User profiles for Christoph Feinauer
 | Christoph FeinauerIsomorphic Labs Verified email at isomorphiclabs.com Cited by 792 |
Inverse statistical physics of protein sequences: a key issues review
In the course of evolution, proteins undergo important changes in their amino acid
sequences, while their three-dimensional folded structure and their biological function remain …
sequences, while their three-dimensional folded structure and their biological function remain …
[HTML][HTML] Fast and accurate multivariate Gaussian modeling of protein families: predicting residue contacts and protein-interaction partners
In the course of evolution, proteins show a remarkable conservation of their three-dimensional
structure and their biological function, leading to strong evolutionary constraints on the …
structure and their biological function, leading to strong evolutionary constraints on the …
Mutator genomes decay, despite sustained fitness gains, in a long-term experiment with bacteria
A Couce, LV Caudwell, C Feinauer… - Proceedings of the …, 2017 - National Acad Sciences
Understanding the extreme variation among bacterial genomes remains an unsolved challenge
in evolutionary biology, despite long-standing debate about the relative importance of …
in evolutionary biology, despite long-standing debate about the relative importance of …
[HTML][HTML] Improving contact prediction along three dimensions
Correlation patterns in multiple sequence alignments of homologous proteins can be
exploited to infer information on the three-dimensional structure of their members. The typical …
exploited to infer information on the three-dimensional structure of their members. The typical …
Deep networks on toroids: removing symmetries reveals the structure of flat regions in the landscape geometry
…, A Ferraro, G Perugini, C Feinauer… - International …, 2022 - proceedings.mlr.press
We systematize the approach to the investigation of deep neural network landscapes by
basing it on the geometry of the space of implemented functions rather than the space of …
basing it on the geometry of the space of implemented functions rather than the space of …
[HTML][HTML] Inter-protein sequence co-evolution predicts known physical interactions in bacterial ribosomes and the Trp operon
Interaction between proteins is a fundamental mechanism that underlies virtually all biological
processes. Many important interactions are conserved across a large variety of species. …
processes. Many important interactions are conserved across a large variety of species. …
Entropic gradient descent algorithms and wide flat minima
The properties of flat minima in the empirical risk landscape of neural networks have been
debated for some time. Increasing evidence suggests they possess better generalization …
debated for some time. Increasing evidence suggests they possess better generalization …
Generating interacting protein sequences using domain-to-domain translation
Motivation Being able to artificially design novel proteins of desired function is pivotal in
many biological and biomedical applications. Generative statistical modeling has recently …
many biological and biomedical applications. Generative statistical modeling has recently …
TULIP—a Transformer based Unsupervised Language model for Interacting Peptides and T-cell receptors that generalizes to unseen epitopes
The accurate prediction of binding between T-cell receptors (TCR) and their cognate epitopes
is key to understanding the adaptive immune response and developing immunotherapies. …
is key to understanding the adaptive immune response and developing immunotherapies. …
The Mean Dimension of Neural Networks--What causes the interaction effects?
R Hahn, C Feinauer, E Borgonovo - arXiv preprint arXiv:2207.04890, 2022 - arxiv.org
Owen and Hoyt recently showed that the effective dimension offers key structural information
about the input-output mapping underlying an artificial neural network. Along this line of …
about the input-output mapping underlying an artificial neural network. Along this line of …