Constructing Treatment Portfolios Using Affinity Propagation

A key problem of interest to biologists and medical researchers is the selection of a subset of queries or treatments that provide maximum utility for a population of targets. For example, when studying how gene deletion mutants respond to each of thousands of drugs, it is desirable to identify a small subset of genes that nearly uniquely define a drug `footprint' that provides maximum predictability about the organism's response to the drugs. As another example, when designing a cocktail of HIV genome sequences to be used as a vaccine, it is desirable to identify a small number of sequences that provide maximum immunological protection to a specified population of recipients. We refer to this task as `treatment portfolio design' and formalize it as a facility location problem. Finding a treatment portfolio is NP-hard in the size of portfolio and number of targets, but a variety of greedy algorithms can be applied. We introduce a new algorithm for treatment portfolio des...

• Type: Conference
• Year: 2008
• Where: RECOMB
• Authors: Delbert Dueck, Brendan J. Frey, Nebojsa Jojic, Vladimir Jojic, Guri Giaever, Andrew Emili, Gabe Musso, Robert Hegele
• Keywords: Computational Biology, Form Computational Analyses, Gene Deletion Mutants, RECOMB 2008, Treatment Portfolio Design