Date: Saturday September 3, 2016
Time: 9:00 – 17:00
Venue: World Forum, room: Europe 2
Background
Mammalian systems constitute over 200 cell types, each specialized to perform a distinct function, and yet all cell types share the same genome. This cell type specificity is achieved by a context-specific interpretation of the DNA sequence to produce a cell type specific transcription signature. Advances in sequencing techniques have accelerated the characterization of transcription landscapes across many normal and malignant cell types. The challenge now is to integrate these data to understand transcriptional control at a systems level. Over the years, powerful machine learning algorithms have been developed for inferring transcriptional networks from expression data, thereby revealing new aspects of complex biological systems.
Aims and scope
This one day SIG session will bring together experts from computational biology and machine learning to present recent advances in the development and application of gene regulatory network inference methods, as well as novel emerging single-cell and epigenomics data types suitable for network inference. The SIG will be split into two half day sessions. The first half will focus entirely on novel network inference methods, while the second half will focus on opportunities and challenges arising from new data types. Each session will feature an invited speaker and three short talks.
Prof. Sushmita Roy, University of Wisconsin-Madison. Website
Prof. Klaas Vandepoele, Ghent University. Website
The target audience is researchers working in the field of network inference or anyone who is working with large scale genome wide data. We expect typically 20 participants.
| time | speaker – title |
|---|---|
| 09.00 – 09.10 | Welcome (Tom Michoel) |
| Morning session | New Methods (Chair: Eric Bonnet) |
| 9.10 – 10.10 | Keynote talk 1: Prof. Sushmita Roy (University of Wisconsin-Madison) |
| 10.10 – 10.40 | Talk 1: Van Anh Huynh-Thu (University of Liege). Combining tree-based and dynamical systems for the inference of gene regulatory networks. |
| 10.40 – 11.10 | Tea/Coffee break |
| 11.10 – 11.40 | Talk 2: Dragan Bosnacki (Eindhoven University of Technology). REGENT: Logarithms, Hubs and Thresholded Transitive Reduction for Enhanced Scalable Network Inference |
| 11.40 – 12.10 | Talk 3: Lingfei Wang (University of Edinburgh). Findr: Fast and accurate causal inference of genetic regulations. |
| 12.10 – 12.40 | Talk 4: Hervé Isambert (Institut Curie). 3off2: A network reconstruction algorithm based on 2-point and 3-point information statistics |
| 12.40 – 13.40 | Lunch break |
| Afternoon session | New Data (Chair: Anagha Joshi) |
| 13.40 – 14.40 | Keynote talk 2: Prof. Klaas Vandepoele (Ghent University). |
| 14.40 – 15.10 | Talk 5: Judith Schutte (Essen University Hospital). An experimentally validated network of nine haematopoietic transcription factors reveals mechanisms of cell state stability. |
| 15.10 – 15.40 | Coffee/tea |
| 15.40 – 16.10 | Talk 6: Anthony Mathelier (University of Oslo). Getting new data from old data: extracting information from TF ChIP-seq data sets. |
| 16.10 – 16.40 | Talk 7: Anil Korkut (Memorial Sloan Kettering Cancer Center). Perturbation biology: Inferring signaling networks in cellular systems. |
| 16.40 – 17.00 | Talk 8: Leelavati Narlikar (National Chemical Laboratory, India). No data left behind: Identifying diversity in transcriptional regulation from high-throughput sequencing experiments. |
| 17.00 – 17.10 | Concluding remarks and follow-up plans. |