Name
Abstract | ||
|---|---|---|
Motivation The volume and complexity of biological data increases rapidly. Many clinical professionals and biomedical researchers without a bioinformatics background are generating big '-omics' data, but do not always have the tools to manage, process or publicly share these data. Results Here we present MOLGENIS Research, an open-source web-application to collect, manage, analyze, visualize and share large and complex biomedical datasets, without the need for advanced bioinformatics skills. Availability and implementation MOLGENIS Research is freely available (open source software). It can be installed from source code (see http://github.com/molgenis), downloaded as a precompiled WAR file (for your own server), setup inside a Docker container (see http://molgenis.github.io), or requested as a Software-as-a-Service subscription. For a public demo instance and complete installation instructions see http://molgenis.org/research. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1093/bioinformatics/bty742 | BIOINFORMATICS |
Field | DocType | Volume |
Biological data,Data set,Source code,Computer science,Software,Bioinformatics,Open source software | Journal | 35 |
Issue | ISSN | Citations |
6 | 1367-4803 | 0 |
PageRank | References | Authors |
0.34 | 7 | 19 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| K. Joeri van der Velde | 1 | 79 | 6.58 |
| Floris Imhann | 2 | 0 | 0.34 |
| Bart Charbon | 3 | 9 | 1.72 |
| Chao Pang | 4 | 143 | 19.04 |
| David van Enckevort | 5 | 5 | 2.90 |
| Mariska Slofstra | 6 | 0 | 0.34 |
| Ruggero Barbieri | 7 | 0 | 0.34 |
| Rudi Alberts | 8 | 31 | 3.53 |
| Dennis Hendriksen | 9 | 16 | 2.41 |
| Fleur Kelpin | 10 | 9 | 1.72 |
| Mark de Haan | 11 | 9 | 2.06 |
| Tommy de Boer | 12 | 9 | 1.72 |
| Sido Haakma | 13 | 0 | 0.34 |
| Connor Stroomberg | 14 | 0 | 0.34 |
| Salome Scholtens | 15 | 0 | 0.34 |
| Gert-Jan van de Geijn | 16 | 0 | 0.34 |
| Eleonora A M Festen | 17 | 0 | 0.34 |
| Rinse K Weersma | 18 | 0 | 0.34 |
| Morris A Swertz | 19 | 155 | 18.03 |