D. Rossell

发表

Deep Sequence Analysis of Non-Small Cell Lung Cancer: Integrated Analysis of Gene Expression, Alternative Splicing, and Single Nucleotide Variations in Lung Adenocarcinomas with and without Oncogenic KRAS Mutations

Krishna R. Kalari, Jennifer M. Carr, Asha A. Nair, 2012, Front. Oncol..

Bayesian Model Selection in High-Dimensional Settings

V. Johnson, D. Rossell, 2012, Journal of the American Statistical Association.

Themis: Batch Preprocessing for Ultrahigh-Resolution Mass Spectra of Complex Mixtures.

D. Rossell, S. Spencer, Remy Gavard, 2017, Analytical chemistry.

On the use of non‐local prior densities in Bayesian hypothesis tests

V. Johnson, D. Rossell, 2010 .

MHC-I Genotype Restricts the Oncogenic Mutational Landscape

T. Ideker, H. Carter, W. Hildebrand, 2017, Cell.

On choosing mixture components via non‐local priors

M. Steel, D. Rossell, Jairo F'uquene, 2016, Journal of the Royal Statistical Society: Series B (Statistical Methodology).

A chemo-centric view of human health and disease

Patrick Aloy, Miquel Duran-Frigola, David Rossell, 2014, Nature Communications.

An Integrated Model of the Transcriptome of HER2-Positive Breast Cancer

Saurabh Baheti, Krishna R. Kalari, Kevin J. Thompson, 2013, PloS one.

GaGa : a Parsimonious and Flexible Hierarchical Model for Microarray Data Analysis

D. Rossell, 2007 .

Semi-Parametric Differential Expression Analysis via Partial Mixture Estimation

C. Scott, D. Rossell, R. Guerra, 2008, Statistical applications in genetics and molecular biology.

Pushing the analytical limits: new insights into complex mixtures using mass spectra segments of constant ultrahigh resolving power† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c9sc02903f

D. Stranz, D. Rossell, A. Guzmán, 2019, Chemical science.

Rhapso: Automatic stitching of mass segments from Fourier transform ion cyclotron resonance mass spectra.

D. Rossell, A. Guzmán, S. Spencer, 2019, Analytical chemistry.

Scalable Bayesian variable selection and model averaging under block orthogonal design

O. Papaspiliopoulos, D. Rossell, 2016, 1606.03749.

dKDM5/LID regulates H3K4me3 dynamics at the transcription-start site (TSS) of actively transcribed developmental genes

H. Auer, D. Rossell, Sílvia Pérez-Lluch, 2012, Nucleic acids research.

Chimeric tRNAs as tools to induce proteome damage and identify components of stress responses

D. Rossell, E. Martí, L. R. de Pouplana, 2009, Nucleic acids research.

A framework for posterior consistency in model selection

D. Rossell, 2018 .

Specification analysis for technology use and teenager well‐being: Statistical validity and a Bayesian proposal

D. Rossell, Christoph Semken, 2022, Journal of the Royal Statistical Society: Series C (Applied Statistics).

Graphical model inference with external network data

Piotr Zwiernik, D. Rossell, Li Li, 2022, 2210.11107.

Bayesian model selection and averaging with mombf

D. Rossell, 2017 .

KairosMS: A new solution for the processing of hyphenated ultrahigh resolution mass spectrometry data.

D. Rossell, S. Spencer, M. Barrow, 2020, Analytical chemistry.

Stromal gene expression defines poor-prognosis subtypes in colorectal cancer

Camille Stephan-Otto Attolini, Eduard Batlle, Elena Sancho, 2015, Nature Genetics.

Dependency of colorectal cancer on a TGF-β-driven program in stromal cells for metastasis initiation.

P. Jung, J. Massagué, X. Zhang, 2012, Cancer cell.

Nonlocal Priors for High-Dimensional Estimation

Donatello Telesca, David Rossell, D. Telesca, 2014, Journal of the American Statistical Association.

Screening designs for drug development.

Peter Müller, David Rossell, Gary L Rosner, 2007, Biostatistics.

Concentration of posterior probabilities and normalized L0 criteria in regression.

