Demo Data from VLDB 2026 / reviewers in the wild / expert
Colin W. Combe
dblp:209/7586
· DBLP profile ↗
3ranked-venue papers
1as first author
0since 2021 · last 2018
0000-0003-2526-2587ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 3 · 1 first-author
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
1 paper |
Bioinformatics and computational biology · 100% | |
| Computer graphics and multimedia
1 paper |
Visualization and visual analytics · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › structural bioinformatics
molecular complex visualization |
0.3 | 1 | 2017 | ComplexViewer: visualization of curated macromolecular complexes · Bioinform. 2017 |
Bioinformatics and computational biology
structural bioinformatics |
0.3 | 1 | 2017 | ComplexViewer: visualization of curated macromolecular complexes · Bioinform. 2017 |
Visualization and visual analytics › biological data visualization
biological network visualization |
0.1 | 1 | 2017 | ComplexViewer: visualization of curated macromolecular complexes · Bioinform. 2017 |
Methods — techniques the papers use, named apart from their topics
scalable vector graphics · 0.6d3.js · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | Encompassing new use cases - level 3.0 of the HUPO-PSI format for molecular interactionsabstractBACKGROUND: Systems biologists study interaction data to understand the behaviour of whole cell systems, and their environment, at a molecular level. In order to effectively achieve this goal, it is critical that researchers have high quality interaction datasets available to them, in a standard data format, and also a suite of tools with which to analyse such data and form experimentally testable hypotheses from them. The PSI-MI XML standard interchange format was initially published in 2004, and expanded in 2007 to enable the download and interchange of molecular interaction data. PSI-XML2.5 was designed to describe experimental data and to date has fulfilled this basic requirement. However, new use cases have arisen that the format cannot properly accommodate. These include data abstracted from more than one publication such as allosteric/cooperative interactions and protein complexes, dynamic interactions and the need to link kinetic and affinity data to specific mutational changes. RESULTS: The Molecular Interaction workgroup of the HUPO-PSI has extended the existing, well-used XML interchange format for molecular interaction data to meet new use cases and enable the capture of new data types, following extensive community consultation. PSI-MI XML3.0 expands the capabilities of the format beyond simple experimental data, with a concomitant update of the tool suite which serves this format. The format has been implemented by key data producers such as the International Molecular Exchange (IMEx) Consortium of protein interaction databases and the Complex Portal. CONCLUSIONS: PSI-MI XML3.0 has been developed by the data producers, data users, tool developers and database providers who constitute the PSI-MI workgroup. This group now actively supports PSI-MI XML2.5 as the main interchange format for experimental data, PSI-MI XML3.0 which additionally handles more complex data types, and the simpler, tab-delimited MITAB2.5, 2.6 and 2.7 for rapid parsing and download. M. Sivade Dumousseau, Diego Alonso-López, Mais G. Ammari, Glyn Bradley, Nancy H. Campbell, Arnaud Céol, Gianni Cesareni, Colin W. Combe, Javier De Las Rivas, Noemi del-Toro, Joshua Heimbach, Henning Hermjakob, Igor Jurisica, Luana Licata, Ruth C. Lovering, David J. Lynn, Birgit Meldal, Gos Micklem, Simona Panni, Pablo Porras, Sylvie Ricard-Blum, Bernd Roechert, Lukasz Salwínski, Anjali Shrivastava, Julie M. Sullivan, Nicolas Thierry-Mieg, Yo Yehudi, Kim Van Roey, Sandra E. Orchard |
BMC Bioinform. | 8 |
| 2018 | JAMI: a Java library for molecular interactions and data interoperabilityabstractBACKGROUND: A number of different molecular interactions data download formats now exist, designed to allow access to these valuable data by diverse user groups. These formats include the PSI-XML and MITAB standard interchange formats developed by Molecular Interaction workgroup of the HUPO-PSI in addition to other, use-specific downloads produced by other resources. The onus is currently on the user to ensure that a piece of software is capable of read/writing all necessary versions of each format. This problem may increase, as data providers strive to meet ever more sophisticated user demands and data types. RESULTS: A collaboration between EMBL-EBI and the University of Cambridge has produced JAMI, a single library to unify standard molecular interaction data formats such as PSI-MI XML and PSI-MITAB. The JAMI free, open-source library enables the development of molecular interaction computational tools and pipelines without the need to produce different versions of software to read different versions of the data formats. CONCLUSION: Software and tools developed on top of the JAMI framework are able to integrate and support both PSI-MI XML and PSI-MITAB. The use of JAMI avoids the requirement to chain conversions between formats in order to reach a desired output format and prevents code and unit test duplication as the code becomes more modular. JAMI's model interfaces are abstracted from the underlying format, hiding the complexity and requirements of each data format from developers using JAMI as a library. M. Sivade Dumousseau, Anjali Shrivastava, Diego Alonso-López, Javier De Las Rivas, Noemi del-Toro, Colin W. Combe, Birgit Meldal, Joshua Heimbach, Juri Rappsilber, Julie M. Sullivan, Yo Yehudi, Sandra E. Orchard |
BMC Bioinform. | 7 |
| 2017 | ComplexViewer: visualization of curated macromolecular complexesabstractSUMMARY: Proteins frequently function as parts of complexes, assemblages of multiple proteins and other biomolecules, yet network visualizations usually only show proteins as parts of binary interactions. ComplexViewer visualizes interactions with more than two participants and thereby avoids the need to first expand these into multiple binary interactions. Furthermore, if binding regions between molecules are known then these can be displayed in the context of the larger complex. AVAILABILITY AND IMPLEMENTATION: freely available under Apache version 2 license; EMBL-EBI Complex Portal: http://www.ebi.ac.uk/complexportal; Source code: https://github.com/MICommunity/ComplexViewer; Package: https://www.npmjs.com/package/complexviewer; http://biojs.io/d/complexviewer. Language: JavaScript; Web technology: Scalable Vector Graphics; Libraries: D3.js. CONTACT: [email protected] or [email protected]. Colin W. Combe, Marine Sivade, Henning Hermjakob, Joshua Heimbach, Birgit Meldal, Gos Micklem, Sandra E. Orchard, Juri Rappsilber |
Bioinform. | 1 |