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14
Relating WholeGenome Expression Data with ProteinProtein Interactions
, 2002
"... this paper is the interactions occurring within specific complexes. These were obtained from the MIPS complexes catalog (Fellenberg et al. 2000), which represents a carefully annotated, comprehensive data set of protein complexes culled from the scientific literature. In addition, we looked at other ..."
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Cited by 153 (14 self)
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this paper is the interactions occurring within specific complexes. These were obtained from the MIPS complexes catalog (Fellenberg et al. 2000), which represents a carefully annotated, comprehensive data set of protein complexes culled from the scientific literature. In addition, we looked at other types of proteinprotein interactions from large "aggregated" data sets collecting many heterogeneous pairwise interactions. We collected these from the MIPS catalogs of physical and genetic interactions (Fellenberg et al. 2000), databases of interacting proteins (DIP and BIND) (Bader and Hogue 2000; Xenarios 2000), and a comprehensive collection of yeast twohybrid experiments (Cagney et al. 2000; lto et al. 2000; Schwikowski et al. 2000; Uetz et al. 2000; Uetz and Hughes 2000; lto et al. 2001). These interactions are subdivided into groups based on their method of discovery. They include physical interactions (e.g., collected through coimmunoprecipitation and copurification), genetic interactions (e.g., determined through genetic means such as synthetic lethality or suppression experiments), and yeast twohybrid pairs
A Bayesian system integrating expression data with sequence patterns for localizing proteins: comprehensive application to the yeast genome
 J. Mol. Biol
, 2000
"... Version Final We develop a probabilistic system for predicting the subcellular localization of proteins and estimating the relative population of the various compartments in yeast. Our system employs a Bayesian approach, updating a protein's probability of being in a compartment based on a diverse ..."
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Cited by 74 (21 self)
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Version Final We develop a probabilistic system for predicting the subcellular localization of proteins and estimating the relative population of the various compartments in yeast. Our system employs a Bayesian approach, updating a protein's probability of being in a compartment based on a diverse range of 30 features. These range from specific motifs (e.g. signal sequences or HDEL) to overall properties of a sequence (e.g. surface composition or isoelectric point) to wholegenome data (e.g. absolute mRNA expression levels or their fluctuations). The strength of our approach is the easy integration of many features, particularly the wholegenome expression data. We construct a training and testing set of ~1300 yeast proteins with an experimentally known localization from merging, filtering, and standardizing the annotation in the MIPS, SwissProt and YPD databases, and we achieve 75 % accuracy on individual protein predictions using this dataset. Moreover, we are able to estimate the relative protein population of the various compartments without requiring a definite localization for every protein. This approach, which is based on an
Inference of protein function from protein structure
 Structure
, 2005
"... sustainable homeostasis. These multiple levels of func ..."
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Cited by 49 (0 self)
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sustainable homeostasis. These multiple levels of func
Ghaoui, L.: Robust control of Markov decision processes with uncertain transition matrices
 Operations Research
"... doi 10.1287/opre.1050.0216 ..."
Bayesian models of cognition
"... For over 200 years, philosophers and mathematicians have been using probability theory to describe human cognition. While the theory of probabilities was first developed as a means of analyzing games of chance, it quickly took on a larger and deeper significance as a formal account of how rational a ..."
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Cited by 23 (1 self)
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For over 200 years, philosophers and mathematicians have been using probability theory to describe human cognition. While the theory of probabilities was first developed as a means of analyzing games of chance, it quickly took on a larger and deeper significance as a formal account of how rational agents should reason in situations of uncertainty
Robust Markov Decision Processes with Uncertain Transition Matrices
, 2004
"... Optimal solutions to Markov decision problems may be very sensitive with respect to the state transition probabilities. In many practical problems, the estimation of these probabilities is far from accurate. Hence, estimation errors are limiting factors in applying Markov decision processes to real ..."
