SHREC19: Protein Shape Retrieval Contest
- 1. Laboratoire GBCM, EA7528, Conservatoire National des Arts-et-Metiers, 2 rue Conte, 75003 Paris, France
- 2. Visual Computing Lab (VCL) team, Information Technologies Institute, Centre for Research and Technology Hellas, Greece
- 3. ISEN-Lille, Yncre ́a, Hauts de France
- 4. Department of Computer Science, Universita` di Verona, Strada le Grazie 15, 37134 Verona
- 5. Department of Biological Sciences, Purdue University, West Lafayette, Indiana, USA
- 6. Universite Haute-Alsace, IRIMAS EA 7499, F-68100 Mulhouse
- 7. Department of Biological Sciences, Purdue University, West Lafayette, Indiana, USA; Department of Computer Science, Purdue University, West Lafayette, Indiana, USA
- 8. Department of Computer Science, Purdue University, West Lafayette, Indiana, USA
- 9. Complex Systems Division, Beijing Computational Science Research Center, Beijing, China 100193
- 10. Complex Systems Division, Beijing Computational Science Research Center, Beijing, China 100193; School of Software Engineering, University of Science and Technology China, Suzhou, Jiangsu, China 215123
Description
This track aimed at retrieving protein evolutionary classification based on their surfaces meshes only. Given that proteins are dynamic, non-rigid objects and that evolution tends to conserve patterns related to their activity and function, this track offers a challenging issue using biologically relevant molecules. We evaluated the performance of 5 different algorithms and analyzed their ability, over a dataset of 5,298 objects, to retrieve various conformations of identical proteins and various conformations of ortholog proteins (proteins from different organisms and showing the same activity). All methods were able to retrieve a member of the same class as the query in at least 94% of the cases when considering the first match, but show more divergent when more matches were considered. Last, similarity metrics trained on databases dedicated to proteins improved the results.
Files
Langenfeld_3DOR2019.pdf
Files
(249.6 kB)
| Name | Size | Download all |
|---|---|---|
|
md5:ba5fa399a78547eff953eca40ae92cb4
|
249.6 kB | Preview Download |