Demo Data from EDBT 2026 / reviewers in the wild / expert
Elisabeth Gasteiger
dblp:21/435
· DBLP profile ↗
8ranked-venue papers
0as first author
1since 2021 · last 2023
0000-0003-1829-162XORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 8 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
5 papers |
Bioinformatics and computational biology · 100% |
Topics — the 7 heaviest of 8, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › protein analysis › protein bioinformatics
protein annotation |
1.1 | 2 | 2023 | Annotation of biologically relevant ligands in UniProtKB using ChEBI · Bioinform. 2023 Enzyme annotation in UniProtKB using Rhea · Bioinform. 2020 |
Bioinformatics and computational biology
bioinformatics infrastructure |
0.4 | 1 | 2020 | The ELIXIR Core Data Resources: fundamental infrastructure for the life sciences · Bioinform. 2020 |
Bioinformatics and computational biology › protein function prediction
enzyme function annotation |
0.4 | 1 | 2020 | Enzyme annotation in UniProtKB using Rhea · Bioinform. 2020 |
Bioinformatics and computational biology › proteomics
post-translational modification |
0.0 | 1 | 2002 | The Sulfinator: predicting tyrosine sulfation sites in protein sequences · Bioinform. 2002 |
Bioinformatics and computational biology › multiple sequence alignment
alignment visualization |
0.0 | 1 | 1996 | LALNVIEW: a graphical viewer for pairwise sequence alignments · Comput. Appl. Biosci. 1996 |
Bioinformatics and computational biology › sequence alignment
pairwise sequence alignment |
0.0 | 1 | 1996 | LALNVIEW: a graphical viewer for pairwise sequence alignments · Comput. Appl. Biosci. 1996 |
Bioinformatics and computational biology
sequence analysis |
0.0 | 1 | 1996 | LALNVIEW: a graphical viewer for pairwise sequence alignments · Comput. Appl. Biosci. 1996 |
Methods — techniques the papers use, named apart from their topics
ontology-based annotation · 1.1SPARQL querying · 1.1hidden markov model · 0.0local alignment · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Annotation of biologically relevant ligands in UniProtKB using ChEBIabstractMOTIVATION: To provide high quality, computationally tractable annotation of binding sites for biologically relevant (cognate) ligands in UniProtKB using the chemical ontology ChEBI (Chemical Entities of Biological Interest), to better support efforts to study and predict functionally relevant interactions between protein sequences and structures and small molecule ligands. RESULTS: We structured the data model for cognate ligand binding site annotations in UniProtKB and performed a complete reannotation of all cognate ligand binding sites using stable unique identifiers from ChEBI, which we now use as the reference vocabulary for all such annotations. We developed improved search and query facilities for cognate ligands in the UniProt website, REST API and SPARQL endpoint that leverage the chemical structure data, nomenclature and classification that ChEBI provides. AVAILABILITY AND IMPLEMENTATION: Binding site annotations for cognate ligands described using ChEBI are available for UniProtKB protein sequence records in several formats (text, XML and RDF) and are freely available to query and download through the UniProt website (www.uniprot.org), REST API (www.uniprot.org/help/api), SPARQL endpoint (sparql.uniprot.org/) and FTP site (https://ftp.uniprot.org/pub/databases/uniprot/). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Elisabeth Coudert, Sebastien Gehant, Edouard De Castro, Monica Pozzato, Delphine Baratin, Teresa Batista Neto, Christian J. A. Sigrist, Nicole Redaschi, Alan J. Bridge, Lucila Aimo, Ghislaine Argoud-Puy, Andrea H. Auchincloss, Kristian B. Axelsen, Parit Bansal, Marie-Claude Blatter, Jerven T. Bolleman, Emmanuel Boutet, Lionel Breuza, Blanca Cabrera Gil, Cristina Casals-Casas, Kamal Chikh Echioukh, Béatrice A. Cuche, Anne Estreicher, Maria Livia Famiglietti, Marc Feuermann, Elisabeth Gasteiger, Pascale Gaudet, Vivienne Baillie Gerritsen, Arnaud Gos, Nadine Gruaz-Gumowski, Chantal Hulo, Nevila Hyka-Nouspikel, Florence Jungo, Arnaud Kerhornou, Philippe Le Mercier, Damien Lieberherr, Patrick Masson, Anne Morgat, Venkatesh Muthukrishnan, Salvo Paesano, Ivo Pedruzzi, Sandrine Pilbout, Lucille Pourcel, Sylvain Poux, Manuela Pruess, Catherine Rivoire, Karin Sonesson, Shyamala Sundaram, Alex Bateman, Maria Jesus Martin, Sandra E. Orchard, Michele Magrane, Shadab Ahmad, Emanuele Alpi, Emily H. Bowler-Barnett, Ramona Britto, Hema Bye-A-Jee, Austra Cukura, Paul Denny 0002, Tunca Dogan, Thankgod Ebenezer, Penelope