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Big data need big theory too

Philosophical transactions of the Royal Society of London. Series A: Mathematical, physical, and engineering sciences, 2016-11, Vol.374 (2080), p.20160153

2016

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Incorporating biological prior knowledge for Bayesian learning via maximal knowledge-driven information priors

BMC bioinformatics, 2017-12, Vol.18 (Suppl 14), p.552-552, Article 552

2017

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Scalable optimal Bayesian classification of single-cell trajectories under regulatory model uncertainty

BMC genomics, 2019-06, Vol.20 (Suppl 6), p.435-435, Article 435

2019

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The impact of function perturbations in Boolean networks

Bioinformatics, 2007-05, Vol.23 (10), p.1265-1273

2007

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Optimal clustering with missing values

BMC bioinformatics, 2019-06, Vol.20 (Suppl 12), p.321-321, Article 321

2019

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Accurate and reliable cancer classification based on probabilistic inference of pathway activity

PloS one, 2009-12, Vol.4 (12), p.e8161-e8161

2009

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Is cross-validation valid for small-sample microarray classification?

Bioinformatics, 2004-02, Vol.20 (3), p.374-380

2004

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A Nonmathematical Review of Optimal Operator and Experimental Design for Uncertain Scientific Models with Application to Genomics

Current genomics, 2019-01, Vol.20 (1), p.16-23

Dougherty, Edward R

2019

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Optimal Bayesian Transfer Learning

IEEE transactions on signal processing, 2018-07, Vol.66 (14), p.3724-3739

2018

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A Bayesian robust Kalman smoothing framework for state-space models with uncertain noise statistics

EURASIP journal on advances in signal processing, 2018-09, Vol.2018 (1), p.1-17, Article 55

2018

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Inferring gene regulatory networks from time series data using the minimum description length principle

Bioinformatics, 2006-09, Vol.22 (17), p.2129-2135

2006

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Optimal clustering under uncertainty

PloS one, 2018-10, Vol.13 (10), p.e0204627-e0204627

2018

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Bayesian Minimum Mean-Square Error Estimation for Classification Error-Part II: Linear Classification of Gaussian Models

IEEE transactions on signal processing, 2011-01, Vol.59 (1), p.130-144

2011

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Quantifying the Multi-Objective Cost of Uncertainty

IEEE access, 2021-01, Vol.9, p.80351-80359

2021

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Experimental Design via Generalized Mean Objective Cost of Uncertainty

IEEE access, 2019, Vol.7, p.2223-2230

2019

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Gene perturbation and intervention in probabilistic Boolean networks

Bioinformatics, 2002-10, Vol.18 (10), p.1319-1331

2002

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Intervention in context-sensitive probabilistic Boolean networks

Bioinformatics, 2005-04, Vol.21 (7), p.1211-1218

2005

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Gene selection: a Bayesian variable selection approach

Bioinformatics (Oxford, England), 2003, Vol.19 (1), p.90-97

2003

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Probabilistic boolean networks predict transcription factor targets to induce transdifferentiation

iScience, 2022-09, Vol.25 (9), p.104951-104951, Article 104951

2022

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Knowledge-driven learning, optimization, and experimental design under uncertainty for materials discovery

Patterns (New York, N.Y.), 2023-11, Vol.4 (11), p.100863-100863, Article 100863

2023

Volltextzugriff (PDF)

Bayesian Regression With Network Prior: Optimal Bayesian Filtering Perspective

IEEE transactions on signal processing, 2016-12, Vol.64 (23), p.6243-6253

2016

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Pathway-based analyses of gene expression profiles at low doses of ionizing radiation

Frontiers in bioinformatics, 2024-05, Vol.4, p.1280971-1280971

2024

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Accelerated search for BaTiO₃-based piezoelectrics with vertical morphotropic phase boundary using Bayesian learning

Proceedings of the National Academy of Sciences - PNAS, 2016-11, Vol.113 (47), p.13301-13306

2016

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Synthetic data for design and evaluation of binary classifiers in the context of Bayesian transfer learning

Data in brief, 2022-06, Vol.42 (C), p.108113-108113, Article 108113

2022

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Performance of feature-selection methods in the classification of high-dimension data

Pattern recognition, 2009-03, Vol.42 (3), p.409-424

2009

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Big data need big theory too

Incorporating biological prior knowledge for Bayesian learning via maximal knowledge-driven information priors

Scalable optimal Bayesian classification of single-cell trajectories under regulatory model uncertainty

The impact of function perturbations in Boolean networks

Optimal clustering with missing values

Accurate and reliable cancer classification based on probabilistic inference of pathway activity

Is cross-validation valid for small-sample microarray classification?

A Nonmathematical Review of Optimal Operator and Experimental Design for Uncertain Scientific Models with Application to Genomics

Optimal Bayesian Transfer Learning

A Bayesian robust Kalman smoothing framework for state-space models with uncertain noise statistics

Inferring gene regulatory networks from time series data using the minimum description length principle

Optimal clustering under uncertainty

Bayesian Minimum Mean-Square Error Estimation for Classification Error-Part II: Linear Classification of Gaussian Models

Quantifying the Multi-Objective Cost of Uncertainty

Experimental Design via Generalized Mean Objective Cost of Uncertainty

Gene perturbation and intervention in probabilistic Boolean networks

Intervention in context-sensitive probabilistic Boolean networks

Gene selection: a Bayesian variable selection approach

Probabilistic boolean networks predict transcription factor targets to induce transdifferentiation

Knowledge-driven learning, optimization, and experimental design under uncertainty for materials discovery

Bayesian Regression With Network Prior: Optimal Bayesian Filtering Perspective

Pathway-based analyses of gene expression profiles at low doses of ionizing radiation

Accelerated search for BaTiO₃-based piezoelectrics with vertical morphotropic phase boundary using Bayesian learning

Synthetic data for design and evaluation of binary classifiers in the context of Bayesian transfer learning

Performance of feature-selection methods in the classification of high-dimension data

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