Demo Data from VLDB 2026 / reviewers in the wild / expert
Andy Yates
dblp:64/1337 · also Andrew D. Yates
· DBLP profile ↗
7ranked-venue papers
2as first author
1since 2021 · last 2021
0000-0002-8886-4772ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 7 · 2 first-author · 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
6 papers |
Bioinformatics and computational biology · 100% |
Topics — the 10 heaviest of 10, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › genomics
genomic data management |
0.7 | 2 | 2021 | Refget: standardized access to reference sequences · Bioinform. 2021 The Ensembl REST API: Ensembl Data for Any Language · Bioinform. 2015 |
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 › bioinformatics infrastructure
bioinformatics framework |
0.2 | 2 | 2012 | BioJava: an open-source framework for bioinformatics in 2012 · Bioinform. 2012 BioJava: an open-source framework for bioinformatics · Bioinform. 2008 |
Bioinformatics and computational biology
cancer genomics |
0.1 | 1 | 2007 | AutoCSA, an algorithm for high throughput DNA sequence variant detection in cancer genomes · Bioinform. 2007 |
Bioinformatics and computational biology › cancer genomics › somatic mutation analysis
somatic variant detection |
0.1 | 1 | 2007 | AutoCSA, an algorithm for high throughput DNA sequence variant detection in cancer genomes · Bioinform. 2007 |
Bioinformatics and computational biology
sequence analysis |
0.1 | 2 | 2012 | BioJava: an open-source framework for bioinformatics in 2012 · Bioinform. 2012 BioJava: an open-source framework for bioinformatics · Bioinform. 2008 |
Bioinformatics and computational biology
structural bioinformatics |
0.1 | 2 | 2012 | BioJava: an open-source framework for bioinformatics in 2012 · Bioinform. 2012 BioJava: an open-source framework for bioinformatics · Bioinform. 2008 |
Bioinformatics and computational biology › statistical genetics
variant effect prediction |
0.1 | 1 | 2015 | The Ensembl REST API: Ensembl Data for Any Language · Bioinform. 2015 |
Bioinformatics and computational biology
protein structure analysis |
0.0 | 1 | 2012 | BioJava: an open-source framework for bioinformatics in 2012 · Bioinform. 2012 |
Bioinformatics and computational biology
sequence alignment |
0.0 | 1 | 2012 | BioJava: an open-source framework for bioinformatics in 2012 · Bioinform. 2012 |
Methods — techniques the papers use, named apart from their topics
statistical analysis · 0.1mutation detection algorithm · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Refget: standardized access to reference sequencesabstractMOTIVATION: Reference sequences are essential in creating a baseline of knowledge for many common bioinformatics methods, especially those using genomic sequencing. RESULTS: We have created refget, a Global Alliance for Genomics and Health API specification to access reference sequences and sub-sequences using an identifier derived from the sequence itself. We present four reference implementations across in-house and cloud infrastructure, a compliance suite and a web report used to ensure specification conformity across implementations. AVAILABILITY AND IMPLEMENTATION: The refget specification can be found at: https://w3id.org/ga4gh/refget. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Andy Yates, Jeremy Adams, Somesh Chaturvedi, Robert Davies, Matthew R. Laird, Rasko Leinonen, Rishi Nag, Nathan C. Sheffield, Oliver Hofmann 0001, Thomas M. Keane |
Bioinform. | 1 |
| 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. | 42 |
| 2018 | Eleven quick tips to build a usable REST API for life sciencesabstractIn recent years, technological advances have greatly expanded the range of data types generated by life sciences researchers. These span domains such as molecular structures, nucleotide and protein sequences, metabolomics, and chemogenomics, resulting in hundreds of public resources holding diverse data sets for reuse in multiple formats [1]. Most resources focus on a specific data type, yet their value for researchers is enhanced once cross-referenced and combined with expert annotation and knowledge. Cross-referencing has increasingly been achieved by implementing website application programming interfaces (web APIs), providing programming-language−agnostic methods to access online resources. Web APIs enable dynamic data exchange between resources, augment websites with additional data, and can provide access to large data sets. Web APIs also enhance adherence to FAIR data principles by making data Findable, Accessible, Interoperable, and Reusable [2], thus increasing the value of those resources.