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Cited by 6 (0 self)
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Optimal solutions to Markov decision problems may be very sensitive with respect to the state transition probabilities. In many practical problems, the estimation of these probabilities is far from accurate. Hence, estimation errors are limiting factors in applying Markov decision processes to realworld problems.
Assessing the Risk of Cumulative Burned Acreage Using the Poisson Probability Model 1
"... Resource managers are frequently concerned that the area burned by wildfire over time will impede achievement of land management objectives. Methods that use the Poisson probability model to quantify that risk are described. The methods require a concise statement of an adverse wildfire outcome and ..."
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Cited by 1 (0 self)
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Resource managers are frequently concerned that the area burned by wildfire over time will impede achievement of land management objectives. Methods that use the Poisson probability model to quantify that risk are described. The methods require a concise statement of an adverse wildfire outcome and information on fire frequencies and sizes. An example is presented that illustrates use of the risk assessment procedure to quantify the tradeoff between burned acreage risk and the cost of a fuels treatment project that reduces risk. Forest wildfire can pose a significant risk to achieving forest land management objectives. Water quality in municipal watersheds can be threatened by wildfire events. Anadromous fisheries can be endangered by the stream sedimentation resulting from runoff when rainstorms follow a large fire or even a series of smaller fires. Maintaining minimum acceptable levels of a wildlife habitat can also be at risk to the cumulative effects of wildfire. Sustained timber supplies are also at risk to wildfire events. For these reasons resource managers are concerned with the uncertainty posed by wildfire. Their concern centers on both the threat to meeting land management objectives and the costs of wildfire risk management. Accurately assessing the uncertainty posed by wildfire is frequently quite difficult, particularly if the outcomes of concern involve collections of random events. When adequate data are available, quantitative techniques can help in estimating the probabilities of wildfire outcomes involving joint random events, as has been shown for adverse fire movement (Wiitala and Carlton 1994). These procedures will help reduce the biases that can creep into purely subjective assessments of these probabilities (Cleaves 1994). This paper describes how probability theory can be used to assess the risk posed by wildfire to achieving resource management objectives. The procedures combine fire size and frequency data with the Poisson probability model to calculate the chance that burned area will exceed some threshold for a given area and period. A hypothetical example is presented that illustrates use of the risk assessment procedure to quantify the tradeoff between burned acreage risk and the cost of a fuels treatment project that reduces risk.
A robust thresholding algorithm for unimodal image histograms
, 2013
"... This article introduces a method to determine the threshold of unimodal image histograms in a robust manner. It is based on a piecewise linear regression that finds the two segments that fit the descending slope of the histogram. The algorithm gives a good estimation of the threshold, and is practic ..."
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Cited by 1 (0 self)
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This article introduces a method to determine the threshold of unimodal image histograms in a robust manner. It is based on a piecewise linear regression that finds the two segments that fit the descending slope of the histogram. The algorithm gives a good estimation of the threshold, and is practically insensitive to the noise distribution, to the quantity of objects to segment, and to random histogram fluctuations. Keywords automatic thresholding; image histogram; unimodal distribution; edge detection 1
Toronto, Canada. Active and Supportive ComputerMediated Resources for Studentto Student Conversations
"... Communication is a central aspect of human learning. Using the Probability Inquiry Environment (PIE) as an example, we examine how external representations (both textual and iconic) mediate facetoface conversations among students, and support productive mathematical discourse. We provide quantitati ..."
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Communication is a central aspect of human learning. Using the Probability Inquiry Environment (PIE) as an example, we examine how external representations (both textual and iconic) mediate facetoface conversations among students, and support productive mathematical discourse. We provide quantitative data that suggests that seventh grade students who used PIE learned some of the basic principles of probability. Two cases studies are provided that illustrate how communication, supported by computermediated representations, contributed to this success. The first case study demonstrates how the computer can actively prompt student conversations that lead to learning. The second case study examines how an animated graphical representation supported these productive conversations.