Due to high demand for this course, we operate a staged admissions process with multiple selection deadlines throughout the year, to maintain a fair and transparent approach. Explore our campus, meet ...
Computational statistics harnesses the power of sophisticated numerical algorithms and high‐performance computing to solve complex inferential problems that are intractable by traditional analytical ...
A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic ...
Data really powers everything that we do. Research activities in the data science area are concerned with the development of machine learning and computational statistical methods, their theoretical ...
A main bottleneck in proteomics is the downstream biological analysis of highly multivariate quantitative protein abundance data generated using mass-spectrometry ...
This course is designed for engineering graduate students who are interested in furthering their knowledge in advanced and emerging methods of engineering design, with the focus on computational ...
Researchers developed a new computational method to analyze complex tissue data that could transform our current understanding of diseases and how we treat them. Researchers at the University of ...
The Computational and Statistical Genomics group is based at FIMM–EMBL and works at the interface of computational genomics, population genetics, and large-scale human datasets. Our research focuses ...
A paper published in Biology Methods and Protocols, indicates that a new computational method may help researchers identify ...
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