A5068403840- Gene expression and cancer classification
- Bioinformatics and Genomic Networks
- Gene Regulatory Network Analysis
- Statistical Methods and Inference
- Bayesian Methods and Mixture Models
- Bayesian Modeling and Causal Inference
- Complex Network Analysis Techniques
- Mental Health Research Topics
- Opinion Dynamics and Social Influence
- Statistical Methods and Bayesian Inference
- Genetic Mapping and Diversity in Plants and Animals
- Advanced Statistical Methods and Models
- Molecular Biology Techniques and Applications
- Cancer Diagnosis and Treatment
- COVID-19 epidemiological studies
- Control Systems and Identification
- Functional Brain Connectivity Studies
- Evolution and Genetic Dynamics
- Gaussian Processes and Bayesian Inference
- CRISPR and Genetic Engineering
- Soil Geostatistics and Mapping
- Species Distribution and Climate Change
- Genetic and phenotypic traits in livestock
- Single-cell and spatial transcriptomics
- Probabilistic and Robust Engineering Design
Università della Svizzera italiana
2017-2024
Società Italiana di Fisica
2024
University of Groningen
2014-2023
Vytautas Magnus University
2022
Wageningen University & Research
2018
Institute of Mathematics and Informatics
2015
University of Liverpool
2012
University College Dublin
2009
Queensland University of Technology
2009
Lancaster University
2006-2008
In this article, we introduce the concept of model uncertainty. We review frequentist and Bayesian ideas underlying selection, which serve as an introduction to rest special issue on ‘All models are wrong...’, a workshop under same name was held in March 2011 Groningen critically examined field statistical selection methods over past 40 years. briefly philosophical debate that is concerned with selection. present results questionnaire distributed participants workshop, showing has not yet...
Hematopoietic stem/progenitor cells (HSPCs) are capable of supporting the lifelong production blood exerting a wide spectrum functions. Lentiviral vector HSPC gene therapy generates human hematopoietic system stably marked at clonal level by integration sites (ISs). Using IS analysis, we longitudinally tracked >89,000 clones from 15 distinct bone marrow and peripheral lineages purified up to 4 years after transplant in four Wiskott-Aldrich syndrome patients treated with therapy. We measured...
An integrated account of the molecular changes occurring during process cellular aging is crucial towards understanding underlying mechanisms. Here, using novel culturing and computational methods as well latest analytical techniques, we mapped proteome transcriptome replicative lifespan budding yeast. With age, found primarily proteins involved in protein biogenesis to increase relative their transcript levels. Exploiting dynamic nature our data, reconstructed high-level directional...
Abstract Purpose: Patients with metastatic adenocarcinoma of unknown origin are a common clinical problem. Knowledge the primary site is important for their management, but histologically, such tumors appear similar. Better diagnostic markers needed to enable assignment metastases likely sites on pathologic samples. Experimental Design: Expression profiling 27 candidate was done using tissue microarrays and immunohistochemistry. In first (training) round, we studied 352 adenocarcinomas, from...
The concept of scale-free network has emerged as a powerful unifying paradigm in the study complex systems biology and physical social studies. Metabolic, protein, gene interaction networks have been reported to exhibit behavior based on analysis distribution number connections nodes. Here we 10 published datasets various biological interactions perform goodness-of-fit tests determine whether given data is drawn from power-law distribution. Our did not identify single that nonzero probability being
Decoding complex relationships among large numbers of variables with relatively few observations is one the crucial issues in science. One approach to this problem Gaussian graphical modeling, which describes conditional independence through presence or absence edges underlying graph. In paper, we introduce a novel and efficient Bayesian framework for model determination trans-dimensional Markov Chain Monte Carlo (MCMC) based on continuous-time birth-death process. We cover theory...
