22347603
Two supervised learning approaches for name disambiguation in author citations
10820274
Simultaneous and exact interval estimates for the contrast of two groups based on an extremely high dimensional variable: application to mass spec data
MOTIVATION
Analysis of high-throughput proteomic/genomic data, in particular, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) data and microarray data, has led to a multitude of techniques aimed at identifying potential biomarkers. Most of the statistical techniques for comparing two groups are based on qualitative measures such as P-value. A quantitative way such as interval estimation for the contrasts of two groups is more appealing.


RESULTS
We have devised a simultaneous confidence bands method capable of detecting potential biomarkers, while controlling for overall confidence coverage level, in high-dimensional datasets that discriminate two treatment groups using a permutation scheme. For example, for the SELDI-TOF MS data, we deal with the entire spectrum simultaneously and construct (1 - alpha) confidence bands for the mean differences between groups. Furthermore, peaks were identified based on the maximal differences between the groups as determined by the confidence bands. The analysis method herein described gives both qualitative (P-value) and quantitative data (magnitude of difference). The Clinical Proteomics Programs Databank's ovarian cancer dataset and data from in-house samples containing known spiked-in proteins were analyzed. We were able to identify potential biomarkers similar to those described in previous analysis of the ovarian cancer data, however, while these markers are highly significant between cancer and normal groups, our analysis indicated the absolute difference between the two groups was minimal. In addition, we found additional markers than those previously described with greater differences in average intensities. The proposed confidence bands method successfully detected the spiked-in peaks, as well as, secondary peaks generated by adducts and double-charged species. We also illustrate our method utilizing paired gene expression data from a prostate cancer microarray experiment by constructing confidence bands for the fold changes between cancer and normal samples.


AVAILABILITY
R-package, 'seie.zip' (license: GNU GPL), is publiclly available at http://research2.dfci.harvard.edu/dfci/MS_spike-in_data/
1216815
Efficient Processing of Updates in Dynamic XML Data
It is important to process the updates when nodes are inserted into or deleted from the XML tree. All the existing labeling schemes have high update cost, thus in this paper we propose a novel Compact Dynamic Binary String (CDBS) encoding to efficiently process the updates. CDBS has two important properties which form the foundations of this paper: (1) CDBS supports that codes can be inserted between any two consecutive CDBS codes with the orders kept and without re-encoding the existing codes; (2) CDBS is orthogonal to specific labeling schemes, thus it can be applied broadly to different labeling schemes or other applications to efficiently process the updates. We report our experimental results to show that our CDBS is superior to previous approaches to process updates in terms of the number of nodes to re-label and the time for updating.
3813961
Using MMQ Model for Performance Simulation of Storage Area Network
The infrastructures of SANs are complex, and the implementations/designs of SANs are varied. So finding a proper modeling method to analysis and simulate SAN performance in a systemic/consistent way is very important for the work efficiency of SAN designers and performance tuners. This paper proposes a methodology of using a multi-tier multiserver queue (MMQ) network system to model a SAN system, which can be generalized to different SAN instances neatly, and be used for both performance analysis and simulation. Besides the main idea and high-level MMQ model, the application of this method is illustrated by constructing a software simulator, which is also designed and implemented in a systemic and reusable style. The simulation validation shows that maximum error range is less than 10%. So we can consider this method a sound solution for the quick performance design comparison and analysis of SAN.
29028846
Reuse or Never Reuse the Deleted Labels in XML Query Processing Based on Labeling Schemes
To facilitate the XML query processing, several kinds of labeling schemes have been proposed. Based on the labeling schemes, the ancestor-descendant and parent-child relationships in XML queries can be quickly determined without accessing the original XML file. Recently, more researches are focused on how to update the labels when nodes are inserted into the XML. However how to process the deleted labels are not discussed previously. We think that the deleted labels can be processed in two different directions: (1) reuse all the deleted labels to control the label size increasing speed and improve the query performance; (2) never reuse the deleted labels to query different versions of the XML data based on labeling schemes. In this paper, we firstly introduce our previous work, called QED, which can completely avoid the re-labeling in XML updates. Secondly based on QED we propose a new algorithm, called Reuse, which can reuse all the deleted labels to control the label size increasing speed; meanwhile the Reuse algorithm can completely avoid the re-labeling also. Thirdly to query different versions of the XML data, we propose another new algorithm, called NeverReuse, which is the only approach that never reuses any deleted labels. Extensive experimental results show that the algorithms proposed in this paper can control the label size increasing speed when reusing all the deleted labels, and is the only approach to query different versions of the XML data based on labeling schemes.
46337154
Minimum cross entropy thresholding
Abstract The threshold selection problem is solved by minimizing the cross entropy between the image and its segmented version. The cross entropy is formulated in a pixel-to-pixel basis between the two images and a computationally attractive algorithm employing the histogram is developed. Without making a priori assumptions about the population distribution, this method provides an unbiased estimate of a binarized version of the image in an information theoretic sense.
206571122
On Half-Transitive Metacirculant Graphs of Prime-Power Order
In this paper, infinitely many graphs of large valency which are half-transitive (that is vertex- and edge-transitive but not arc-transitive) are constructed, and a complete classification is given of half-transitive metacirculant graphs of order a p-power and valency less than 2p, where p is a prime. In particular, it is shown that, for any odd prime p, integers n?3 and k?2 such that k divides p?1, there are exactly (pn?2?1)/2+pn?3?1 nonisomorphic connected half-transitive metacirculants of order pn and valency 2k.