Registration is closed! Please note that you can no longer register for this seminar as the maximal number of participants has been reached.
In order to participate in the seminar you are required to attend the first meeting.
There the topics are distributed. No prior reservation is possible.
Due to the corona pandemic, the first meeting will be held via Zoom.
If you like to participate, please register via mail (teaching@bioinf.uni-sb.de).
After you received a topic, please confirm your participation in the seminar until February 17th, 2023 via mail to teaching@bioinf.uni-sb.de.
Also, you have to register officially in HISPOS until March 3rd, 2023.
| # | Paper | Authors | |
|---|---|---|---|
| 1 | Predicting correlated outcomes from molecular data | Rauschenberger and Glaab | |
| 2 | Mixed Integer Linear Programming based machine learning approach identifies regulators of telomerase in yeast | Poos et al. | |
| 3 | Off-target predictions in CRISPR-Cas9 gene editing using deep learning | Lin and Wong | |
| 4 | SEACells: Inference of transcriptional and epigenomic cellular states from single-cell genomics data | Persad et al. | |
| 5 | Anticancer drug synergy prediction in understudied tissues using transfer learning | Kim et al. | |
| 6 | Clustering Single-Cell Expression Data Using Random Forest Graphs | Pouyan et al. | |
| 7 | StackEPI: identification of cell line-specific enhancer–promoter interactions based on stacking ensemble learning | Fan and Peng | |
| 8 | GSVA: gene set variation analysis for microarray and RNA-Seq data | Hänzelmann et al. | |
| 9 | Functional random forest with applications in dose-response predictions | Rahman et al. |