Garmiri, Leonardo Jose da Costa Gonzales, Emma Hatton-Ellis, Abdulrahman Hussein, Alexandr Ignatchenko, Giuseppe Insana, Rizwan Ishtiaq, Vishal Joshi, Dushyanth Jyothi, Swaathi Kandasamy, Antonia Lock, Aurelien Luciani, Marija Lugaric, Yvonne Lussi, Alistair MacDougall, Fábio Madeira, Mahdi Mahmoudy, Alok Mishra 0004, Katie Moulang, Andrew Nightingale, Sangya Pundir, Guoying Qi, Shriya Raj, Pedro Raposo, Daniel Rice, Rabie Saidi, Elena Speretta, James D. Stephenson, Prabhat Totoo, Edward Turner, Nidhi Tyagi, Preethi Vasudev, Kate Warner, Xavier Watkins, Rossana Zaru, Hermann Zellner, Cathy H. Wu, Cecilia N. Arighi, Leslie Arminski, Chuming Chen, Yongxing Chen, Hongzhan Huang, Kati Laiho, Peter B. McGarvey, Darren A. Natale, Karen E. Ross, C. R. Vinayaka, Qinghua Wang 0003 |
Bioinform. | 26 |
| 2020 | The ELIXIR Core Data Resources: fundamental infrastructure for the life sciencesabstractSUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Rachel Drysdale, Charles E. Cook, Robert Petryszak, Vivienne Baillie Gerritsen, Mary Barlow, Elisabeth Gasteiger, Franziska Gruhl, Jerry Lanfear, Rodrigo Lopez, Nicole Redaschi, Heinz Stockinger, Daniel Teixeira, Aravind Venkatesan, Alex Bateman, Alan J. Bridge, Guy Cochrane, Robert D. Finn, Frank Oliver Glöckner, Marc Hanauer, Thomas M. Keane, Luana Licata, Per Oksvold, Sandra E. Orchard, Christine A. Orengo, Helen E. Parkinson, Bengt Persson, Pablo Porras, Jordi Rambla De Argila, Ana Rath, Charlotte Rodwell, Ugis Sarkans, Dietmar Schomburg, Ian Sillitoe, J. Dylan Spalding, Mathias Uhlen, Sameer Velankar, Juan Antonio Vizcaíno, Kalle von Feilitzen, Christian von Mering, Andy Yates, Niklas Blomberg, Christine Durinx, Johanna R. McEntyre |
Bioinform. | 6 |
| 2020 | Enzyme annotation in UniProtKB using RheaabstractMOTIVATION: To provide high quality computationally tractable enzyme annotation in UniProtKB using Rhea, a comprehensive expert-curated knowledgebase of biochemical reactions which describes reaction participants using the ChEBI (Chemical Entities of Biological Interest) ontology. RESULTS: We replaced existing textual descriptions of biochemical reactions in UniProtKB with their equivalents from Rhea, which is now the standard for annotation of enzymatic reactions in UniProtKB. We developed improved search and query facilities for the UniProt website, REST API and SPARQL endpoint that leverage the chemical structure data, nomenclature and classification that Rhea and ChEBI provide. AVAILABILITY AND IMPLEMENTATION: UniProtKB at https://www.uniprot.org; UniProt REST API at https://www.uniprot.org/help/api; UniProt SPARQL endpoint at https://sparql.uniprot.org/; Rhea at https://www.rhea-db.org. Anne Morgat, Thierry Lombardot, Elisabeth Coudert, Kristian B. Axelsen, Teresa Batista Neto, Sebastien Gehant, Parit Bansal, Jerven T. Bolleman, Elisabeth Gasteiger, Edouard De Castro, Delphine Baratin, Monica Pozzato, Ioannis Xenarios, Sylvain Poux, Nicole Redaschi, Alan J. Bridge |
Bioinform. | 9 |
| 2009 | Infrastructure for the life sciences: design and implementation of the UniProt websiteabstractBACKGROUND: The UniProt consortium was formed in 2002 by groups from the Swiss Institute of Bioinformatics (SIB), the European Bioinformatics Institute (EBI) and the Protein Information Resource (PIR) at Georgetown University, and soon afterwards the website http://www.uniprot.org was set up as a central entry point to UniProt resources. Requests to this address were redirected to one of the three organisations' websites. While these sites shared a set of static pages with general information about UniProt, their pages for searching and viewing data were different. To provide users with a consistent view and to cut the cost of maintaining three separate sites, the consortium decided to develop a common website for UniProt. Following several years of intense development and a year of public beta testing, the http://www.uniprot.org domain was switched to the newly developed site described in this paper in July 2008. DESCRIPTION: The UniProt consortium is the main provider of protein sequence and annotation data for much of the life sciences community. The http://www.uniprot.org website is the primary access point to this data and to documentation and basic tools for the data. These tools include full text and field-based text search, similarity search, multiple sequence alignment, batch retrieval and database identifier mapping. This paper discusses the design and implementation of the new website, which was released in July 2008, and shows how it improves