Evaluating Validation Techniques for Biological Network Alignment.
Fried, Inbar.
2015
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Abstract:
Cross-species biological network alignments are powerful tools for knowledge discovery
and have been a major focus in the field of computational biology. Many alignment
algorithms have been published in recent years, along with validation techniques to
quantify the success of an alignment. In this work we show that existing validation
techniques are not always suitable metrics to ... read moreassess an alignment's performance. We
evaluate the validation techniques using a collection of network perturbation tests, and
extend our analyses to several cross-species alignments. This thesis begins by
introducing the field of biological network alignment, including the protein protein
interaction (PPI) networks, existing alignment algorithms, and existing validation
techniques. The focus then shifts towards a description of the experiments performed in
this work, followed by an analysis of the results that reveals the inadequacies of
existing validation techniques.
Thesis (M.S.)--Tufts University, 2015.
Submitted to the Dept. of Computer Science.
Advisor: Benjamin Hescott.
Committee: Donna Slonim, and Mark Crovella.
Keyword: Computer science.read less - ID:
- 3197xz332
- Component ID:
- tufts:21419
- To Cite:
- DCA Citation Guide EndNote