D. Rossell, 2020, 1806.04071.

Designing alternative splicing RNA-seq studies. Beyond generic guidelines

Camille Stephan-Otto Attolini, David Rossell, Víctor Peña, 2015, Bioinform..

Isolation and in vitro expansion of human colonic stem cells

Hans Clevers, Eduard Batlle, Elena Sancho, 2011, Nature Medicine.

Hybrid Periportal Hepatocytes Regenerate the Injured Liver without Giving Rise to Cancer

K. Deisseroth, Brian Hsueh, H. Carter, 2015, Cell.

BIG DATA AND STATISTICS: A STATISTICIAN'S PERSPECTIVE.

David Rossell, D. Rossell, 2014, Metode science studies journal.

The intestinal stem cell signature identifies colorectal cancer stem cells and predicts disease relapse.

Hans Clevers, Eduard Batlle, Elena Sancho, 2011, Cell stem cell.

Ectopic Expression of Germline Genes Drives Malignant Brain Tumor Growth in Drosophila

D. Rossell, S. Llamazares, A. Janic, 2010, Science.

Drosophila HP1c isoform interacts with the zinc-finger proteins WOC and Relative-of-WOC to regulate gene expression.

H. Auer, D. Rossell, F. Azorín, 2008, Genes & development.

QUANTIFYING ALTERNATIVE SPLICING FROM PAIRED-END RNA-SEQUENCING DATA.

David Rossell, Manuel Kroiss, Camille Stephan-Otto Attolini, 2014, The annals of applied statistics.

Confounder importance learning for treatment effect inference

Omiros Papaspiliopoulos, David Rossell, Miquel Torrens-i-Dinares, 2021, 2110.00314.

chroGPS, a global chromatin positioning system for the functional analysis and visualization of the epigenome

O. Reina, D. Rossell, F. Azorín, 2013, Nucleic acids research.

Heterogeneous Large Datasets Integration Using Bayesian Factor Regression

David Rossell, Richard S. Savage, Alejandra Avalos-Pacheco, 2018, Bayesian Analysis.

Characterizing MHC-I Genotype Predictive Power for Oncogenic Mutation Probability in Cancer Patients.

D. Rossell, M. Slifker, J. Font-Burgada, 2020, Methods in molecular biology.

Bayesian block-diagonal variable selection and model averaging.

O. Papaspiliopoulos, D. Rossell, 2017, Biometrika.

Revealing the Reactivity of Individual Chemical Entities in Complex Mixtures: the Chemistry Behind Bio-Oil Upgrading

D. Rossell, M. Witt, S. Spencer, 2022, Analytical chemistry.

htSeqTools: high-throughput sequencing quality control, processing and visualization in R

Oscar Flores, Camille Stephan-Otto Attolini, David Rossell, 2012, Bioinform..

Concentration of Posterior Model Probabilities and Normalized L0 Criteria

David Rossell, D. Rossell, 2018, Bayesian Analysis.

Tractable Bayesian Variable Selection: Beyond Normality

David Rossell, Francisco J Rubio, D. Rossell, 2016, Journal of the American Statistical Association.

Dependence in elliptical partial correlation graphs

Piotr Zwiernik, D. Rossell, 2020, Electronic Journal of Statistics.

Approximate Laplace approximations for scalable model selection

A. Bhattacharya, D. Rossell, Oriol Abril, 2020, Journal of the Royal Statistical Society: Series B (Statistical Methodology).

Additive Bayesian Variable Selection under Censoring and Misspecification

David Rossell, Francisco Javier Rubio, D. Rossell, 2019, Statistical Science.

General Bayesian loss function selection and the use of improper models

D. Rossell, Jack Jewson, 2021, Journal of the Royal Statistical Society: Series B (Statistical Methodology).

Tractable Bayesian Variable Selection: Beyond Normality

D. Rossell, F. Rubio, 2016, Journal of the American Statistical Association.

mombf package vignette

D. Rossell, 2009 .

Bayes Factors Based on Test Statistics Under Order Restrictions

Valen E. Johnson, Veerabhadran Baladandayuthapani, David Rossell, 2008 .