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| + | == Handling Data cascades == | ||
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| + | The recent explosition of data science and artificial intelligence relies on one critical capability: being able to gather, clean, analyse and render the data on which the algorithms rely. | ||
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| + | BICS offers a whole support of material, software, data and methodology resources to support the handling of data cascade in the domains of medical, biological, industrial and educational domains. | ||
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| + | The BICS data Seminar 2019 provides the overview of the state of the art for data handling cascade. | ||
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==The program== | ==The program== | ||
Version actuelle datée du 9 juillet 2019 à 10:44
Handling Data cascades
The recent explosition of data science and artificial intelligence relies on one critical capability: being able to gather, clean, analyse and render the data on which the algorithms rely.
BICS offers a whole support of material, software, data and methodology resources to support the handling of data cascade in the domains of medical, biological, industrial and educational domains.
The BICS data Seminar 2019 provides the overview of the state of the art for data handling cascade.
The program
Welcome to our speakers:
| Time | Author | Title |
|---|---|---|
| 9:30 | Pierre Parrend | Handling data cascade |
| 9:45 | Arnaud Kress | BICS Infrastructure |
| 10:00 | Laetitia Poidevin | Omics databases |
| 10:15 | Luc Moulinier | Protein fold recognition |
| 10:30 | Kirsley Chennen | Data FAIRification |
| 10:45 | Thomas Weber | Variants |
| 11:30 | Nicolas Scalzitti | Genome annotation |
| 11:45 | Anne Jeannin | Data for deep learning |
| 12:00 | Pierre Parrend | Handling industrial data |
| 12:30 | The End |