Search results for " graph"
showing 10 items of 1277 documents
Design of antitumor drugs targeting c-kit receptor by a new mixed ligand-structure based method
2020
An important challenge, in the medicinal chemistry field, is the research of novel forceful drugs to overcome tumor-acquired resistance. The c-Kit tyrosine kinase receptor (TKR) represents a suitable target for the carcinogenesis control of gastro-intestinal stromal (GIST), leukemia, and mastocytosis tumors; nevertheless, several hotspot mutations of the protein limit the efficacy of a few clinical administered TKRs inhibitors. In this study, a new in silico protocol based on ligand and structure-based combined method is proposed, with the aim to identify a set of new c-Kit inhibitors able to complex c-Kit mutated proteins. A recent and freely available web-server DRUDIT is used for the lig…
Model selection for penalized Gaussian Graphical Models
2013
High-dimensional data refers to the case in which the number of parameters is of one or more order greater than the sample size. Penalized Gaussian graphical models can be used to estimate the conditional independence graph in high-dimensional setting. In this setting, the crucial issue is to select the tuning parameter which regulates the sparsity of the graph. In this paper, we focus on estimating the "best" tuning parameter. We propose to select this tuning parameter by minimizing an information criterion based on the generalized information criterion and to use a stability selection approach in order to obtain a more stable graph. The performance of our method is compared with the state…
Covariate adjusted censored gaussian lasso estimator
2021
The covariate adjusted glasso is one of the most used estimators for in- ferring genetic networks. Despite its diffusion, there are several fields in applied research where the limits of detection of modern measurement technologies make the use of this estimator theoretically unfounded, even when the assumption of a multivariate Gaussian distribution is satisfied. In this paper we propose an extension to censored data.
SPARSE INFERENCE IN COVARIATE ADJUSTED CENSORED GAUSSIAN GRAPHICAL MODELS
2021
The covariate adjusted glasso is one of the most used estimators for inferring genetic networks. Despite its diffusion, there are several fields in applied research where the limits of detection of modern measurement technologies make the use of this estimator theoretically unfounded, even when the assumption of a multivariate Gaussian distribution is satisfied. In this paper we propose an extension to censored data.
A computational method to estimate sparse multiple Gaussian graphical models
2012
In recent years several researchers have proposed the use of the Gaussian graphical model defined on a high dimensional setting to explore the dependence relationships between random variables. Standard methods, usually proposed in literature, are based on the use of a specific penalty function, such as the L1-penalty function. In this paper our aim is to estimate and compare two or more Gaussian graphical models defined in a high dimensional setting. In order to accomplish our aim, we propose a new computational method, based on glasso method, which lets us to extend the notion of p-value.
Genetic Network construction in CML gene expression profile data analysis
2009
Aim of this paper is to define a new statistical framework to identify central modules in Gaussian Graphical Models (GGMs) estimated by gene expression data measured on a sample of patients with negative molecular response to imatinib. A central module is defined as a module of a GGM which contains genes that are defined differentially expressed.
The Joint Censored Gaussian Graphical Lasso Model
2022
The Gaussian graphical model is one of the most used tools for inferring genetic networks. Nowadays, the data are often collected from different sources or under different biological conditions, resulting in heterogeneous datasets that exhibit a dependency structure that varies across groups. The complex structure of these data is typically recovered using regularized inferential procedures that use two penalties, one that encourages sparsity within each graph and the other that encourages common structures among the different groups. To this date, these approaches have not been developed for handling the case of censored data. However, these data are often generated by gene expression tech…
Holding the Road: Away from Edmund Wilson and Mary McCarthy, by Reuel K. Wilson
2020
A sad reflection of the current state of American publishing is that Reuel Wilson had to publish privately the autobiography under review. And yet no book could be further away from a vanity public...
Data Analytics in Healthcare: A Tertiary Study
2022
AbstractThe field of healthcare has seen a rapid increase in the applications of data analytics during the last decades. By utilizing different data analytic solutions, healthcare areas such as medical image analysis, disease recognition, outbreak monitoring, and clinical decision support have been automated to various degrees. Consequently, the intersection of healthcare and data analytics has received scientific attention to the point of numerous secondary studies. We analyze studies on healthcare data analytics, and provide a wide overview of the subject. This is a tertiary study, i.e., a systematic review of systematic reviews. We identified 45 systematic secondary studies on data analy…
Strong chromatic index of products of graphs
2007
Graphs and Algorithms