A new graph-attention-based generative adversarial network called GARAGE produces realistic synthetic single-cell RNA-seq ...
Whether you’re genuinely interested in getting insights and solving problems using data, or just attracted by what has been called “the most promising career” by LinkedIn and the “best job in America” ...
Researchers in Hangzhou have developed MGCRN, a graph-based recurrent neural network that maintains high forecasting accuracy ...
We introduce GRouNdGAN, a gene regulatory network (GRN)-guided reference-based causal implicit generative model for simulating single-cell RNA-seq data, in silico perturbation experiments, and ...
Graph neural networks (GNNs) are a type of neural network architecture and deep learning method that can help users analyze graphs, enabling them to make predictions based on the data described by a ...
Explore the concept of graph databases, their use cases, benefits, drawbacks, and popular tools. A graph database is a dynamic database management system uniquely structured to manage complex and ...
Many organizations use data fabrics to connect disparate data sources to a central access point, regardless of their type or location. Some take this further by incorporating knowledge graphs into ...
Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. This eMag examines how architects can lead ...
Understand the principles of efficient algorithms for dealing with large scale data sets and be able to select appropriate algorithms for specific problems. Understand and be able to apply the main ...
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