespread. This limited use is partly explained by the peculiarities of glyco-data that are notoriously hard to produce and analyze. Nonetheless, as time goes, the accumulation of glycomics, glycoproteomics, and glycan-binding data has reached a point where even the most recent deep learning methods can provide predictors with good performance. We discuss the historical development of the application of various AI methods in the broader field of glycoinformatics. A particular focus is placed on shining a light on challenges in glyco-data handling, contextualized by lessons learnt from related disciplines. Ending on the discussion of state-of-the-art deep learning approaches in glycoinformatics, we also envision the future of glycoinformatics, including development that need to occur in order to truly unleash the capabilities of glycoscience in the systems biology era.
|
|
6. |
- Campbell, Matthew P, et al.
(author)
-
Toolboxes for a standardised and systematic study of glycans
- 2014
-
In: BMC Bioinformatics. - 1471-2105. ; 15:Suppl. 1
-
Journal article (peer-reviewed)abstract
- Abstract Background Recent progress in method development for characterising the branched structures of complex carbohydrates has now enabled higher throughput technology. Automation of structure analysis then calls for software development since adding meaning to large data collections in reasonable time requires corresponding bioinformatics methods and tools. Current glycobioinformatics resources do cover information on the structure and function of glycans, their interaction with proteins or their enzymatic synthesis. However, this information is partial, scattered and often difficult to find to for non-glycobiologists. Methods Following our diagnosis of the causes of the slow development of glycobioinformatics, we review the "objective" difficulties encountered in defining adequate formats for representing complex entities and developing efficient analysis software. Results Various solutions already implemented and strategies defined to bridge glycobiology with different fields and integrate the heterogeneous glyco-related information are presented. Conclusions Despite the initial stage of our integrative efforts, this paper highlights the rapid expansion of glycomics, the validity of existing resources and the bright future of glycobioinformatics.
|
|
7. |
- Campbell, MP, et al.
(author)
-
UniCarbKB: Putting the pieces together for glycomics research
- 2011
-
In: Proteomics. - : Wiley. - 1615-9853. ; 11:21, s. 4117-4121
-
Journal article (peer-reviewed)abstract
- Despite the success of several international initiatives the glycosciences still lack a managed infrastructure that contributes to the advancement of research through the provision of comprehensive structural and experimental glycan data collections. UniCarbKB is an initiative that aims to promote the creation of an online information storage and search platform for glycomics and glycobiology research. The knowledgebase will offer a freely accessible and information-rich resource supported by querying interfaces, annotation technologies and the adoption of common standards to integrate structural, experimental and functional data. The UniCarbKB framework endeavors to support the growth of glycobioinformatics and the dissemination of knowledge through the provision of an open and unified portal to encourage the sharing of data. In order to achieve this, the framework is committed to the development of tools and procedures that support data annotation, and expanding interoperability through cross-referencing of existing databases. Database URL: http://www.unicarbkb.org.
|
|
8. |
- Gotz, L., et al.
(author)
-
GlycoDigest: a tool for the targeted use of exoglycosidase digestions in glycan structure determination
- 2014
-
In: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 30:21, s. 3131-3133
-
Journal article (peer-reviewed)abstract
- Sequencing oligosaccharides by exoglycosidases, either sequentially or in an array format, is a powerful tool to unambiguously determine the structure of complex N- and O-link glycans. Here, we introduce GlycoDigest, a tool that simulates exoglycosidase digestion, based on controlled rules acquired from expert knowledge and experimental evidence available in GlycoBase. The tool allows the targeted design of glycosidase enzyme mixtures by allowing researchers to model the action of exoglycosidases, thereby validating and improving the efficiency and accuracy of glycan analysis.
|
|
9. |
- Hayes, Catherine A, et al.
(author)
-
UniCarb-DB: a database resource for glycomic discovery
- 2011
-
In: BIOINFORMATICS. - 1367-4803. ; 27:9, s. 1343-1344
-
Journal article (peer-reviewed)abstract
- Glycosylation is one of the most important post-translational modifications of proteins, known to be involved in pathogen recognition, the innate immune response and protection of epithelial membranes. However, when compared to the tools and databases available for the processing of high-throughput proteomic data, the glycomic domain is severely lacking. While tools to assist the analysis of MS and HPLC are continuously improving there are few resources available to support LC-MS/MS techniques for glycan structure profiling. Here, we present a platform for presenting oligosaccharide structures and fragment data characterised by LC-MS/ MS strategies. The database is annotated with high-quality data sets and is designed to extend and reinforce those standards and ontologies developed by existing glycomics databases
|
|
10. |
- Jin, Chunsheng, et al.
(author)
-
UniCarb-DB: An MS/MS Experimental Glycomic Fragmentation Database
- 2024
-
In: Methods in molecular biology (Clifton, N.J.). - 1940-6029. ; 2836, s. 77-96
-
Journal article (peer-reviewed)abstract
- Glycosylation is a unique posttranslational modification that dynamically shapes the surface of cells. Glycans attached to proteins or lipids in a cell or tissue are studied as a whole and collectively designated as a glycome. UniCarb-DB is a glycomic spectral library of tandem mass spectrometry (MS/MS) fragment data. The current version of the database consists of over 1500 entries and over 1000 unique structures. Each entry contains parent ion information with associated MS/MS spectra, metadata about the original publication, experimental conditions, and biological origin. Each structure is also associated with the GlyTouCan glycan structure repository allowing easy access to other glycomic resources. The database can be directly utilized by mass spectrometry (MS) experimentalists through the conversion of data generated by MS into structural information. Flexible online search tools along with a downloadable version of the database are easily incorporated in either commercial or open-access MS software. This chapter highlights UniCarb-DB online search tool to browse differences of isomeric structures between spectra, a peak matching search between user-generated MS/MS spectra and spectra stored in UniCarb-DB and more advanced MS tools for combined quantitative and qualitative glycomics.
|
|