netbiosig2013-talk tijana milenkovic
DESCRIPTION
Presentation for Network Biology SIG 2013 by Tijana Milenkovic, University of Notre Dame, USA. “What Can Biological Networks Tell Us About Aging?”TRANSCRIPT
Computer Science and EngineeringUniversity of Notre Dame
What can biological networks tell us about aging?
Fazle E. Faisal, Han Zhao, and Tijana Milenković
Current knowledge about human aging
• Human aging - hard to study experimentally– Long lifespan– Ethical constraints
• Hence– Sequence-based knowledge transfer from model species– Differential gene expression
• I.e., current “ground truth” - computational predictions• But
– Not all genes in model species have human orthologs– Plus, genes’ “connectivities” typically ignored
• But, genes, i.e., their protein products, carry out biological processes by interacting with each other
• And this is exactly what biological networks model!– E.g., protein-protein interaction (PPI) networks
Biological networks
Key idea 1
Use network alignment to transfer aging-related knowledge from model species to human
Current network-based research of aging
• Relies on static network representations
• Plus, it relies on primitive measures of topology
• Plus, different biological data types capture different functional slices of the cell
Key idea 2
Data integration: form dynamic age-specific networks
Then, measure change of proteins’ network positions with age•Many centrality measures
This work appears in …
• T. Milenković, Han Zhao, and F.E. Faisal, “Global Network Alignment In The Context Of Aging”, in Proceedings of ACM-BCB 2013, to appear.
• F.E. Faisal and T. Milenković, “Dynamic networks reveal key players in aging”, arXiv:1307.3388 [cs.CE], 2013. Also, under revision.
• Map “similar” nodes between different networks in a way that conserves edges
Global network alignment in the context of aging
• Pairwise (two networks at a time)• Multiple (more than two networks at a time)
Global network alignment in the context of aging
Global network alignment in the context of aging
• Network alignment: 2-step approach– Node cost function– Alignment strategy
• Different methods use both different cost functions and alignment strategies
• Hence, unfair method evaluation
Global network alignment in the context of aging
• Our goal: mix and match node cost functions and alignment strategies of state-of-the-art methods
• Fair evaluation• New superior method?• Application to aging
Global network alignment in the context of aging
• MI-GRAAL (pairwise aligner)• IsoRankN (multiple aligner)• Total of 8 mix-and-match aligners
Global network alignment in the context of aging
• Align PPI networks of:– Yeast– Fruitfly– Worm– Human
• Evaluate:– All 8 aligners according to all measures from MI-GRAAL
and IsoRankN papers, and many others
• Compare:– Different cost functions under same alignment strategy– Different alignment strategies under same cost
Global network alignment in the context of aging
• Different cost functions under same align. strategy– MI-GRAAL’s cost function is always superior
Global network alignment in the context of aging
• Different align. strategies under same cost function– N/A: the two strategies are very different
Global network alignment in the context of aging
• Compare aligners in the context of aging– Predict aging-related genes from “statistically
significant” alignments– Measure prediction accuracy
• MI-GRAAL’s cost function is again superior
• Now, we can compare different alignment strategies under same cost function– Yet, caution!
Global network alignment in the context of aging
• Different align. strategies under same cost function– MI-GRAAL: higher recall– IsoRankN: higher precision
Hence, new superior multiple network aligner!
Dynamic networks reveal key players in aging
• Relationships between different network centralities
Complex Networks (CoNe) Lab
Acknowledgements
• NSF CCF-1319469 ($445K)• NSF EAGER CCF-1243295 ($207K)• NIH R01 Supplement 3R01GM074807-07S1
($248K)• Google Award ($33K)
• ISMB/ECCB Posters – O040 – O052 – O072
(O: Systems Biology & Networks)[email protected]