Zobrazeno 1 - 10
of 103
pro vyhledávání: '"Gesine, Reinert"'
Autor:
Stephanie Armbruster, Gesine Reinert
Publikováno v:
Applied Network Science, Vol 9, Iss 1, Pp 1-21 (2024)
Abstract Network-based time series models have experienced a surge in popularity over the past years due to their ability to model temporal and spatial dependencies, arising from the spread of infectious disease. The generalised network autoregressiv
Externí odkaz:
https://doaj.org/article/1070fc94399d4111b1829502c7ce5d65
Autor:
Ruihua Zhang, Gesine Reinert
Publikováno v:
Entropy, Vol 26, Iss 10, p 813 (2024)
A better understanding of protein–protein interaction (PPI) networks representing physical interactions between proteins could be beneficial for evolutionary insights as well as for practical applications such as drug development. As a statistical
Externí odkaz:
https://doaj.org/article/4e53704128c54847a0faf163c207b9b7
Autor:
Florian Klimm, Enrique M. Toledo, Thomas Monfeuga, Fang Zhang, Charlotte M. Deane, Gesine Reinert
Publikováno v:
BMC Genomics, Vol 21, Iss 1, Pp 1-10 (2020)
Abstract Background Recent advances in single-cell RNA sequencing have allowed researchers to explore transcriptional function at a cellular level. In particular, single-cell RNA sequencing reveals that there exist clusters of cells with similar gene
Externí odkaz:
https://doaj.org/article/1dac96c804a549c589fad5752cff1859
Publikováno v:
BMC Bioinformatics, Vol 20, Iss 1, Pp 1-14 (2019)
Abstract Background Protein interaction databases often provide confidence scores for each recorded interaction based on the available experimental evidence. Protein interaction networks (PINs) are then built by thresholding on these scores, so that
Externí odkaz:
https://doaj.org/article/11cb227468d34de7bc05bb3cb7f684ea
Autor:
Javier Pardo-diaz, Mariano Beguerisse-díaz, Philip S. Poole, Charlotte M. Deane, Gesine Reinert
Publikováno v:
Journal of Computational Biology. 29:752-768
Nitrogen uptake in legumes is facilitated by bacteria such as Rhizobium leguminosarum. For this bacterium, gene expression data are available, but functional gene annotation is less well developed than for other model organisms. More annotations coul
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e2bda01b5b41dc4d6151d1d890758f96
https://doi.org/10.1089/cmb.2021.0600
https://doi.org/10.1089/cmb.2021.0600
Autor:
Andreas Anastasiou, Alessandro Barp, François-Xavier Briol, Bruno Ebner, Robert E. Gaunt, Fatemeh Ghaderinezhad, Jackson Gorham, Arthur Gretton, Christophe Ley, Qiang Liu, Lester Mackey, Chris J. Oates, Gesine Reinert, Yvik Swan
Publikováno v:
Statistical Science. 38
Stein’s method compares probability distributions through the study of a class of linear operators called Stein operators. While mainly studied in probability and used to underpin theoretical statistics, Stein’s method has led to significant adva
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8b6eb63a1e41f143700cb38b55b8a842
https://doi.org/10.1214/22-sts863
https://doi.org/10.1214/22-sts863
Autor:
Lyuba V. Bozhilova, Charlotte M. Deane, Javier Pardo-Diaz, Mariano Beguerisse-Díaz, Gesine Reinert, Philip S. Poole
Publikováno v:
Bioinformatics
Motivation Even within well-studied organisms, many genes lack useful functional annotations. One way to generate such functional information is to infer biological relationships between genes/proteins, using a network of gene coexpression data that
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c8d5f7b25523d2206ea4e3cf1097f63e
https://doi.org/10.1093/bioinformatics/btab041
https://doi.org/10.1093/bioinformatics/btab041
Autor:
Charlotte M. Deane, Philip S. Poole, Javier Pardo-Diaz, Mariano Beguerisse-Díaz, Gesine Reinert
Publikováno v:
Netw Sci (Camb Univ Press)
Even within well-studied organisms, many genes lack useful functional annotations. One way to generate such functional information is to infer biological relationships between genes or proteins, using a network of gene coexpression data that includes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c7bf73d63d8cc46469cb5dd38a3d68f0
https://europepmc.org/articles/PMC7613200/
https://europepmc.org/articles/PMC7613200/
Publikováno v:
Intelligent Data Engineering and Automated Learning – IDEAL 2022 ISBN: 9783031217524
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::afd96a069e2e5af5d8bdf1aea14cde5a
https://doi.org/10.1007/978-3-031-21753-1_42
https://doi.org/10.1007/978-3-031-21753-1_42
Autor:
Gesine Reinert, A. D. Barbour
Publikováno v:
Journal of Complex Networks. 9
The Network Disturbance Model of Doreian (1989) expresses the dependency between observations taken at the vertices of a network by modelling the correlation between neighbouring vertices, using a single correlation parameter $\rho$. It has been obse
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::29f325996fd1effe395b7e39b0011ba4
https://doi.org/10.1093/comnet/cnab028
https://doi.org/10.1093/comnet/cnab028