11 papers · ranked by Valyu relevance
Krishna Rijal, Pankaj Mehta
The Gillespie algorithm is commonly used to simulate and analyze complex chemical reaction networks. Here, we leverage recent breakthroughs in deep learning to develop a fully differentiable variant of the Gillespie algorithm. The differentiable Gillespie algorithm (DGA) approximates discontinuous operations in the…
Hung-I Harry Chen, Yuanhang Liu, Yi Zou, Zhao Lai + 3 more
RNA sequencing (RNA-seq) is a powerful tool for genome-wide expression profiling of biological samples with the advantage of high-throughput and high resolution. There are many existing algorithms nowadays for quantifying expression levels and detecting differential gene expression, but none of them takes the…
Chen Wang, Feng Gao, Georgios B. Giannakis, Gennaro D’Urso + 1 more
Gene networks in living cells can change depending on various conditions such as caused by different environments, tissue types, disease states, and development stages. Identifying the differential changes in gene networks is very important to understand molecular basis of various biological process. While existing…
Jiacheng Leng, Jiating Yu, Ling-Yun Wu
Differential graph inference is a critical analytical technique that enables researchers to accurately identify the variables and their interactions that change under different conditions. By comparing two conditions, researchers can gain a deeper understanding of the differences between them. Currently, the mainstream…
Herty Liany, Jagath C. Rajapakse, R. Krishna Murthy Karuturi
Differential co-expression signifies change in degree of co-expression of a set of genes among different biological conditions. It has been used to identify differential co-expression networks or interactomes. Many algorithms have been developed for single-factor differential co-expression analysis and applied in a…
Fang-Cheng Yeh, Islam M. Zaydan, Valerie R. Suski, David Lacomis + 3 more
Diffusion MRI tractography has been used to map the axonal structure of human brain, but its ability to detect neurodegeneration is yet to be explored. Here we report differential tractography, a new type of tractography that utilizes a novel tracking strategy to map the exact segment of fiber pathways with…
Jurgen Riedel, Chris P. Barnes
In this study we examine the emergence of complex biological patterns through the lens of reaction-diffusion systems. We introduce two novel complexity metrics, Diversity of Number of States (DNOS) and Diversity of Pattern Complexity (DPC), which aim to quantify structural intricacies in pattern formation, enhancing…
Kai Trepka
Building models of organismal growth enables predictions of natural variability and responses to perturbations. Complex systems such as animal pattern development and bacterial colonies can be modeled numerically using a reaction-diffusion system with relatively few factors and yield qualitatively accurate results…
Qichen Huang, Haoyang Guo
Cellular automata and graph reaction–diffusion systems encode local spatial interactions in different mathematical forms. We develop a cochain-operator calculus for these two settings. Over a finite field F_q_, every local rule on a finite neighborhood has a unique reduced polynomial representative. On an oriented…
Ouassim Bara, Michel Fliess, Cédric Join, Judy Day + 1 more
An effective and patient-specific feedback control synthesis for inflammation resolution is still an ongoing research area. A strategy consisting of manipulating a pro and anti-inflammatory mediator is considered here as used in some promising model-based control studies. These earlier studies, unfortunately, suffer…
Jack Oldham
This section demonstrates the cell to cell communication algorithm that enables population size detection and consequently results in formation of a gradient of signalling production rates. This concept is derived from a quorum sensing (6) inspired thought experiment that is to ask how a population of cells can…