Camacho Cáceres, Katia I.

Profile Picture

Filters

20141
Reset filters

Settings

Citations

Publication Search Results

Now showing 1 - 1 of 1
  • Thumbnail Image
    Publication
    Optimization-driven meta-analysis: The simultaneous search for cancer biomarkers with multiple microarray experiments
    (2014) Camacho Cáceres, Katia I.; Cabrera Ríos, Mauricio; College of Engineering; Dávila, Saylisse; Seguel, Jaime; Department of Industrial Engineering; Torres, Pedro
    In bioinformatics, it is possible to generate experimental data at a high pace. For example, microarrays can provide large amounts of data for genetic relative expression in illnesses of interest such as cancer. These data are stored and often times abandoned when new experimental technologies arrive. This work, re-examines lung cancer microarray data with a multiple criteria optimization-based strategy developed in our research group. This strategy does not require any adjustment of parameters by the user and is capable to converge consistently to important genes –potential biomarkers- even in the presence of multiple and incommensurate units across microarrays. In this thesis, three different cases were approached with the proposed method: lung cancer and leukemia, each using microarrays, and breast cancer with microRNA. The lists of resulting genes in the first two cases are provided with a discussion of their role in cancer, as well as the possible research directions for each of them. A list of microRNA sequences is also provided in the third case, emphasizing that this last case is to demonstrate the transferability of analysis ideas to other high throughput biological experiments. It is also recognized at this point that experimental validation is necessary to confirm the role of genes for which not enough evidence was found in the literature. Fundamentally, these genes with little reported information represent the best opportunities for biological discovery from existing data.