Top 4 Biorxiv Papers Today in Systems Biology


1.996 Mikeys
#1. Inferring the quasipotential landscape of microbial ecosystems with topological data analysis
William K Chang, Libusha Kelly
The dynamics of high-dimensional, nonlinear systems drive biology at all scales, from gene regulatory networks to ecosystems. Microbial ecosystems ('microbiomes') exemplify such systems due to their richness and the small length- and time-scales of complex ecological and evolutionary dynamics. Microbes inhabit, respond to, and alter environments ranging from the human gut to the ocean. Here, using information theory and topological data analysis (TDA), we model microbiome dynamics as motion on a potential energy-like landscape, called the quasipotential , identifying attractor states and trajectories that characterize ecological processes including disease progression in the human microbiome and geochemical cycling in the oceans. Our approach allows holistic analysis and prediction of large-scale dynamics in generalized complex systems that are difficult to reduce to their underlying interactions.
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Authors: 2
Total Words: 4843
Unqiue Words: 1726

1.996 Mikeys
#2. eNetXplorer: an R package for the quantitative exploration of elastic net families for generalized linear models
Julián Candia, John S. Tsang
Background: Regularized generalized linear models (GLMs) are popular regression methods in bioinformatics, particularly useful in scenarios with fewer observations than parameters/features or when many of the features are correlated. In both ridge and lasso regularization, feature shrinkage is controlled by a penalty parameter lambda. The elastic net introduces a mixing parameter alpha to tune the shrinkage continuously from ridge to lasso. Selecting alpha objectively and determining which features contributed significantly to prediction after model fitting remain a practical challenge given the paucity of available software to evaluate performance and statistical significance. Results: eNetXplorer builds on top of glmnet to address the above issues for linear (Gaussian), binomial (logistic), and multinomial GLMs. It provides new functionalities to empower practical applications by using a cross validation framework that assesses the predictive performance and statistical significance of a family of elastic net models (as alpha is...
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Authors: 2
Total Words: 6501
Unqiue Words: 1847

1.994 Mikeys
#3. Evaluation of BMP-mediated patterning in zebrafish embryos using a growing finite difference embryo model
Linlin M. Li, Xu M. Wang, Mary C. Mullins, David M. Umulis
Bone Morphogenetic Proteins (BMPs) play an important role in dorsal-ventral (DV) patterning of the early zebrafish embryo. BMP signaling is regulated by a network of extracellular and intracellular factors that impact the range and signaling of BMP ligands. Recent advances in understanding the mechanism of pattern formation support a source-sink mechanism, however it is not clear how the source-sink mechanism shapes patterns in 3D, nor how sensitive the pattern is along both the anteroposterior (AP) and DV axes of the embryo. We propose a new three-dimensional growing finite difference model to simulate the BMP patterning process during the blastula stage. This model provides a starting point to elucidate how different mechanisms and components work together in 3D to create and maintain the BMP gradient in the embryo. We also show how the 3D model fits the BMP signaling gradient data at multiple time points along both axes. Furthermore, sensitivity analysis of the model suggests that the spatiotemporal patterns of Chordin and BMP...
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Authors: 4
Total Words: 5882
Unqiue Words: 1895

1.91 Mikeys
#4. A stochastic spatial model for heterogeneity in cancer growth
Alexandre Sarmento Queiroga, Mauro Cesar Cafundo de Morais, Tharcisio Citrangulo Tortelli, Roger Chammas, Alexandre Ferreira Ramos
Establishing a quantitative understanding of tumor heterogeneity, a major feature arising from the evolutionary processes taking place within the tumor microenvironment is an important challenge for cancer biologists. Recently established experimental techniques enabled summarizing the variety of tumor cell phenotypes in proliferative or migratory. In the former, cells mostly proliferate and rarely migrate, while the opposite happens with cells having the latter phenotype, a "go-and-grow" description of heterogeneity. In this manuscript we present a discrete time Markov chain to simulate the spatial evolution of a tumor which heterogeneity is described by cells having those two phenotypes. The cell density curves have two qualitatively distinct temporal regimes, as they recover the Gompertz curve widely used for tumor growth description, and a bi-phasic growth which temporal shape resembles the tumor growth dynamics under influence of immunoediting. We also show how our representation of heterogeneity gives rise to variable...
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Authors: 5
Total Words: 0
Unqiue Words: 0

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