data access for users with different levels of experience, as well as to machines for programmatic access.http://www.uniprot.org/ is open for both academic and commercial use. The site was built with open source tools and libraries. Feedback is very welcome and should be sent to [email protected]. CONCLUSION: The new UniProt website makes accessing and understanding UniProt easier than ever. The two main lessons learned are that getting the basics right for such a data provider website has huge benefits, but is not trivial and easy to underestimate, and that there is no substitute for using empirical data throughout the development process to decide on what is and what is not working for your users. Eric Jain, Amos Bairoch, Severine Duvaud, Isabelle Phan, Nicole Redaschi, Baris E. Suzek, Maria Jesus Martin, Peter B. McGarvey, Elisabeth Gasteiger |
BMC Bioinform. | 9 |
| 2004 | Swiss-Prot: Juggling between evolution and stabilityabstractWe describe some of the aspects of Swiss-Prot that make it unique, explain what are the developments we believe to be necessary for the database to continue to play its role as a focal point of protein knowledge, and provide advice pertinent to the development of high-quality knowledge resources on one aspect or the other of the life sciences. Amos Bairoch, Brigitte Boeckmann, Serenella Ferro, Elisabeth Gasteiger |
Briefings Bioinform. | 4 |
| 2002 | High-quality Protein Knowledge Resource: SWISS-PROT and TrEMBLabstractSWISS-PROT is a curated protein sequence database which strives to provide a high level of annotation (such as the description of the function of a protein, its domain structure, post-translational modifications, variants, etc.), a minimal level of redundancy and a high level of integration with other databases. Together with its automatically annotated supplement TrEMBL, it provides a comprehensive and high-quality view of the current state of knowledge about proteins. Ongoing developments include the further improvement of functional and automatic annotation in the databases including evidence attribution with particular emphasis on the human, archaeal and bacterial proteomes and the provision of additional resources such as the International Protein Index (IPI) and XML format of SWISS-PROT and TrEMBL to the user community. Claire O'Donovan, Maria Jesus Martin, Alexandre Gattiker, Elisabeth Gasteiger, Amos Bairoch, Rolf Apweiler |
Briefings Bioinform. | 4 |
| 2002 | The Sulfinator: predicting tyrosine sulfation sites in protein sequencesabstractUNLABELLED: Protein tyrosine sulfation is an important post-translational modification of proteins that go through the secretory pathway. No clear-cut acceptor motif can be defined that allows the prediction of tyrosine sulfation sites in polypeptide chains. The Sulfinator is a software tool that can be used to predict tyrosine sulfation sites in protein sequences with an overall accuracy of 98%. Four different Hidden Markov Models were constructed, each of them specialized to recognize sulfated tyrosine residues depending on their location within the sequence: near the N-terminus, near the C-terminus, in the center of a window with a size of at least 25 amino acids, as well as in windows containing several tyrosine residues. AVAILABILITY: The Sulfinator is accessible at (http://www.expasy.org/tools/sulfinator/). SUPPLEMENTARY INFORMATION: Sulfinator documentation is accessible at (http://www.expasy.org/tools/sulfinator/sulfinator-doc.html). Flavio Monigatti, Elisabeth Gasteiger, Amos Bairoch, Eva Jung |
Bioinform. | 2 |
| 1996 | LALNVIEW: a graphical viewer for pairwise sequence alignmentsabstractLALNVIEW is a graphical program for visualising local alignments between two sequences (protein or nucleic acids). Sequences are represented by coloured rectangles to give an overall picture of their similarities. LALNVIEW can display sequence features (exon, intron, active site, domain, propeptide, etc.) along with the alignment. When using LALNVIEW through our Web servers, sequence features are automatically extracted from database annotations (SWISS-PROT, GenBank, EMBL or HOVERGEN) and displayed with the alignment. LALNVIEW is a useful tool for analysing pairwise sequence alignments and for making the link between sequence homology and what is known about the structure or function of sequences. LALNVIEW executables for UNIX, Macintosh and PC computers are freely available from our server (http:// expasy.hcuge.ch/sprot/lalnview.html). Laurent Duret, Elisabeth Gasteiger, Guy Perrière |
Comput. Appl. Biosci. | 2 |