Bayesian Networks Predict Neuronal Transdifferentiation
نویسندگان
چکیده
منابع مشابه
Modeling Neuronal Interactivity using Dynamic Bayesian Networks
Functional Magnetic Resonance Imaging (fMRI) has enabled scientists to look into the active brain. However, interactivity between functional brain regions, is still little studied. In this paper, we contribute a novel framework for modeling the interactions between multiple active brain regions, using Dynamic Bayesian Networks (DBNs) as generative models for brain activation patterns. This fram...
متن کاملUsing neural networks to predict road roughness
When a vehicle travels on a road, different parts of vehicle vibrate because of road roughness. This paper proposes a method to predict road roughness based on vertical acceleration using neural networks. To this end, first, the suspension system and road roughness are expressed mathematically. Then, the suspension system model will identified using neural networks. The results of this step sho...
متن کاملUsing Bayesian Networks to Predict Software Defects and Reliability
This paper reviews the use of Bayesian Networks (BNs) in predicting software defects and software reliability. The approach allows us to incorporate causal process factors as well as combine qualitative and quantitative measures, hence overcoming some of the well-known limitations of traditional software metrics methods. The approach has been used by organisations such as Motorola, Siemens and ...
متن کاملComputational Genomics: Project Using Bayesian Networks to Predict Lactose and Tryptophan Networks In E.Coli
Constructing genetic regulatory networks from microarray data is a new challenge for computational biology. Boolean models and differential equations are two of the techniques used. Recently, Bayesian networks were utilized for this problem giving optimistic results. In our study, we use graphical models and Bayesian scoring in order to predict a subset of two famous regulatory networks from E....
متن کاملAn Introduction to Inference and Learning in Bayesian Networks
Bayesian networks (BNs) are modern tools for modeling phenomena in dynamic and static systems and are used in different subjects such as disease diagnosis, weather forecasting, decision making and clustering. A BN is a graphical-probabilistic model which represents causal relations among random variables and consists of a directed acyclic graph and a set of conditional probabilities. Structure...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: G3 Genes|Genomes|Genetics
سال: 2018
ISSN: 2160-1836
DOI: 10.1534/g3.118.200401