4523050
Determination of Local Statistical Significance of Patterns in Markov Sequences with Application to Promoter Element Identification
High-level eukaryotic genomes present a particular challenge to the computational identification of transcription factor binding sites (TFBSs) because of their long noncoding regions and large numbers of repeat elements. This is evidenced by the noisy results generated by most current methods. In this paper, we present a p-value-based scoring scheme using probability generating functions to evaluate the statistical significance of potential TFBSs. Furthermore, we introduce the local genomic context into the model so that candidate sites are evaluated based both on their similarities to known binding sites and on their contrasts against their respective local genomic contexts. We demonstrate that our approach is advantageous in the prediction of myogenin and MEF2 binding sites in the human genome. We also apply LMM to large-scale human binding site sequences in situ and found that, compared to current popular methods, LMM analysis can reduce false positive errors by more than 50% without compromising sensitivity. This improvement will be of importance to any subsequent algorithm that aims to detect regulatory modules based on known PSSMs.
14960694
Comparative analysis of gene sets in the gene ontology space under the multiple hypothesis testing framework
The gene ontology (GO) resource can be used as a powerful tool to uncover the properties shared among, and specific to, a list of genes produced by high-throughput functional genomics studies, such as microarray studies. In the comparative analysis of several gene lists, researchers maybe interested in knowing which GO terms are enriched in one list of genes but relatively depleted in another. Statistical tests such as Fisher's exact test or Chi-square test can be performed to search for such GO terms. However, because multiple GO terms are tested simultaneously, individual p-values from individual tests do not serve as good indicators for picking GO terms. Furthermore, these multiple tests are highly correlated, usual multiple testing procedures that work under an independence assumption are not applicable. In this paper we introduce a procedure, based on false discovery rate (FDR), to treat this correlated multiple testing problem. This procedure calculates a moderately conserved estimator of q-value for every GO term. We identify the GO terms with q-values that satisfy a desired level as the significant GO terms. This procedure has been implemented into the GoSurfer software. GoSurfer is a windows based graphical data mining tool. It is freely available at http://www.gosurfer.org.
21945290
Statistical cerebrovascular segmentation in three-dimensional rotational angiography based on maximum intensity projections
Segmentation of three-dimensional rotational angiography (3D-RA) can provide quantitative 3D morphological information of vasculature. The expectation maximization-(EM-) based segmentation techniques have been widely used in the medical image processing community, because of the implementation simplicity, and computational efficiency of the approach. In a brain 3D-RA, vascular regions usually occupy a very small proportion (around 1%) inside an entire image volume. This severe imbalance between the intensity distributions of vessels and background can lead to inaccurate statistical modeling in the EM-based segmentation methods, and thus adversely affect the segmentation quality for 3D-RA. In this paper we present a new method for the extraction of vasculature in 3D-RA images. The new method is fully automatic and computationally efficient. As compared with the original 3D-RA volume, there is a larger proportion (around 20%) of vessels in its corresponding maximum intensity projection (MIP) image. The proposed method exploits this property to increase the accuracy of statistical modeling with the EM algorithm. The algorithm takes an iterative approach to compiling the 3D vascular segmentation progressively with the segmentation of MIP images along the three principal axes, and use a winner-takes-all strategy to combine the results obtained along individual axes. Experimental results on 12 3D-RA clinical datasets indicate that the segmentations obtained by the new method exhibit a high degree of agreement to the ground truth segmentations and are comparable to those produced by the manual optimal global thresholding method.
206572113
Measuring distance between program features
We present a metric to determine the distance between the features of a software system. Such a measurement can elucidate how features of the system being examined are close to each other. We first use an execution slice-based technique to identify a set of code (basic blocks in our case) that is used to implement each feature. Then, depending on whether the execution frequency of each block is considered during the construction of such sets of code, a static as well as a dynamic distance is computed for each pair of features. These two types of distance differ in that the former computes the distance between two features only by how these features are implemented in the system, while the latter also takes into account how each feature is executed based on a user's operational profile. In other words, the static distance quantitatively gives the closeness of two features from the system implementation point of view, whereas the dynamic distance presents such closeness from the users' execution point of view. To illustrate the use of our metric, we report a case study on a Symbolic Hierarchical Automated Reliability and Performance Evaluator (SHARPE). The results of our study suggest that the distance metric discussed in this paper can provide a good measurement, in a quantitative way, of how close two program features are. Such information can also serve as a good start to understanding how a modification made to one feature is likely to affect other features.
19382997
Fast Evaluation of the Elementary Functions in Single Precision
In this paper we introduce a new method for the fast evaluation of the elementary functions in single precision based on the evaluation of truncated Taylor series using a difference method. We assume the availability of large and fast (at least for read purposes) memory. We call this method the ATA (Add-Table lookup-Add) method. As the name implies, the hardware required for the method are adders (both two/ and multi/operand adders) and fast tables. For IEEE single precision numbers our initial estimates indicate that we can calculate the basic elementary functions, namely reciprocal, square root, logarithm, exponential, trigonometric and inverse trigonometric functions, within the latency of two to four floating point multiplies. >
11803699
An agent-based testing approach for Web applications
In recent years, Web applications have grown so quickly that they have already become crucial to the success of businesses. However, since they are built on Internet and open standard technologies, Web applications bring new challenges to researchers, such as dynamic behaviors, heterogeneous representations, novel control flow and data flow mechanisms, etc. In this paper, we propose an agent-based approach for Web application testing. While the agent-based framework greatly reduces the complexity of Web applications, a four-level dataflow test approach can be employed to perform structure testing on them. In this approach, data flow analysis is performed as function level testing, function cluster level testing, object level testing, and Web application level testing, from low abstract level to high abstract level. Each test agent in the framework takes charge of the testing in an abstract level for a particular type of Web document or object.
2760120
Mutation Testing Applied to Validate SDL Specifications
Mutation Testing is an error-based criterion that provides mechanisms to evaluate the quality of a test set and/or to generate test sets. This criterion, originally proposed to program testing, has also been applied to specification testing. In this paper, we propose the application of Mutation Testing for testing SDL specifications. We define a mutant operator set for SDL that intends to model errors related to the behavioral aspect of the processes, the communication among processes, the structure of the specification and some intrinsic characteristics of SDL. A testing strategy to apply the mutant operators to test SDL specifications is proposed. We illustrate our approach using the Alternating-Bit protocol.