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

[1]  Read OnlineThe,et al.  The Biology of Cancer , 2022, Nature.

[2]  Edward R. Dougherty,et al.  Constructing Pathway-Based Priors within a Gaussian Mixture Model for Bayesian Regression and Classification , 2019, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[3]  Martin Krzywinski,et al.  Points of Significance: Classification and regression trees , 2017, Nature Methods.

[4]  E. Dougherty,et al.  An Optimization-Based Framework for the Transformation of Incomplete Biological Knowledge into a Probabilistic Structure and Its Application to the Utilization of Gene/Protein Signaling Pathways in Discrete Phenotype Classification , 2015, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[5]  Minoru Kanehisa,et al.  KEGG as a reference resource for gene and protein annotation , 2015, Nucleic Acids Res..

[6]  Roger D. Peng,et al.  What is the question? , 2015, Science.

[7]  J. Ferlay,et al.  International trends in lung cancer incidence by histological subtype: adenocarcinoma stabilizing in men but still increasing in women. , 2014, Lung cancer.

[8]  Edward R. Dougherty,et al.  Scientific knowledge is possible with small-sample classification , 2013, EURASIP J. Bioinform. Syst. Biol..

[9]  Yan Zhang,et al.  Research and applications: An integrated approach to identify causal network modules of complex diseases with application to colorectal cancer , 2013, J. Am. Medical Informatics Assoc..

[10]  Edward R. Dougherty,et al.  Optimal classifiers with minimum expected error within a Bayesian framework - Part I: Discrete and Gaussian models , 2013, Pattern Recognit..

[11]  Edward R. Dougherty,et al.  Optimal classifiers with minimum expected error within a Bayesian framework - Part II: Properties and performance analysis , 2013, Pattern Recognit..

[12]  Shabaz Mohammed,et al.  Comparative Phosphoproteomic Analysis of Checkpoint Recovery Identifies New Regulators of the DNA Damage Response , 2013, Science Signaling.

[13]  Benjamin E. Gross,et al.  Integrative Analysis of Complex Cancer Genomics and Clinical Profiles Using the cBioPortal , 2013, Science Signaling.

[14]  Byung-Jun Yoon,et al.  Identification of Robust Pathway Markers for Cancer through Rank-Based Pathway Activity Inference , 2013, Adv. Bioinformatics.

[15]  Oliver Sawodny,et al.  Properties of Boolean networks and methods for their tests , 2013, EURASIP J. Bioinform. Syst. Biol..

[16]  Hyung-Seok Choi,et al.  A pathway-based classification of breast cancer integrating data on differentially expressed genes, copy number variations and MicroRNA target genes , 2012, Molecules and cells.

[17]  Luonan Chen,et al.  Identifying Responsive Modules by Mathematical Programming: An Application to Budding Yeast Cell Cycle , 2012, PloS one.

[18]  M. Kon,et al.  Pathway-based classification of cancer subtypes , 2012, Biology Direct.

[19]  Anton J. Haug.  Introduction to Monte Carlo Methods , 1994 .

[20]  James O. Berger,et al.  Objective Priors for Discrete Parameter Spaces , 2012 .

[21]  Benjamin E. Gross,et al.  The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. , 2012, Cancer discovery.

[22]  Jianping Hua,et al.  Tracking transcriptional activities with high-content epifluorescent imaging. , 2012, Journal of biomedical optics.

[23]  Wei Pan,et al.  Bayesian Joint Modeling of Multiple Gene Networks and Diverse Genomic Data to Identify Target Genes of a Transcription Factor. , 2012, The annals of applied statistics.

[24]  Jeff Shrager,et al.  A Novel Classification of Lung Cancer into Molecular Subtypes , 2012, PloS one.

[25]  David A. Gell,et al.  Metallothionein (MT) -I and MT-II Expression Are Induced and Cause Zinc Sequestration in the Liver after Brain Injury , 2012, PloS one.

[26]  S. Kauffman,et al.  Evolution before genes , 2012, Biology Direct.

[27]  Edward R. Dougherty,et al.  Probabilistic reconstruction of the tumor progression process in gene regulatory networks in the presence of uncertainty , 2011, BMC Bioinformatics.

[28]  Amin Zollanvari,et al.  The Illusion of Distribution-Free Small-Sample Classification in Genomics , 2011, Current genomics.

[29]  J. Nevins.  Pathway-based classification of lung cancer: a strategy to guide therapeutic selection. , 2011, Proceedings of the American Thoracic Society.

[30]  Qizhai Li,et al.  Robust joint analysis allowing for model uncertainty in two-stage genetic association studies , 2011, BMC Bioinformatics.

[31]  A. Datta,et al.  From biological pathways to regulatory networks , 2010, 49th IEEE Conference on Decision and Control (CDC).

[32]  Alfred O. Hero,et al.  Distributed Covariance Estimation in Gaussian Graphical Models , 2010, IEEE Transactions on Signal Processing.

[33]  Michael L. Gatza,et al.  A pathway-based classification of human breast cancer , 2010, Proceedings of the National Academy of Sciences.

[34]  Wei Pan,et al.  Network‐based genomic discovery: application and comparison of Markov random‐field models , 2010, Journal of the Royal Statistical Society. Series C, Applied statistics.

