Publications by Computational Biology and Bioinformatics

Xu, W. and Reinert, G. (2023) “AgraSSt: approximate graph Stein statistics for interpretable assessment of implicit graph generators”, Advances in Neural Information Processing Systems 35.

Lu, Y., Reinert, G. and Cucuringu, M. (2023) “Co-trading networks for modeling dynamic interdependency structures and estimating high-dimensional covariances in US equity markets”, arXiv.

Lu, Y., Reinert, G. and Cucuringu, M. (2023) “Co-Trading Networks for Modeling Dynamic Interdependency Structures and Estimating High-Dimensional Covariances in US Equity Markets”, SSRN Electronic Journal.

Agarwal, I. et al. (2023) “Relating pathogenic loss-of-function mutations in humans to their evolutionary fitness costs”, eLife, 12, p. e83172.

Raybould, M. et al. (2023) “Computationally profiling peptide: MHC recognition by T-cell receptors and T-cell receptor-mimetic antibodies”, Frontiers in Immunology, 13.

Spoendlin, F. et al. (2023) “Improved computational epitope profiling using structural models identifies a broader diversity of antibodies that bind the same epitope”, bioRxiv.

Mijoule, G. et al. (2023) “Stein’s density method for multivariate continuous distributions”, Electronic Journal of Probability, 28(none).

He, Y. et al. (2023) “PyTorch Geometric Signed Directed: A Software Package on Graph Neural Networks for Signed and Directed Graphs”, in Proceedings of Machine Learning Research, pp. 121–1227.

Raybould, M. et al. (2023) “Contextualising the developability risk of antibodies with lambda light chains using enhanced therapeutic antibody profiling”, bioRxiv.

Hu, S. et al. (2023) “Leveraging fine-scale population structure reveals conservation in genetic effect sizes between human populations across a range of human phenotypes”, bioRxiv.