Wilks’ dissimilarity for gene clustering: computational issues

Autor: F. Marta L. Di Lascio, Alberto Roverato

Publikováno v: Epidemiology, Biostatistics, and Public Health; V. 10 N. 2 (2013)
Epidemiology, Biostatistics, and Public Health; Vol. 10 No. 2 (2013)
Epidemiology Biostatistics and Public Health, Vol 10, Iss 2 (2013)
Epidemiology, Biostatistics and Public Health; Vol 10, No 2 (2013)

Clustering methods are widely used in the analysis of gene expression data for their ability to uncover coordinated expression profiles. One important goal of clustering is to discover co–regulated genes because it has been postulated that co–reg

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dd29eae769166d433792902788337c0c
https://doi.org/10.2427/8761

Structural learning of Gaussian graphical models from microarray data with p larger than n

Autor: Alberto Roverato, Robert Castelo

Publikováno v: Statistica, Vol 66, Iss 4, Pp 343-372 (2008)

Learning of large-scale networks of interactions from microarray data is an important and challenging problem in bioinformatics. A widely used approach is to assume that the available data constitute a random sample from a multivariate distribution b

Externí odkaz: https://doaj.org/article/6691264211164cc78b8a039f0864f3b2

On the interpretation of inflated correlation path weights in concentration graphs

Autor: Alberto Roverato

Statistical models associated with graphs, called graphical models, have become a popular tool for representing network structures in many modern applications. Relevant features of the model are represented by vertices, edges and other higher order s

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d2d32d002d3f45414421bd6bf7e6ef15
http://hdl.handle.net/11577/3401988

Log‐mean Linear Parameterization for Discrete Graphical Models of Marginal Independence and the Analysis of Dichotomizations

Autor: Alberto Roverato

Publikováno v: Scandinavian Journal of Statistics. 42:627-648

We extend the log-mean linear parameterization for binary data to discrete variables with arbitrary number of levels and show that also in this case it can be used to parameterize bi-directed graph models. Furthermore, we show that the log-mean linea

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36bde1ddc447ddd07b4415aa531061bd
https://doi.org/10.1111/sjos.12126

The networked partial correlation and its application to the analysis of genetic interactions

Autor: Robert Castelo, Alberto Roverato

Publikováno v: Recercat. Dipósit de la Recerca de Catalunya
instname

Genetic interactions confer robustness on cells in response to genetic perturbations. This often occurs through molecular buffering mechanisms that can be predicted using, among other features, the degree of coexpression between genes, commonly estim

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7804643afb8afc3ad733b3fadfbc89ec
http://hdl.handle.net/11585/588428