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Displaying 1-14 out of 14 total
Intervention in Gene Regulatory Networks via Phenotypically Constrained Control Policies Based on Long-Run Behavior
Found in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
By Xiaoning Qian,Edward R. Dougherty
Issue Date:January 2012
pp. 123-136
A salient purpose for studying gene regulatory networks is to derive intervention strategies to identify potential drug targets and design gene-based therapeutic intervention. Optimal and approximate intervention strategies based on the transition probabil...
 
Conditioning-Based Modeling of Contextual Genomic Regulation
Found in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
By Edward R. Dougherty, Marcel Brun, Jeffrey M. Trent, Michael L. Bittner
Issue Date:April 2009
pp. 310-320
A more complete understanding of the alterations in cellular regulatory and control mechanisms that occur in the various forms of cancer has been one of the central targets of the genomic and proteomic methods that allow surveys of the abundance and/or sta...
 
The Granulometric Size Density in Filter Optimization
Found in: Graphics, Patterns and Images, SIBGRAPI Conference on
By Edward R. Dougherty
Issue Date:October 1999
pp. 257
Binary granulometric filters are constructed from parametrized unions and intersections of morphological openings. They are especially useful in filtering out clutter when an observed image is composed of a signal unioned with the clutter; however, their g...
 
Bayesian Robustness in the Control of Gene Regulatory Networks
Found in: Statistical Signal Processing, IEEE/SP Workshop on
By Ranadip Pal, Aniruddha Datta, Edward R. Dougherty
Issue Date:August 2007
pp. 31-35
The presence of noise and the availability of a limited number of samples prevent the transition probabilities of a gene regulatory network from being accurately estimated. Thus, it is important to study the effect of modeling errors on the final outcome o...
 
Which Control Gene Should be Used in Genetic Regulatory Networks?
Found in: Statistical Signal Processing, IEEE/SP Workshop on
By Golnaz Vahedi, Aniruddha Datta, Edward R. Dougherty
Issue Date:August 2007
pp. 6-10
Probabilistic Boolean Networks (PBNs) are rule-based models for gene regulatory networks. Previously, we proposed a method for finding the control policies with the highest effect on steady-state distributions of PBNs. To this end, the theory of infinite-h...
 
Evolving Feature Selection
Found in: IEEE Intelligent Systems
By Huan Liu, Edward R. Dougherty, Jennifer G. Dy, Kari Torkkola, Eugene Tuv, Hanchuan Peng, Chris Ding, Fuhui Long, Michael Berens, Lance Parsons, Zheng Zhao, Lei Yu, George Forman
Issue Date:November 2005
pp. 64-76
Feature selection is a preprocessing technique, commonly used on high-dimensional data, that studies how to select a subset or list of attributes or variables that are used to construct models describing data. Wide data sets, which have a huge number of fe...
 
On Reinforcement Learning in Genetic Regulatory Networks
Found in: Statistical Signal Processing, IEEE/SP Workshop on
By Babak Faryabi, Aniruddha Datta, Edward R. Dougherty
Issue Date:August 2007
pp. 11-15
The control of probabilistic Boolean networks as a model of genetic regulatory networks is formulated as an optimal stochastic control problem and has been solved using dynamic programming; however, the proposed methods fail when the number of genes in the...
 
Is There Correlation Between the Estimated and True Classification Errors in Small-Sample Settings?
Found in: Statistical Signal Processing, IEEE/SP Workshop on
By Blaise Hanczar, B. Jianping Hua, Edward R. Dougherty
Issue Date:August 2007
pp. 16-20
The validity of a classifier model, consisting of a trained classifier and it estimated error, depends upon the relationship between the estimated and true errors of the classifier. Absent a good error estimation rule, the classifier-error model lacks scie...
 
Inferring Connectivity of Genetic Regulatory Networks Using Information-Theoretic Criteria
Found in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
By Wentao Zhao, Erchin Serpedin, Edward R. Dougherty
Issue Date:April 2008
pp. 262-274
Recently, the concept of mutual information has been proposed for infering the structure of genetic regulatory networks from gene expression profiling. After analyzing the limitations of mutual information in inferring the gene-to-gene interactions, this p...
 
Incorporation of Biological PathwayKnowledge in the Construction of Priorsfor Optimal Bayesian Classification
Found in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
By Mohammad Shahrokh Esfahani,Edward R. Dougherty
Issue Date:January 2014
pp. 202-218
Small samples are commonplace in genomic/proteomic classification, the result being inadequate classifier design and poor error estimation. The problem has recently been addressed by utilizing prior knowledge in the form of a prior distribution on an uncer...
 
Design of Statistically Optimal Stack Filters
Found in: Graphics, Patterns and Images, SIBGRAPI Conference on
By Nina S. T. Hirata, Junior Barrera, Edward R. Dougherty
Issue Date:October 1999
pp. 265
Any gray-scale image can be represented as a ``stack'' of a decreasing sequence of binary images, obtained by thresholding the gray-scale image at each level. Stack filters are a special class of gray-scale image operators whose filtered images can be repr...
 
Fuzzy Intervention in Biological Phenomena
Found in: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
By Aniruddha Datta, Edward R. Dougherty, Hazem N. Nounou, Mohamed N. Nounou, Nader Meskin
Issue Date:November 2012
pp. 1819-1825
An important objective of modeling biological phenomena is to develop therapeutic intervention strategies to move an undesirable state of a diseased network toward a more desirable one. Such transitions can be achieved by the use of drugs to act on some ge...
     
Intervention in Gene Regulatory Networks via Phenotypically Constrained Control Policies Based on Long-Run Behavior
Found in: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
By Edward R. Dougherty, Xiaoning Qian
Issue Date:January 2012
pp. 123-136
A salient purpose for studying gene regulatory networks is to derive intervention strategies to identify potential drug targets and design gene-based therapeutic intervention. Optimal and approximate intervention strategies based on the transition probabil...
     
Conditioning-Based Modeling of Contextual Genomic Regulation
Found in: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
By Edward R. Dougherty, Jeffrey M. Trent, Marcel Brun, Michael L. Bittner
Issue Date:April 2009
pp. 310-320
A more complete understanding of the alterations in cellular regulatory and control mechanisms that occur in the various forms of cancer has been one of the central targets of the genomic and proteomic methods that allow surveys of the abundance and/or sta...
     
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