SWISS-MODEL: homology modelling of protein structures and complexes
Homology modelling has matured into an important technique in structural biology, significantly contributing to narrowing the gap between known protein sequences and experimenta...
Publications
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734 publications
A Mathematical Theory of Evidence
Both in science and in practical affairs we reason by combining facts only inconclusively supported by evidence. Building on an abstract understanding of this process of combina...
Large-Area Synthesis of High-Quality and Uniform Graphene Films on Copper Foils
Growing Graphene The highest quality graphene samples, single-atom-thick layers of carbon, are suspended flakes exfoliated from graphite, but these samples are very small in siz...
Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications
The purpose of this study was to classify breast carcinomas based on variations in gene expression patterns derived from cDNA microarrays and to correlate tumor characteristics ...
Non-local Neural Networks
Both convolutional and recurrent operations are building blocks that process one local neighborhood at a time. In this paper, we present non-local operations as a generic family...
High-Resolution Image Synthesis with Latent Diffusion Models
By decomposing the image formation process into a sequential application of denoising autoencoders, diffusion models (DMs) achieve state-of-the-art synthesis results on image da...
Petri nets: Properties, analysis and applications
Starts with a brief review of the history and the application areas considered in the literature. The author then proceeds with introductory modeling examples, behavioral and st...
The cornerstones of competitive advantage: A resource‐based view
Abstract This paper elucidates the underlying economics of the resource‐based view of competitive advantage and integrates existing perspectives into a parsimonious model of res...
Gaussian Processes for Machine Learning
We give a basic introduction to Gaussian Process regression models. We focus on understanding the role of the stochastic process and how it is used to define a distribution over...