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
20 resultados
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Agora exibindo 1 - 10 de 20
- 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.
- Stochastic model for gene transcription on Drosophila melanogaster embryos(2016) PRATA, Guilherme N.; HORNOS, Jose Eduardo M.; RAMOS, Alexandre F.We examine immunostaining experimental data for the formation of stripe 2 of even-skipped (eve) transcripts on D. melanogaster embryos. An estimate of the factor converting immunofluorescence intensity units into molecular numbers is given. The analysis of the eve dynamics at the region of stripe 2 suggests that the promoter site of the gene has two distinct regimes: an earlier phase when it is predominantly activated until a critical time when it becomes mainly repressed. That suggests proposing a stochastic binary model for gene transcription on D. melanogaster embryos. Our model has two random variables: the transcripts number and the state of the source of mRNAs given as active or repressed. We are able to reproduce available experimental data for the average number of transcripts. An analysis of the random fluctuations on the number of eves and their consequences on the spatial precision of stripe 2 is presented. We show that the position of the anterior or posterior borders fluctuate around their average position by similar to 1% of the embryo length, which is similar to what is found experimentally. The fitting of data by such a simple model suggests that it can be useful to understand the functions of randomness during developmental processes.
- Binary Expression Enhances Reliability of Messaging in Gene Networks(2020) GAMA, Leonardo R.; GIOVANINI, Guilherme; BALAZSI, Gabor; RAMOS, Alexandre F.The promoter state of a gene and its expression levels are modulated by the amounts of transcription factors interacting with its regulatory regions. Hence, one may interpret a gene network as a communicating system in which the state of the promoter of a gene (the source) is communicated by the amounts of transcription factors that it expresses (the message) to modulate the state of the promoter and expression levels of another gene (the receptor). The reliability of the gene network dynamics can be quantified by Shannon's entropy of the message and the mutual information between the message and the promoter state. Here we consider a stochastic model for a binary gene and use its exact steady state solutions to calculate the entropy and mutual information. We show that a slow switching promoter with long and equally standing ON and OFF states maximizes the mutual information and reduces entropy. That is a binary gene expression regime generating a high variance message governed by a bimodal probability distribution with peaks of the same height. Our results indicate that Shannon's theory can be a powerful framework for understanding how bursty gene expression conciliates with the striking spatio-temporal precision exhibited in pattern formation of developing organisms.
- 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.conferenceObject A simulation of laser energy absorption by a nanowired surface(2019) VASCONCELOS, Miguel F. S.; RAMOS, Alexandre F.The quest for strategies for performing nuclear fusion induced by laser remains open despite recent experiments demonstrating energy gain. A major challenge of the field is to surmount the plasma shielding which prevents the deposition of larger fractions of the energy of the laser rays into the target. Recently, a petawatt laser and computer simulations were used to show that a nanowired surface enables the trapping of the rays and the formation of a high density plasma. Here we simulate the laser target interaction considering a 0.5 TW laser and compare the energy absorption by both a smoothed and a nanowired target. We show that the nanowires enable a stronger laser-target coupling despite the absence of the trapping of the rays. Our results point out on the necessity of a deeper understanding of the mechanisms underlying the higher absorption of the laser energy by the nanowired surfaces.conferenceObject Evaluation of the functional role and the potential prognostic value of the members of the PHLDA family (pleckstrin homology-like domain family A) using data mining.(2018) VALOYES, Maira Andrea; RAMOS, Alexandre; NAGAI, Maria Aparecida- Physical implications of so(2,1) symmetry in exact solutions for a self-repressing gene(2019) RAMOS, Alexandre F.; REINITZ, JohnWe chemically characterize the symmetries underlying the exact solutions of a stochastic negatively self-regulating gene. The breaking of symmetry at a low molecular number causes three effects. Two branches of the solution exist, having high and low switching rates, such that the low switching rate branch approaches deterministic behavior and the high switching rate branch exhibits sub-Fano behavior. The average protein number differs from the deterministically expected value. Bimodal probability distributions appear as the protein number becomes a readout of the ON/OFF state of the gene.
- Optimal low-latency network topologies for cluster performance enhancement(2020) DENG, Yuefan; GUO, Meng; RAMOS, Alexandre F.; HUANG, Xiaolong; XU, Zhipeng; LIU, WeifengWe propose that clusters interconnected with network topologies having minimal mean path length will increase their processing speeds. We approach our heuristic by constructing clusters of up to 32 nodes having torus, ring, Chvatal, Wagner, Bidiakis and optimal topology for minimal mean path length and by simulating the performance of 256 nodes clusters with the same network topologies. The optimal (or near-optimal) low-latency network topologies are found by minimizing the mean path length of regular graphs. The selected topologies are benchmarked using ping-pong messaging, the MPI collective communications and the standard parallel applications including effective bandwidth, FFTE, Graph 500 and NAS parallel benchmarks. We established strong correlations between the clusters' performances and the network topologies, especially the mean path lengths, for a wide range of applications. In communication-intensive benchmarks, optimal graphs enabled network topologies with multifold performance enhancement in comparison with mainstream graphs. It is striking that mere adjustment of the network topology suffices to reclaim performance from the same computing hardware.