Microarray experiments are a powerful method for the analysis of gene expression levels at a systems scale. Microarray techniques can illuminate how gene expression is modified under pathological or stressful conditions, and provide insight into the molecular mechanisms of disease. However, intra-gene spot-to-spot variability in some microarray experiments is much larger than one would expect from stability considerations, implying that a better understanding of the kinetics of nucleic acid hybridization is necessary in order to better interpret experimental results and to improve microarray design. Microarrays enable researchers to quickly obtain quantitative data for the simultaneous expression levels of thousands of genes. However, the determination of the significance of such data vis-a-vis the vast amounts of scientific information available on genes, gene products, tissues, cells and organisms, requires the application of statistical techniques. Thanks to the interest in these problems and the concerted effort of many researchers, several different techniques for data analysis are nowadays available. However, available methods often disregard the inherent uncertainties in the data and their effect on the estimation of cross correlations among expression levels of different genes. In view of these challenges, the main goals of the proposed research are: (i) to obtain a fundamental understanding of DNA hybridization in microarrays, and (ii) to develop algorithms that are able to distinguish true correlations between changes in expression levels of genes from spurious correlations that appear due to noise. To achieve the first goal, we will develop a new meso-scale model for DNA hybridization in microarrays. To achieve the second goal, we will generalize random matrix theory methods to the study of cross-correlations among changes in expression levels for different genes. An improved understanding of these questions will lead to the development of more accurate tools for the study of information exchange within gene regulation networks, enabling one to better predict the effect of perturbations to the state of a cell. Our goals also hold the potential to lead to a deeper understanding of the mechanisms that control multi-cellular development and to shed light on pathological cellular events, including the onset and progression of human disease. Moreover, our research will help to better assess the effect of drugs on patients undergoing disease progression, and ease the process of distinguishing normal, carrier and disease genotypes beforehand.
| Stringer, Michael J; Sales-Pardo, Marta; Nunes Amaral, Luís A (2010) Statistical validation of a global model for the distribution of the ultimate number of citations accrued by papers published in a scientific journal. J Am Soc Inf Sci Technol 61:1377-1385 |
| Amaral, Luis A Nunes (2008) A truer measure of our ignorance. Proc Natl Acad Sci U S A 105:6795-6 |
| Sales-Pardo, Marta; Guimera, Roger; Moreira, Andre A et al. (2007) Extracting the hierarchical organization of complex systems. Proc Natl Acad Sci U S A 104:15224-9 |
| Camacho, J; Stouffer, D B; Amaral, L A N (2007) Quantitative analysis of the local structure of food webs. J Theor Biol 246:260-8 |
| Guimera, R; Sales-Pardo, M; Amaral, L A N (2007) A network-based method for target selection in metabolic networks. Bioinformatics 23:1616-22 |
| Guimera, Roger; Sales-Pardo, Marta; Amaral, Luis A N (2007) Classes of complex networks defined by role-to-role connectivity profiles. Nat Phys 3:63-69 |
| Guimera, Roger; Sales-Pardo, Marta; Amaral, Luis A Nunes (2007) Module identification in bipartite and directed networks. Phys Rev E Stat Nonlin Soft Matter Phys 76:036102 |
| Stouffer, Daniel B; Camacho, Juan; Jiang, Wenxin et al. (2007) Evidence for the existence of a robust pattern of prey selection in food webs. Proc Biol Sci 274:1931-40 |
| Sales-Pardo, Marta; Chan, Albert O B; Amaral, Luis A N et al. (2007) Evolution of protein families: is it possible to distinguish between domains of life? Gene 402:81-93 |
| Stouffer, Daniel B; Camacho, Juan; Amaral, Luis A Nunes (2006) A robust measure of food web intervality. Proc Natl Acad Sci U S A 103:19015-20 |
Showing the most recent 10 out of 21 publications
