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Multiple criteria optimization joint analyses of microarray experiments in lung cancer: from existing microarray data to new knowledge.

Camacho-Cáceres KI, Acevedo-Díaz JC, Pérez-Marty LM, Ortiz M, Irizarry J, Cabrera-Ríos M, Isaza CE - Cancer Med (2015)

Bottom Line: These data, however, are stored and often times abandoned when new experimental technologies arrive.This work reexamines lung cancer microarray data with a novel multiple criteria optimization-based strategy aiming to detect highly differentially expressed genes.In the analysis, groups of samples from patients with distinct smoking habits (never smoker, current smoker) and different gender are contrasted to elicit sets of highly differentially expressed genes, several of which are already associated to lung cancer and other types of cancer.

View Article: PubMed Central - PubMed

Affiliation: Bio IE Lab, The Applied Optimization Group, Industrial Engineering Department, University of Puerto Rico, Mayaguez, Puerto Rico.

No MeSH data available.


Related in: MedlinePlus

Diagram representing six analyses between four different conditions (HNS, HCS, CNS, CCS). The edges of the graph list the genes in the associated Pareto‐efficient frontier.
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cam4540-fig-0008: Diagram representing six analyses between four different conditions (HNS, HCS, CNS, CCS). The edges of the graph list the genes in the associated Pareto‐efficient frontier.

Mentions: Figure 8 shows a summary of the six analyses between never smoker versus current smoker in cancer and control tissues. The circles on the left side represent the controls never smoker (HNS) and controls current smoker (HCS) tissues, while the circles on the right hand side represent the cancer never smoker (CNS) and cancer current smoker (CCS) tissues. Additionally, the upper circles represent never smoker tissues, whereas the lower circles symbolize current smoker tissues.


Multiple criteria optimization joint analyses of microarray experiments in lung cancer: from existing microarray data to new knowledge.

Camacho-Cáceres KI, Acevedo-Díaz JC, Pérez-Marty LM, Ortiz M, Irizarry J, Cabrera-Ríos M, Isaza CE - Cancer Med (2015)

Diagram representing six analyses between four different conditions (HNS, HCS, CNS, CCS). The edges of the graph list the genes in the associated Pareto‐efficient frontier.
© Copyright Policy - creativeCommonsBy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4940807&req=5

cam4540-fig-0008: Diagram representing six analyses between four different conditions (HNS, HCS, CNS, CCS). The edges of the graph list the genes in the associated Pareto‐efficient frontier.
Mentions: Figure 8 shows a summary of the six analyses between never smoker versus current smoker in cancer and control tissues. The circles on the left side represent the controls never smoker (HNS) and controls current smoker (HCS) tissues, while the circles on the right hand side represent the cancer never smoker (CNS) and cancer current smoker (CCS) tissues. Additionally, the upper circles represent never smoker tissues, whereas the lower circles symbolize current smoker tissues.

Bottom Line: These data, however, are stored and often times abandoned when new experimental technologies arrive.This work reexamines lung cancer microarray data with a novel multiple criteria optimization-based strategy aiming to detect highly differentially expressed genes.In the analysis, groups of samples from patients with distinct smoking habits (never smoker, current smoker) and different gender are contrasted to elicit sets of highly differentially expressed genes, several of which are already associated to lung cancer and other types of cancer.

View Article: PubMed Central - PubMed

Affiliation: Bio IE Lab, The Applied Optimization Group, Industrial Engineering Department, University of Puerto Rico, Mayaguez, Puerto Rico.

No MeSH data available.


Related in: MedlinePlus