Presentation Transcript

1. RECOMB/ISCB 2013Conference on Regulatory and Systems Genomics, with DREAM ChallengesConference Sharing

   Presenter: Yip Kit Sang Danny Date and Venue: 28th Nov, 2013 at SHB1027
2. Agenda Introduction on the conference DREAM8 challenges Insights from conference on System Biology and Regulatory Genomics Trip in Toronto RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
3. Conference information Name of conference: RECOMB/ISCB 2013 Date of conference: 8 – 12 Nov, 2013 Place of conference The Bram & BlumaAppel Salon, Toronto Reference Library, Toronto, Ontario, Canada Areas of the conference DREAM8 reverse engineering challenges System Biology Regulatory Genomics Statistics of the conference DREAM8: > 350 teams, > 1000 models Papers, abstract: nearly 190 submissions RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
4. Getting Toronto from Hong Kong Hong Kong International Airport About 15 hours on direct flight Toronto Pearson International Airport About 1 hour on shuttle bus Toronto Downtown (Eaton Chelsea, Grand Hotel, Toronto Reference Library) RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
5. Toronto Reference Library RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
6. Conference Agenda
7. Conference Agenda RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
8. The Bram & BlumaAppel Salon Seats Stage Tea breaks Posters RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
9. The Bram & BlumaAppel Salon Seats Stage Tea breaks Posters RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
10. DREAM8 Challenge 1 Descriptions HPN-DREAM Breast Cancer Network Inference Challenge Build network models that represent the active cell signaling pathways in breast cancer (139), Predict the dynamic response of various phospho-proteins to drug perturbations (25), Propose novel strategies to visualize these high dimensional data (14) RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
11. DREAM8 Challenge 1 Results and Discussions Winner! Some used prior knowledge to construct the network, and used the data to test the network Some constructed and tested the network with the given data Which one is better? Or which one is the winner? One team (6 members) tried 6 different models RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
12. DREAM8 Challenge 2 Descriptions NIEHS-NCATS-UNC DREAM Toxicogenetics Challenge Develop predictive models of cytotoxicity using genetic and genomic data to predict individual responses to compound exposure (99/42) Use chemical attributes to predict population-based cytotoxicity characteristics (median, variance) for a set of compounds. 232 participants registered for the Challenge (83/24) RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
13. DREAM8 Challenge 2 Results and Discussions Strategies of winning teams Identify a novel feature, chemical structure clusters, clustering based on the chemical structure of the compound (k-means, RF) Criticisms It is very strange that all chemical attributes, expression data, genotypes information cannot help with the predictions, tested with many different algorithms (Correlation, clustering, SVM, k-NN, …etc) It seems that the winning teams are predicting where the experiments were carried out, instead of predicting if the compounds is toxic RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
14. DREAM8 Challenge 3 Descriptions The Whole-Cell Parameter Estimation DREAM Challenge Estimating the model parameters for specific biological processes from simulated data, provided with a whole cell model of Mycoplasma genitalium (700/9) RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
15. DREAM8 Challenge 3Results and Discussions Testing: Mathlab executable program with time and space limits, unlimited trials Closest parameters estimation: Maximum likelihood with bootstrap Closest prediction value: RF with PCA for dimensionality reduction Why did the one giving closet parameter estimation (total error < 1e-10) miss the closest prediction value? RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
16. Conference on Systems Biology and Regulatory Genomics 2 days for each conference 3 – 4 keynote speakers (30 min each) 13 – 14 oral presentations (15 min each) 2 coffee breaks with poster presentations (less than 25 min each) A lunch session with poster presentations (less than 1 hour 15 min) RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
17. Insight 1: Causality Time A B A B A C Expression level C A D D A E E A F C F F A C G Different rates of transcription RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
18. Insight 1: Causality A direct graph represents causes and effects The source, sink, hub, patterns, … of the graph Dynamics of network RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
19. Insight 2: Network Reconstruction Correlation, partial correlation Mutual information Bayesian network with Gaussian modelling Chi-square regression, logistics regression LASSO, prior LASSO Different parameters estimations (e.g. ODE) … etc RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
20. Insight 3: Pattern Enumeration A B B B A C A C A B D C A B A B A B D C D C D C Self-looping: Self-looping (3 nodes): Feed-forward loop: Self-looping (4 nodes): Feed-forward loop (4 nodes): Clique (4 nodes) … etc More importantly, the hierarchy of modules RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
21. Insight 4: Combination of Tests(Robustness of Testing) Expression data 6 different reconstruction algorithms Gene network 144 experiments already More variations: Different cell types Different diseases Directed or undirected Different annotations … etc 8 different patterns Patterns discovery 3 different analyses Functional enrichment analysis RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
22. Insight 5: Old Methods, New Data Sequence assembly of a new species, comparisons between some existing species, reasons for similarities and differences Novelties: new discoveries, experiments, literature review, annotation databases RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
23. Sidetrack 1: Targets Calling Use validated targets with predictions from one famous algorithm Prediction algorithm relies on experiment data I think this approach is lazy, but it reduces the complexity of the problem and it is generally accepted by the reviewers RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
24. Sidetrack 2: Presentation of Graph/Tree with heatmap RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
25. Sidetrack 3: Most seen Algorithms in Data Analysis in the conference Random forest Logistics regression Maximum likelihood Hidden Markov model Support vector machine k-nearest neighbour Hierarchical clustering k-means clustering Genetic algorithm Matrix factorization … etc RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
26. Toronto Map Eaton Centre Toronto Reference Library Dundas Square CN Tower RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
27. Toronto Map Royal Ontario Museum University of Toronto China Town University of Toronto University of Toronto RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
28. Niagara Falls (Three Perspectives) RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
29. Video for Niagara Falls Bio_RM_20131128_Niagara.mp4 RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
30. Toronto Zoo RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013
31. Toronto Zoo (Canadian Animals) RECOMB/ISCB 2013 | Conference Sharing | Danny Yip | 28th Nov, 2013