Belief Networks for Bioinformatics
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[1] Aurélien Mazurie,et al. Gene networks inference using dynamic Bayesian networks , 2003, ECCB.
[2] Adam A. Margolin,et al. Reverse engineering of regulatory networks in human B cells , 2005, Nature Genetics.
[3] Luis M. de Campos,et al. A hybrid methodology for learning belief networks: BENEDICT , 2001, Int. J. Approx. Reason..
[4] Gregory F. Cooper,et al. The Computational Complexity of Probabilistic Inference Using Bayesian Belief Networks , 1990, Artif. Intell..
[5] L. Baum,et al. A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains , 1970 .
[6] Stuart J. Russell,et al. Dynamic bayesian networks: representation, inference and learning , 2002 .
[7] Sun-Mi Lee,et al. Bayesian networks for knowledge discovery in large datasets: basics for nurse researchers , 2003, J. Biomed. Informatics.
[8] Ernest Fraenkel,et al. High-resolution computational models of genome binding events , 2006, Nature Biotechnology.
[9] Ethem Alpaydin,et al. Introduction to machine learning , 2004, Adaptive computation and machine learning.
[10] David Maxwell Chickering,et al. Learning Equivalence Classes of Bayesian Network Structures , 1996, UAI.
[11] Paulo Cesar G. da Costa,et al. PR-OWL: A Framework for Probabilistic Ontologies , 2006, FOIS.
[12] Ben Taskar,et al. Rich probabilistic models for gene expression , 2001, ISMB.
[13] Kristian G. Olesen,et al. HUGIN - a Shell for Building Belief Universes for Expert Systems , 1989, IJCAI 1989.
[14] Michael I. Jordan. Learning in Graphical Models , 1999, NATO ASI Series.
[15] Marek J. Druzdzel,et al. A Hybrid Anytime Algorithm for the Construction of Causal Models From Sparse Data , 1999, UAI.
[16] Claudio J. Verzilli,et al. Bayesian graphical models for genomewide association studies. , 2006, American journal of human genetics.
[17] Zoubin Ghahramani,et al. A Bayesian network model for protein fold and remote homologue recognition , 2002, Bioinform..
[18] D. Griffeath,et al. Introduction to Random Fields , 2020, 2007.09660.
[19] David Page,et al. Biological applications of multi-relational data mining , 2003, SKDD.
[20] David Haussler,et al. Phylogenetic Hidden Markov Models , 2005 .
[21] Ron Shamir,et al. A Probabilistic Methodology for Integrating Knowledge and Experiments on Biological Networks , 2006, J. Comput. Biol..
[22] Judea Pearl,et al. A Theory of Inferred Causation , 1991, KR.
[23] Judea Pearl,et al. Evidential Reasoning Using Stochastic Simulation of Causal Models , 1987, Artif. Intell..
[24] Hilbert J. Kappen,et al. The Cluster Variation Method for Efficient Linkage Analysis on Extended Pedigrees , 2006, BMC Bioinformatics.
[25] David J. Spiegelhalter,et al. Local computations with probabilities on graphical structures and their application to expert systems , 1990 .
[26] Peter J. F. Lucas,et al. Bayesian networks in biomedicine and health-care , 2004, Artif. Intell. Medicine.
[27] Finn V. Jensen,et al. Bayesian Networks and Decision Graphs , 2001, Statistics for Engineering and Information Science.
[28] Sean R. Eddy,et al. Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids , 1998 .
[29] David Heckerman,et al. A Tutorial on Learning with Bayesian Networks , 1999, Innovations in Bayesian Networks.
[30] Peter Norvig,et al. Artificial Intelligence: A Modern Approach , 1995 .
[31] Nir Friedman,et al. Learning Bayesian Network Structure from Massive Datasets: The "Sparse Candidate" Algorithm , 1999, UAI.
[32] Kathryn B. Laskey. MEBN: A Logic for Open-World Probabilistic Reasoning , 2006 .
