====== Genome Informatics Research Seminar (2S) ======
| [[https://ekvv.uni-bielefeld.de/kvv_publ/publ/vd?id=288197063|392188]] | Stoye | Winter 2021/22 | Monday 14-16 in U10-146 |

==== Short Description ====
In this seminar, current research of the Genome Informatics group is reported. 

(In dieser Veranstaltung wird in Vorträgen über aktuelle Themen aus der Forschung der Arbeitsgruppe Genominformatik berichtet.)

==== Schedule ====
^ **Date** ^ **Topic** ^ **Name** ^
| 11.10.2021 | (no class) ||
| 18.10.2021 | Organization of the seminar | Jens S |
| 25.10.2021 | -- | -- |
| 01.11.2021 | holiday ||
| 08.11.2021 | -- | -- |
| 15.11.2021 | VeChat: Correcting errors in long reads using variation graphs | Xiao L |
| 22.11.2021 | A fully-sensitive time and space-efficient filter for finding epsilon-matches utilizing syncmers | Pina K |
| 29.11.2021 | -- | -- |
| 06.12.2021 | -- | -- |
| 13.12.2021 | -- | -- |
| 20.12.2021 | -- | -- |
| X-mas break |||
| 10.01.2022  | VarPan: variant calling on colored and compacted de Bruijn graphs | Mario M |
| 17.01.2022 | PathOGenes – a graph database approach | Johannes Sch |
| 24.01.2022 | From the breakpoint towards the DCJ double distance | Marília DVB |
| 31.01.2022 | -- | -- |
| 07.02.2022 | Something with Genome Halving | Leonard B |
| **23.02.2022, 10 c.t.** | OpenModelica: Pseudo-Array Causalization in the New Backend (abstract below) | Karim A |

Missing: Jens S, Tizian S, Roland W, Michael B, Diego R, Luca P

====Abstracts====

===OpenModelica: Pseudo-Array Causalization in the New Backend===
**Karim Abdelhak**, 23.02.2022, 10h15, U10-146

Work on the new backend continued to support unscalarized arrays of variables and equations. The base strategy consists of solving the matching problem on a scalarized adjacency matrix and recovering the array structure afterwards. While the matching algorithm itself still depends on the number of scalar equations, the rest of the backend, and especially code generation, is handled more efficiently.

The algorithm for Pseudo-Array Causalization leads to a faster compilation time of array structures ranging from 10 to 100 times faster, while maintaining or slightly improving simulation time.