A Method for Visualizing Similarity in Gene Expression Datasets
We made significant progress in developing a method of mapping large datasets onto a two dimensional surface where every point corresponds to an Iterated Function Systems (IFS). These IFS can be used to generate an long sequence of scalable arbitrary numbers. There is a correspondence between the similarity of these sequences and their location on the surface of the map. The values contained in these generated sequences is compared against sequential values of target datasets. A point that corresponds to the "best fit" to each target dataset is then located. One can quantify the relationship between similarities of target datasets and the location and geometry of their corresponding points on such a map with a view to optimizing the technique for visualizing relative similarity (or difference) between large sets of gene expression data. Sandy Shaw leveraged the progress made into a new company, Fractal Genomics.
Key Personnel: Sandy Shaw
Collaborator: Jenny Harrison (Math UCB).
The premise of the agent paradigm, its related theory and methodologies together with advances in multilevel modeling of complex systems of interactions opened new frontiers for advancing the physical, natural, social, military, and information sciences and engineering...