Representational state transfer (REST) [3] is a popular method for providing interoperability between a client and server [4] using the hypertext transfer protocol (HTTP), the same building block as the world wide web, [5] and a common exchange format, e.g., JavaScript Object Notation (JSON) [6]. REST APIs are considered easier to develop than previous web-service standards, e.g., Simple Object Access Protocol (SOAP). However, REST specifies a set of requirements that any implementation of a REST API must address. Although well-known resources such as the World Wide Web Consortium (W3C) (https://www.w3.org) and the Internet Engineering Task Force (IETF) (https://www.ietf.org/) provide guidance on how to implement such a service, they can be difficult to understand and may have limited documentation. We present here 11 quick tips for creating and maintaining REST web APIs that were developed while implementing various web APIs (https://www.ebi.ac.uk/services) for European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI)’s data resources. Aleksandra Tarkowska, Denise Carvalho-Silva, Charles E. Cook, Edd Turner, Robert D. Finn, Andy Yates |
PLoS Comput. Biol. | 6 |
| 2015 | The Ensembl REST API: Ensembl Data for Any LanguageabstractAbstract Motivation: We present a Web service to access Ensembl data using Representational State Transfer (REST). The Ensembl REST server enables the easy retrieval of a wide range of Ensembl data by most programming languages, using standard formats such as JSON and FASTA while minimizing client work. We also introduce bindings to the popular Ensembl Variant Effect Predictor tool permitting large-scale programmatic variant analysis independent of any specific programming language. Availability and implementation: The Ensembl REST API can be accessed at http://rest.ensembl.org and source code is freely available under an Apache 2.0 license from http://github.com/Ensembl/ensembl-rest . Contact: [email protected] or [email protected] Supplementary information: Supplementary data are available at Bioinformatics online. Andy Yates, Kathryn Beal, Stephen Keenan, William M. McLaren, Miguel Pignatelli, Graham R. S. Ritchie, Magali Ruffier, Kieron R. Taylor, Alessandro Vullo, Paul Flicek |
Bioinform. | 1 |
| 2012 | BioJava: an open-source framework for bioinformatics in 2012abstractUNLABELLED: BioJava is an open-source project for processing of biological data in the Java programming language. We have recently released a new version (3.0.5), which is a major update to the code base that greatly extends its functionality. RESULTS: BioJava now consists of several independent modules that provide state-of-the-art tools for protein structure comparison, pairwise and multiple sequence alignments, working with DNA and protein sequences, analysis of amino acid properties, detection of protein modifications and prediction of disordered regions in proteins as well as parsers for common file formats using a biologically meaningful data model. AVAILABILITY: BioJava is an open-source project distributed under the Lesser GPL (LGPL). BioJava can be downloaded from the BioJava website (http://www.biojava.org). BioJava requires Java 1.6 or higher. All inquiries should be directed to the BioJava mailing lists. Details are available at http://biojava.org/wiki/BioJava:MailingLists. Andreas Prlic, Andy Yates, Spencer Bliven, Peter W. Rose, Julius O. B. Jacobsen, Peter V. Troshin, Mark Chapman, Jianjiong Gao, Chuan Hock Koh, Sylvain Foisy, Richard C. G. Holland, Gediminas Rimsa, Michael L. Heuer, Hannes Brandstätter-Müller, Philip E. Bourne, Scooter Willis |
Bioinform. | 2 |
| 2008 | BioJava: an open-source framework for bioinformaticsabstractSUMMARY: BioJava is a mature open-source project that provides a framework for processing of biological data. BioJava contains powerful analysis and statistical routines, tools for parsing common file formats and packages for manipulating sequences and 3D structures. It enables rapid bioinformatics application development in the Java programming language. AVAILABILITY: BioJava is an open-source project distributed under the Lesser GPL (LGPL). BioJava can be downloaded from the BioJava website (http://www.biojava.org). BioJava requires Java 1.5 or higher. All queries should be directed to the BioJava mailing lists. Details are available at http://biojava.org/wiki/BioJava:MailingLists. Richard C. G. Holland, Thomas A. Down, Matthew R. Pocock, Andreas Prlic, David S. Huen, Keith James, Sylvain Foisy, Andreas Dräger, Andy Yates, Michael L. Heuer, Mark J. Schreiber |
Bioinform. | 9 |
| 2007 | AutoCSA, an algorithm for high throughput DNA sequence variant detection in cancer genomesabstractUNLABELLED: The undertaking of large-scale DNA sequencing screens for somatic variants in human cancers requires accurate and rapid processing of traces for variants. Due to their often aneuploid nature and admixed normal tissue, heterozygous variants found in primary cancers are often subtle and difficult to detect. To address these issues, we have developed a mutation detection algorithm, AutoCSA, specifically optimized for the high throughput screening of cancer samples. AVAILABILITY: http://www.sanger.ac.uk/genetics/CGP/Software/AutoCSA. Ed Dicks, Jon W. Teague, Philip Stephens, Keiran Raine, Andy Yates, C. Mattocks, P. Tarpey, Adam P. Butler, Andrew Menzies, Andrew M. Jenkinson, Helen Davies, Sarah Edkins, Simon A. Forbes, Kristian A. Gray, Christopher Greenman, Rebecca Shepherd, Michael R. Stratton, P. Andrew Futreal, Richard Wooster |
Bioinform. | 5 |