[33] Rolf Backofen,et al. A multiple-feature framework for modelling and predicting transcription factor binding sites , 2005, Bioinform..
[34] Kathryn B. Laskey,et al. Network Engineering for Complex Belief Networks , 1996, UAI.
[35] Dan Gusfield,et al. On the Complexity of Fundamental Computational Problems in Pedigree Analysis , 2003, J. Comput. Biol..
[36] Tommi S. Jaakkola,et al. Physical network models and multi-source data integration , 2003, RECOMB '03.
[37] Hilbert J. Kappen,et al. Linkage Analysis: A Bayesian Approach , 2002, ICANN.
[38] C S Jensen,et al. Blocking Gibbs sampling for linkage analysis in large pedigrees with many loops. , 1999, American journal of human genetics.
[39] Adnan Darwiche,et al. New Advances in Compiling CNF into Decomposable Negation Normal Form , 2004, ECAI.
[40] Dan Geiger,et al. Exact genetic linkage computations for general pedigrees , 2002, ISMB.
[41] D. Koller,et al. A module map showing conditional activity of expression modules in cancer , 2004, Nature Genetics.
[42] Kevin B. Korb,et al. Bayesian Artificial Intelligence , 2004, Computer science and data analysis series.
[43] Michael C. Horsch,et al. Dynamic Bayesian networks , 1990 .
[44] Arthur M. Lesk,et al. Introduction to bioinformatics , 2002 .
[45] Rina Dechter. Bucket elimination: a unifying framework for processing hard and soft constraints , 1996, CSUR.
[46] Haidong Wang,et al. Discovering molecular pathways from protein interaction and gene expression data , 2003, ISMB.
[47] Armin Shmilovici,et al. Identification of transcription factor binding sites with variable-order Bayesian networks , 2005, Bioinform..
[48] Doheon Lee,et al. Modularized learning of genetic interaction networks from biological annotations and mRNA expression data , 2005, Bioinform..
[49] Simon Whelan,et al. Statistical Methods in Molecular Evolution , 2005 .
[50] Peter J. Woolf,et al. Bayesian analysis of signaling networks governing embryonic stem cell fate decisions , 2005, Bioinform..
[51] Craig Boutilier,et al. Context-Specific Independence in Bayesian Networks , 1996, UAI.
[52] Michael P. Wellman. Fundamental Concepts of Qualitative Probabilistic Networks , 1990, Artif. Intell..
[53] Nir Friedman,et al. Inferring Cellular Networks Using Probabilistic Graphical Models , 2004, Science.
[54] Silja Renooij,et al. How to Elicit Many Probabilities , 1999, UAI.
[55] Adnan Darwiche,et al. A differential approach to inference in Bayesian networks , 2000, JACM.
[56] Xinkun Wang,et al. An effective structure learning method for constructing gene networks , 2006, Bioinform..
[57] A. Owen,et al. A Bayesian framework for combining heterogeneous data sources for gene function prediction (in Saccharomyces cerevisiae) , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[58] Manfred Jaeger,et al. Compiling relational Bayesian networks for exact inference , 2006, Int. J. Approx. Reason..
[59] Chris Harbron,et al. Heuristic algorithms for finding inexpensive elimination schemes , 1995 .
[60] Daphne Koller,et al. Probabilistic Discovery of Overlapping Cellular Processes and Their Regulation , 2005, J. Comput. Biol..
[61] Nir Friedman,et al. Learning Belief Networks in the Presence of Missing Values and Hidden Variables , 1997, ICML.
[62] R. M. Oliver,et al. Influence diagrams, belief nets and decision analysis , 1992 .
[63] Pierre Baldi,et al. Bioinformatics - the machine learning approach (2. ed.) , 2000 .
[64] Daphne Koller,et al. Rich probabilistic models for genomic data , 2004 .
[65] Dan Geiger,et al. Optimizing Exact Genetic Linkage Computations , 2004, J. Comput. Biol..
