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Reducing FalsePositive Prediction of Minimotifs with a Genetic Interaction Filter
"... Background: Minimotifs are short contiguous peptide sequences in proteins that have known functions. At its simplest level, the minimotif sequence is present in a source protein and has an activity relationship with a target, most of which are proteins. While many scientists routinely investigate ne ..."
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Cited by 1 (0 self)
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new minimotif functions in proteins, the major webbased discovery tools have a high rate of falsepositive prediction. Any new approach that reduces falsepositives will be of great help to biologists. Methods and Findings: We have built three filters that use genetic interactions to reduce falsepositive
Improved prediction of signal peptides  SignalP 3.0
 J. MOL. BIOL.
, 2004
"... We describe improvements of the currently most popular method for prediction of classically secreted proteins, SignalP. SignalP consists of two different predictors based on neural network and hidden Markov model algorithms, where both components have been updated. Motivated by the idea that the cle ..."
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Cited by 656 (7 self)
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peptide discrimination improvement is mainly due to the elimination of false positive predictions, as well as the introduction of a new discrimination score for the neural network. The new method has also been benchmarked against other available methods. Predictions can be made at the publicly available
A direct approach to false discovery rates
, 2002
"... Summary. Multiplehypothesis testing involves guarding against much more complicated errors than singlehypothesis testing. Whereas we typically control the type I error rate for a singlehypothesis test, a compound error rate is controlled for multiplehypothesis tests. For example, controlling the ..."
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Cited by 773 (14 self)
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and then estimate its corresponding error rate. This new approach offers increased applicability, accuracy and power. We apply the methodology to both the positive false discovery rate pFDR and FDR, and provide evidence for its benefits. It is shown that pFDR is probably the quantity of interest over FDR. Also
The control of the false discovery rate in multiple testing under dependency
 Annals of Statistics
, 2001
"... Benjamini and Hochberg suggest that the false discovery rate may be the appropriate error rate to control in many applied multiple testing problems. A simple procedure was given there as an FDR controlling procedure for independent test statistics and was shown to be much more powerful than comparab ..."
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Cited by 1092 (16 self)
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comparable procedures which control the traditional familywise error rate. We prove that this same procedure also controls the false discovery rate when the test statistics have positive regression dependency on each of the test statistics corresponding to the true null hypotheses. This condition
Predicting Internet Network Distance with CoordinatesBased Approaches
 In INFOCOM
, 2001
"... In this paper, we propose to use coordinatesbased mechanisms in a peertopeer architecture to predict Internet network distance (i.e. roundtrip propagation and transmission delay) . We study two mechanisms. The first is a previously proposed scheme, called the triangulated heuristic, which is bas ..."
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Cited by 631 (6 self)
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In this paper, we propose to use coordinatesbased mechanisms in a peertopeer architecture to predict Internet network distance (i.e. roundtrip propagation and transmission delay) . We study two mechanisms. The first is a previously proposed scheme, called the triangulated heuristic, which
Predicting the Semantic Orientation of Adjectives
, 1997
"... We identify and validate from a large corpus constraints from conjunctions on the positive or negative semantic orientation of the conjoined adjectives. A loglinear regression model uses these constraints to predict whether conjoined adjectives are of same or different orientations, achiev ..."
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Cited by 473 (5 self)
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We identify and validate from a large corpus constraints from conjunctions on the positive or negative semantic orientation of the conjoined adjectives. A loglinear regression model uses these constraints to predict whether conjoined adjectives are of same or different orientations, achiev
Neural NetworkBased Face Detection
 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 1998
"... We present a neural networkbased upright frontal face detection system. A retinally connected neural network examines small windows of an image and decides whether each window contains a face. The system arbitrates between multiple networks to improve performance over a single network. We present ..."
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Cited by 1208 (22 self)
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a straightforward procedure for aligning positive face examples for training. To collect negative examples, we use a bootstrap algorithm, which adds false detections into the training set as training progresses. This eliminates the difficult task of manually selecting nonface training examples
Network Applications of Bloom Filters: A Survey
 Internet Mathematics
, 2002
"... Abstract. ABloomfilter is a simple spaceefficient randomized data structure for representing a set in order to support membership queries. Bloom filters allow false positives but the space savings often outweigh this drawback when the probability of an error is controlled. Bloom filters have been u ..."
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Cited by 519 (17 self)
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Abstract. ABloomfilter is a simple spaceefficient randomized data structure for representing a set in order to support membership queries. Bloom filters allow false positives but the space savings often outweigh this drawback when the probability of an error is controlled. Bloom filters have been
Expected stock returns and volatility
 Journal of Financial Economics
, 1987
"... This paper examines the relation between stock returns and stock market volatility. We find evidence that the expected market risk premium (the expected return on a stock portfolio minus the Treasury bill yield) is positively related to the predictable volatility of stock returns. There is also evid ..."
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Cited by 710 (10 self)
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This paper examines the relation between stock returns and stock market volatility. We find evidence that the expected market risk premium (the expected return on a stock portfolio minus the Treasury bill yield) is positively related to the predictable volatility of stock returns. There is also
High dimensional graphs and variable selection with the Lasso
 ANNALS OF STATISTICS
, 2006
"... The pattern of zero entries in the inverse covariance matrix of a multivariate normal distribution corresponds to conditional independence restrictions between variables. Covariance selection aims at estimating those structural zeros from data. We show that neighborhood selection with the Lasso is a ..."
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Cited by 733 (22 self)
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show that the proposed neighborhood selection scheme is consistent for sparse highdimensional graphs. Consistency hinges on the choice of the penalty parameter. The oracle value for optimal prediction does not lead to a consistent neighborhood estimate. Controlling instead the probability of falsely
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