We propose a sparse high-dimensional time series chain graphical model for reconstructing genetic networks from gene expression data parametrized by precision matrix and autoregressive coefficient matrix. consider the steps as blocks or chains. The proposed approach explores patterns of contemporaneous dynamic interactions efficiently combining Gaussian models Bayesian networks. use penalized likelihood inference with smoothly clipped absolute deviation penalty to explore relationships among...
In the biomedical field, infrared (IR) spectroscopic studies can involve processing of data derived from many samples, divided into classes such as category tissue (e.g., normal or cancerous) patient identity. We require reliable methods to identify class-specific information on which wavenumbers, representing various molecular groups, are responsible for observed class groupings. Employing a prostate sample three regions (transition zone, peripheral and adjacent adenocarcinoma),...
We envisage a future research environment where digital data on species interactions are easily accessible and comprehensively cover all species, life stages habitats. To achieve this goal, we need from many sources, including the largely untapped potential of citizen science for mobilising utilising existing information interactions. Traditionally volunteers contributing occurrence have focused single‐species observations within one target taxon. make recommendations how to improve...
Despite theoretical arguments that so-called 'loop designs' for two-channel DNA microarray experiments are more efficient, biologists continue to use 'reference designs'. We describe two sets of with RNA from different biological systems (TPA-stimulated mammalian cells and Streptomyces coelicolor). In each case, both a loop reference design were used the same preparations aim studying their relative efficiency.The results these show (1) attains much higher precision than design, (2)...
Background Differences in within-person emotion dynamics may be an important source of heterogeneity depression. To investigate these dynamics, researchers have previously combined multilevel regression analyses with network representations. However, sparse methods, specifically developed for longitudinal analyses, not been applied. Therefore, this study used approach to population-level and individual-level healthy depressed persons compared method the approach. Methods Time-series data...
Summary Dupuytren disease is a fibroproliferative disorder with unknown aetiology that often progresses and eventually can cause permanent contractures of the fingers affected. We provide computationally efficient Bayesian framework to discover potential risk factors investigate which are jointly Our approach based on Gaussian copula graphical models, way underlying conditional independence structure variables in multivariate data mixed types. In particular, we combine semiparametric...
Abstract Background Network enrichment analysis is a powerful method, which allows to integrate gene with the information on relationships between genes that provided by networks. Existing tests for network deal only undirected networks, they can be computationally slow and are based normality assumptions. Results We propose NEAT, test analysis. The hypergeometric distribution, naturally arises as null distribution in this context. NEAT applied not undirected, but directed partially networks...
Graphical models provide powerful tools to uncover complicated patterns in multivariate data and are commonly used Bayesian statistics machine learning. In this paper, we introduce the R package BDgraph which performs structure learning for general undirected graphical (decomposable non-decomposable) with continuous, discrete, mixed variables. The efficiently implements recent improvements literature, including that of Mohammadi Wit (2015) Dobra (2018). To speed up computations,...
Graphical models are a powerful tool in modelling and analysing complex biological associations high-dimensional data. The R-package netgwas implements the recent methodological development on copula graphical to (i) construct linkage maps, (ii) infer disequilibrium networks from genotype data, (iii) detect genotype-phenotype networks. learns structure of ordinal data mixed ordinal-and-continuous Here, we apply functionality various multivariate example datasets taken literature demonstrate...
Abstract The microbiome constitutes a complex microbial ecology of interacting components that regulates important pathways in the host. Most communities at various body sites tend to share common substructures interactions, while also showing diversity related needs local environment. aim this paper is develop method for inferring both core and differences such microbiota systems. approach combines two elements: (i) random graph model generating networks across environments, capturing...
Hidden Markov random fields represent a complex hierarchical model, where the hidden latent process is an undirected graphical structure. Performing inference for such models difficult primarily because likelihood of states often unavailable. The main contribution this article to present approximate methods calculate large lattices based on exact smaller lattices. We introduce by relaxing some dependencies in and also extending tractable approximations likelihood, so-called pseudolikelihood...