[66] David Page,et al. A Bayesian Network Approach to Operon Prediction , 2003, Bioinform..
[67] Silja Renooij,et al. From Qualitative to Quantitative Probabilistic Networks , 2002, UAI.
[68] Alun Thomas,et al. Multilocus linkage analysis by blocked Gibbs sampling , 2000, Stat. Comput..
[69] Carsten Riggelsen,et al. Approximation Methods for Efficient Learning of Bayesian Networks , 2008, Frontiers in Artificial Intelligence and Applications.
[70] Gregory F. Cooper,et al. A Bayesian method for the induction of probabilistic networks from data , 1992, Machine Learning.
[71] Simon Kasif,et al. Protein Secondary-Structure Modeling with Probabilistic Networks , 1993, ISMB.
[72] Nir Friedman,et al. Discovering Hidden Variables: A Structure-Based Approach , 2000, NIPS.
[73] Wei Chu,et al. Protein secondary structure prediction using sigmoid belief networks to parameterize segmental semi-Markov models , 2004, ESANN.
[74] Geoffrey Zweig,et al. Speech Recognition with Dynamic Bayesian Networks , 1998, AAAI/IAAI.
[75] Peter J.F. Lucas. Bayesian analysis, pattern analysis, and data mining in health care , 2004, Current opinion in critical care.
[76] M Silberstein,et al. Online system for faster multipoint linkage analysis via parallel execution on thousands of personal computers. , 2006, American journal of human genetics.
[77] Wai Lam,et al. LEARNING BAYESIAN BELIEF NETWORKS: AN APPROACH BASED ON THE MDL PRINCIPLE , 1994, Comput. Intell..
[78] Jill P. Mesirov,et al. Computational Biology , 2018, Encyclopedia of Parallel Computing.
[79] David Heckerman,et al. Learning With Bayesian Networks (Abstract) , 1995, ICML.
[80] Andrew W. Moore,et al. Learning evaluation functions for global optimization , 1998 .
[81] David J. Spiegelhalter,et al. Bayesian analysis in expert systems , 1993 .
[82] Judea Pearl,et al. Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.
[83] Jos W. H. M. Uiterwijk,et al. SequaPro: A Tool for Semi-Qualitative Decision Making , 2001 .
[84] Michal Linial,et al. Using Bayesian Networks to Analyze Expression Data , 2000, J. Comput. Biol..
[85] Paul P. Wang,et al. Advances to Bayesian network inference for generating causal networks from observational biological data , 2004, Bioinform..
[86] Dirk Drasdo,et al. Gene network inference from incomplete expression data: transcriptional control of hematopoietic commitment , 2006, Bioinform..
[87] Richard E. Neapolitan,et al. Learning Bayesian networks , 2007, KDD '07.
[88] Sean R. Eddy,et al. Profile hidden Markov models , 1998, Bioinform..
[89] Steffen L. Lauritzen,et al. Graphical Models for Genetic Analyses , 2003 .
[90] Gregory F. Cooper,et al. A Bayesian method for learning belief networks that contain hidden variables , 1993, Journal of Intelligent Information Systems.
[91] Hidde de Jong,et al. Modeling and Simulation of Genetic Regulatory Systems: A Literature Review , 2002, J. Comput. Biol..
[92] Nir Friedman,et al. The Bayesian Structural EM Algorithm , 1998, UAI.
[93] Robert G. Cowell,et al. Conditions Under Which Conditional Independence and Scoring Methods Lead to Identical Selection of Bayesian Network Models , 2001, UAI.
[94] David J. Spiegelhalter,et al. Probabilistic Networks and Expert Systems , 1999, Information Science and Statistics.
[95] P. Spirtes,et al. Causation, prediction, and search , 1993 .
[96] Jesper Tegnér,et al. Growing Bayesian network models of gene networks from seed genes , 2005, ECCB/JBI.