1) Integrative approach to modeling cellular signaling pathways

It has been noted by Vogelstein, Lane and Levine [Nature 408, 307-310 (2000)] that "…cellular signaling pathways […] cannot be understood by looking at isolated components. Instead it is essential to consider the tangled networks into which these signaling components are integrated." Characterizing these tangled networks is a truly challenging task. Indeed, microarray techniques can illuminate how gene expression is modified under pathological or stressful conditions, and provide
insight into the molecular mechanisms of a disease. However, the physiological function of a gene identified by sequencing is often unknown, and determining the function of these newly sequenced genes is a daunting task due to their large number and to their involvement in multiple regulatory systems. Moreover, the individual genes are not expressed independently but are instead coupled in an often unknown fashion. Because of this coupling, activation or suppression of a given gene leads to a cascade of changes in the expression levels of a number of other genes. Further, many of the interactions occurring in the cell are entirely at the post-transcriptional level--which can cause significant discrepancies between protein and mRNA levels. Moreover, a recent study by Superti-Fuga and co-workers [Nature 415, 141-147 (2002)] demonstrated that proteins are typically involved in cells processes not in isolated form but as protein complexes, suggesting that the structure of the network may change over time as new nodes--the complexes--are created and destroyed.
The complexity of the tangled web of nonlinear interactions between genes, proteins and the environment necessitates the development of simplified models to illuminate biological function. A promising approach is the study of gene interaction as a network model. Indeed Vogelstein, Lane and Levine hypothesize that "[o]ne way to understand the p53 network is to compare it to the Internet."
The goal of my research in this area is to develop "global" models for cellular signaling pathways that will take into consideration time-dependent and spatial-localization aspects of some components of the network. The development of these models will enable a more rational design and interpretation of experimental work and permit novel approaches to treatment. To tackle the challenges of modeling cellular signaling pathways, I apply and generalize concepts and techniques used in statistical physics and in the engineering of communication networks.
2) Complex dynamics in healthy physiologic systems
Recent studies demonstrate that heart rate variability, physical activity, or core temperature of healthy humans display complex fluctuations which are altered for disease or aging. These studies suggest that health may be related to the body's ability to call upon a wide range of responses when confronted with different environmental stimuli. For example, when walking up-hill one's heart has to adjust to the need to provide more oxygen to the cells in the body and one's heart rate has to increase. However, in congestive heart failure patients, the heart is not able to respond adequately to the increased demands of the body and the patients become tired and out-of-breath. This lack of a broad range of responses is even more extreme in patients with older implanted pacemakers, which would act only when the heart rate of the patient would become too low or too high. Modern pacemakers can detect changes in position or level of physical activity but are still unable to reproduce the wide range of response observed in the healthy heart.
My research in this area is directed at answering two classes of question. The first question concerns the effect of complex stimulation on diseased or aged individuals. Would stimulation with the same statistical properties of healthy variability lead to better clinical outcomes than (i) no stimulation, or (ii) simple--i.e., periodic or random--stimulation? The second question concerns the ability to develop new diagnosis and prognosis techniques based on the analysis of continuous recording of physiological signals.
For instance, is it possible to identify differences in the activity records of healthy versus depressed individuals? Can such a system be used safely to monitor the condition of patients at risk for depression?

L.A.N. Amaral, A. Scala, M. Barthelemy, and H.E. Stanley, "Classes of small-world networks." Proc. Nat. Ac. Sci. USA 97, 11149-11152 (2000).

A. Scala, L.A.N. Amaral, and M. Barthelemy, "Small-world networks and the conformation space of a short lattice polymer chain." Europhys. Lett. 55, 594-600 (2001).

F. Liljeros, C.R. Edling, L.A.N. Amaral, H.E. Stanley, and Y. Aberg, "The web of human sexual contacts." Nature (London) 411, 907-908 (2001).

S. Mossa, M. Barthelemy, H.E. Stanley, and L.A.N. Amaral, "Truncation of power law behavior in scale-free network models due to information filtering." Phys. Lett. Lett. 88, 138701 (2002); Virtual J. of Biol. Phys. Res. 3(6) (2002).

J. Camacho, R. Guimera, and L.A.N. Amaral, "Robust patterns in food web structure." Phys. Lett. Lett. 88, 228102 (2002); Virtual J. of Biol. Phys. Res. 3(10) (2002).

P.Ch. Ivanov, L.A.N. Amaral, A.L. Goldberger, S. Havlin, M.B. Rosenblum, Z. Struzik, and H.E. Stanley, "Multifractality in human heartbeat dynamics." Nature (London) 399, 461-465 (1999).

L.A.N. Amaral, P.Ch. Ivanov, N. Aoyagi, I. Hidaka, S. Tomono, A.L. Goldberger, H.E. Stanley, and Y. Yamamoto, "Behavioral-independent features of complex heartbeat dynamics." Phys. Rev. Lett. 86, 6026-6029 (2001).

P. Bernaola-Galvan, P.Ch. Ivanov, L.A.N. Amaral, and H.E. Stanley, "Scale invariance in the nonstationarity of physiologic signals." Phys. Rev. Lett. 87, 168105 (2001).

A.L. Goldberger, L.A.N. Amaral, L. Glass, S. Havlin, J. Hausdorff, P.Ch. Ivanov, R. Mark, J. Mietus, G. Moody, C.-K. Peng, and H. E. Stanley, "PhysioBank, PhysioToolkit, and PhysioNet: Components of a new Research Resource for Complex Physiologic Signals." Circulation 101, e215-e220 (2000).

View all publications by publications by Luis A. Nunes Amaral listed in the National Library of Medicine (PubMed).