Gene regulatory network inference based on ca
<p>The work provides a new clue for constructing GRNs, and proposed framework GRINCD also shows potential in identifying key factors affecting cancer development.</p>
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<p>The work provides a new clue for constructing GRNs, and proposed framework GRINCD also shows potential in identifying key factors affecting cancer development.</p>
Gene regulatory networks (GRNs) depict the regulatory mechanisms of genes within cellular systems as a network, offering vital insights for understanding cell processes and molecular interactions that determine cellular phenotypes.
A new project to improve the processing speed of neural networks on Apple Silicon is potentially able to speed up training on large datasets by up to ten times.
A new project to improve the processing speed of neural networks on Apple Silicon is potentially able to speed up training on large datasets by up to ten times.
To kick-start the new Research Priority Area (RPA) of the Faculty of Science in "Artificial Intelligence for Sustainable Molecules and Materials" (AI4SMM), four projects have just been launched. Combining the Faculty’s strengths in computer science and sustainability research, AI4SMM aims to develop and use machine learning techniques for the design of molecules and materials for a sustainable future. The projects cover topics as diverse as metamaterials for sustainable steel, and protein mixtures for sustainable food design.