ALEXANDRE FERREIRA RAMOS
Projetos de Pesquisa
Unidades Organizacionais
SIN-86, EACH - Docente
LIM/24 - Laboratório de Oncologia Experimental, Hospital das Clínicas, Faculdade de Medicina - Líder
LIM/26 - Laboratório de Pesquisa em Cirurgia Experimental, Hospital das Clínicas, Faculdade de Medicina
LIM/24 - Laboratório de Oncologia Experimental, Hospital das Clínicas, Faculdade de Medicina - Líder
LIM/26 - Laboratório de Pesquisa em Cirurgia Experimental, Hospital das Clínicas, Faculdade de Medicina
6 resultados
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- A comparative analysis of noise properties of stochastic binary models for a self-repressing and for an externally regulating gene(2020) GIOVANINI, Guilherme; SABINO, Alan U.; BARROS, Luciana R. C.; RAMOS, Alexandre F.This manuscript presents a comparison of noise properties exhibited by two stochastic binary models for: (i) a self-repressing gene; (ii) a repressed or activated externally regulating one. The stochastic models describe the dynamics of probability distributions governing two random variables, namely, protein numbers and the gene state as ON or OFF. In a previous work, we quantify noise in protein numbers by means of its Fano factor and write this quantity as a function of the covariance between the two random variables. Then we show that distributions governing the number of gene products can be super-Fano, Fano or sub-Fano if the covariance is, respectively, positive, null or negative. The latter condition is exclusive for the self-repressing gene and our analysis shows the conditions for which the Fano factor is a sufficient classifier of fluctuations in gene expression. In this work, we present the conditions for which the noise on the number of gene products generated from a self-repressing gene or an externally regulating one are quantitatively similar. That is important for inference of gene regulation from noise in gene expression quantitative data. Our results contribute to a classification of noise function in biological systems by theoretically demonstrating the mechanisms underpinning the higher precision in expression of a self-repressing gene in comparison with an externally regulated one.
- Lessons and perspectives for applications of stochastic models in biological and cancer research(2018) SABINO, Alan U.; VASCONCELOS, Miguel Fs; SITTONI, Misaki Yamada; LAUTENSCHLAGER, Willian W.; QUEIROGA, Alexandre S.; MORAIS, Mauro Cc; RAMOS, Alexandre F.The effects of randomness, an unavoidable feature of intracellular environments, are observed at higher hierarchical levels of living matter organization, such as cells, tissues, and organisms. Additionally, the many compounds interacting as a well-orchestrated network of reactions increase the difficulties of assessing these systems using only experiments. This limitation indicates that elucidation of the dynamics of biological systems is a complex task that will benefit from the establishment of principles to help describe, categorize, and predict the behavior of these systems. The theoretical machinery already available, or ones to be discovered to help solve biological problems, might play an important role in these processes. Here, we demonstrate the application of theoretical tools by discussing some biological problems that we have approached mathematically: fluctuations in gene expression and cell proliferation in the context of loss of contact inhibition. We discuss the methods that have been employed to provide the reader with a biologically motivated phenomenological perspective of the use of theoretical methods. Finally, we end this review with a discussion of new research perspectives motivated by our results.
- Symmetry-guided design of topologies for supercomputer networks(2018) SABINO, Alan U.; VASCONCELOS, Miguel F. S.; DENG, Yuefan; RAMOS, Alexandre F.A family of graphs optimized as the topologies for interconnection networks is proposed. The needs of such topologies with minimal diameters and minimal mean path lengths are met by special constructions of the weight vectors in a representation of the symplectic algebra. Such design of topologies can conveniently reconstruct the mesh and hypercube, widely used as network topologies, as well as many other classes of graphs potentially suitable for network topologies.
conferenceObject Stochastic model of contact inhibition and the proliferation of melanoma in situ.(2018) MORAIS, Mauro Cesar C.; STUHL, Izabella; SABINO, Alan U.; LAUTENSCHLAGER, Willian W.; QUEIROGA, Alexandre S.; TORTELLI JR., Tharcisio C.; CHAMMAS, Roger; SUHOV, Yuri; RAMOS, Alexandre F.- A comparative analysis of noise properties of stochastic binary models for a self-repressing and for an externally regulating gene (vol 17, pg 5477, 2020)(2020) GIOVANINI, Guilherme; SABINO, Alan U.; BARROS, Luciana R. C.; RAMOS, Alexandre F.
- Stochastic model of contact inhibition and the proliferation of melanoma in situ(2017) MORAIS, Mauro Cesar Cafundo; STUHL, Izabella; SABINO, Alan U.; LAUTENSCHLAGER, Willian W.; QUEIROGA, Alexandre S.; TORTELLI JR., Tharcisio Citrangulo; CHAMMAS, Roger; SUHOV, Yuri; RAMOS, Alexandre F.Contact inhibition is a central feature orchestrating cell proliferation in culture experiments; its loss is associated with malignant transformation and tumorigenesis. We performed a co-culture experiment with human metastatic melanoma cell line (SKMEL-147) and immortalized keratinocyte cells (HaCaT). After 8 days a spatial pattern was detected, characterized by the formation of clusters of melanoma cells surrounded by keratinocytes constraining their proliferation. In addition, we observed that the proportion of melanoma cells within the total population has increased. To explain our results we propose a spatial stochastic model (following a philosophy of the Widom-Rowlinson model from Statistical Physics and Molecular Chemistry) which considers cell proliferation, death, migration, and cell-to-cell interaction through contact inhibition. Our numerical simulations demonstrate that loss of contact inhibition is a sufficient mechanism, appropriate for an explanation of the increase in the proportion of tumor cells and generation of spatial patterns established in the conducted experiments.