[35]  E. Dougherty,et al.  Accurate and Reliable Cancer Classification Based on Probabilistic Inference of Pathway Activity , 2009, PloS one.

[36]  Michael L. Bittner,et al.  Conditioning-Based Modeling of Contextual Genomic Regulation , 2009, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[37]  Alfred O. Hero,et al.  Covariance Estimation in Decomposable Gaussian Graphical Models , 2009, IEEE Transactions on Signal Processing.

[38]  Wei Pan,et al.  Network-based support vector machine for classification of microarray samples , 2009, BMC Bioinformatics.

[39]  Doheon Lee,et al.  Inferring Pathway Activity toward Precise Disease Classification , 2008, PLoS Comput. Biol..

[40]  Wei Pan,et al.  BIOINFORMATICS ORIGINAL PAPER doi:10.1093/bioinformatics/btm612 Systems biology , 2022 .

[41]  Petre Stoica,et al.  On Estimation of Covariance Matrices With Kronecker Product Structure , 2008, IEEE Transactions on Signal Processing.

[42]  Harry Vrieling,et al.  Analysis of Gene Expression Using Gene Sets Discriminates Cancer Patients with and without Late Radiation Toxicity , 2006, PLoS medicine.

[43]  Aurélien Naldi,et al.  Dynamical analysis of a generic Boolean model for the control of the mammalian cell cycle , 2006, ISMB.

[44]  Jorge Nocedal,et al.  An interior algorithm for nonlinear optimization that combines line search and trust region steps , 2006, Math. Program..

[45]  Carsten Peterson,et al.  Signal transduction pathway profiling of individual tumor samples , 2005, BMC Bioinformatics.

[46]  R. Preuss,et al.  Entropic Priors , 2003, physics/0312131.

[47]  Edward R. Dougherty,et al.  Probabilistic Boolean networks: a rule-based uncertainty model for gene regulatory networks , 2002, Bioinform..

[48]  Hoon Kim,et al.  Monte Carlo Statistical Methods , 2000, Technometrics.

[49]  Jorge Nocedal,et al.  An Interior Point Algorithm for Large-Scale Nonlinear Programming , 1999, SIAM J. Optim..

[50]  Arnold Zellner,et al.  Models, prior information, and Bayesian analysis☆ , 1996 .

[51]  L. Wasserman,et al.  The Selection of Prior Distributions by Formal Rules , 1996 .

[52]  Corinna Cortes,et al.  Support-Vector Networks , 1995, Machine Learning.

[53]  G. Casella,et al.  Explaining the Gibbs Sampler , 1992 .

[54]  S. D. Hill,et al.  Least-informative Bayesian prior distributions for finite samples based on information theory , 1989, Proceedings of the 28th IEEE Conference on Decision and Control,.

[55]  Silviu Guiasu,et al.  The principle of maximum entropy , 1985 .

[56]  J. Rissanen.  A UNIVERSAL PRIOR FOR INTEGERS AND ESTIMATION BY MINIMUM DESCRIPTION LENGTH , 1983 .

[57]  D. Luenberger,et al.  Estimation of structured covariance matrices , 1982, Proceedings of the IEEE.

[58]  S. Kauffman.  Metabolic stability and epigenesis in randomly constructed genetic nets. , 1969, Journal of theoretical biology.

[59]  Edwin T. Jaynes,et al.  Prior Probabilities , 1968, Encyclopedia of Machine Learning.

[60]  E. Jaynes.  Information Theory and Statistical Mechanics , 1957 .

[61]  H. Jeffreys.  An invariant form for the prior probability in estimation problems , 1946, Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences.

[62]  Doreen Eichel,et al.  Learning And Soft Computing Support Vector Machines Neural Networks And Fuzzy Logic Models , 2016 .

[63]  Trevor J Pugh,et al.  Mutational heterogeneity in cancer and the search for new cancer genes , 2014 .

[64]  E. Dougherty,et al.  Incorporation of Biological Pathway Knowledge in the Construction of Priors for Optimal Bayesian Classification , 2014, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[65]  Edward R. Dougherty,et al.  Bayesian Minimum Mean-Square Error Estimation for Classification Error—Part I: Definition and the Bayesian MMSE Error Estimator for Discrete Classification , 2011, IEEE Transactions on Signal Processing.

[66]  L. Breiman.  Random Forests , 2001, Machine Learning.

[67]  EMILY J. Hale.  The question. , 2000, Nursing.

[68]  Hiroyuki Ogata,et al.  KEGG: Kyoto Encyclopedia of Genes and Genomes , 1999, Nucleic Acids Res..

[69]  Nader Ebrahimi,et al.  Measuring Informativeness of Data by Entropy and Variance , 1999 .

[70]  C. Rodr.  Entropic Priors , 1991 .

[71]  J. Bernardo.  Reference Posterior Distributions for Bayesian Inference , 1979 .

[72]  H. David.  International trends. , 1968, Journal of psychiatric nursing and mental health services.

[73]  U. G. Dailey.  Cancer,Facts and Figures about. , 2022, Journal of the National Medical Association.