357440
Scaling up accurate phylogenetic reconstruction from gene-order data
MOTIVATION
Phylogenetic reconstruction from gene-order data has attracted increasing attention from both biologists and computer scientists over the last few years. Methods used in reconstruction include distance-based methods (such as neighbor-joining), parsimony methods using sequence-based encodings, Bayesian approaches, and direct optimization. The latter, pioneered by Sankoff and extended by us with the software suite GRAPPA, is the most accurate approach, but cannot handle more than about 15 genomes of limited size (e.g. organelles).


RESULTS
We report here on our successful efforts to scale up direct optimization through a two-step approach: the first step decomposes the dataset into smaller pieces and runs the direct optimization (GRAPPA) on the smaller pieces, while the second step builds a tree from the results obtained on the smaller pieces. We used the sophisticated disk-covering method (DCM) pioneered by Warnow and her group, suitably modified to take into account the computational limitations of GRAPPA. We find that DCM-GRAPPA scales gracefully to at least 1000 genomes of a few hundred genes each and retains surprisingly high accuracy throughout the range: in our experiments, the topological error rate rarely exceeded a few percent. Thus, reconstruction based on gene-order data can now be accomplished with high accuracy on datasets of significant size.
1484935
Improving genome rearrangement phylogeny using sequence-style parsimony
The study of genome rearrangements, the evolutionary events that change the order and strandedness of genes within genomes, presents new opportunities for discoveries about deep evolutionary events. The best software so far, GRAPPA, solves breakpoint and inversion phylogenies by scoring each tree topology through iterative improvements of internal node gene orders. We find that the greedy hill-climbing approach means the accuracy is limited because of multiple local optima. To address this problem, we propose integration GRAPPA with MPME, a string encoding of gene adjacency relationships whose optimal internal node assignments can be determined globally in polynomial time, to provide better initializations for GRAPPA. In simulation studies, the new algorithm yields shorter tree lengths and better accuracy in phylogeny reconstruction.
14427891
Phylogenetic reconstruction from arbitrary gene-order data
Phylogenetic reconstruction from gene-order data has attracted attention from both biologists and computer scientists over the last few years. So far, our software suite GRAPPA is the most accurate approach, but it requires that all genomes have identical gene content, with each gene appearing exactly once in each genome. Some progress has been made in handling genomes with unequal gene content, both in terms of computing pair-wise genomic distances and in terms of reconstruction. In this paper, we present a new approach for computing the median of three arbitrary genomes and apply it to the reconstruction of phylogenies from arbitrary gene-order data. We implemented these methods within GRAPPA and tested them on simulated datasets under various conditions as well as on a real dataset of chloroplast genomes; we report the results of our simulations and our analysis of the real dataset and compare them to reconstructions made by using neighbor-joining and using the original GRAPPA on the same genomes with equalized gene contents. Our new approach is remarkably accurate both in simulations and on the real dataset, in contrast to the distance-based approaches and to reconstructions using the original GRAPPA applied to equalized gene contents.
8476755
Succinct Text Indexes on Large Alphabet
In this paper, we first consider some properties of strings who have the same suffix array. Next, we design a data structure to support rank and select operations on an alphabet Σ using nlog|Σ| + (nlog|Σ|) bits in O(log|Σ|) time for a text of length n. It also supports an extended rank, namely rank≤, such that rank$^{\rm \leq}_{\alpha}$(T,i) returns the number of letters which are smaller than α in string T, plus the number of αs up to position i. Also, it runs in O(log|Σ|) time. By this structure, we implement the DAWG succinctly. The main structure only takes nlog|Σ| + o(nlog|Σ|) bits and supports basic operations of DAWG efficiently.
1746627
Inversion Medians Outperform Breakpoint Medians in Phylogeny Reconstruction from Gene-Order Data
Phylogeny reconstruction from gene-order data has attracted much attention over the last few years. The two software packages used for that purpose, BPAnalysis and GRAPPA, both use so-called breakpoint medians in their computations. Some of our past results indicate that using inversion scores rather than breakpoint scores in evaluating trees leads to the selection of better trees. On that basis, we conjectured that phylogeny reconstructions could be improved by using inversion medians, which minimize evolutionary distance under an inversions-only model of genome rearrangement. Recent algorithmic developments have made it possible to compute inversion medians for problems of realistic size.Our experimental studies unequivocally show that inversion medians are strongly preferable to breakpoint medians in the context of phylogenetic reconstruction from gene-order data. Improvements are most pronounced in the reconstruction of ancestral genomes, but are also evident in the topological accuracy of the reconstruction as well as, surprisingly, in the overall running time. Improvements are strongest for small average distances along tree edges and for evolutionary scenarios with a preponderance of inversion events, but occur in all cases, including evolutionary scenarios with high proportions of transpositions.All of our tests were run using our GRAPPA package, available (under GPL) at www.cs.unm.edu/~moret/GRAPPA; the next release will include the inversion median software we used in this study. The software used includes RevMed, developed by the authors and available at www.cs.unm.edu/~acs, and A. Caprara's inversion median code, generously made available for testing.
39775533
Research of Atomic and Anonymous Electronic Commerce Protocol
Atomicity and anonymity are the two important requirements for application in electronic commerce. However absolutely anonymity may lead to confliction with law enforcement, e.g. blackmailing or money laundering. Therefore, it is important to design systems satisfying both atomicity and revocable anonymity. Based on the concept of two-phase commitment, we realize atomicity in electronic transaction with the Trusted Third Part as coordinator. Also we develops Brands' fair signature model, propose a method to enable not only anonymity but also owner-trace and money-trace.
10131271
Hierarchical Classification of Documents with Error Control
Classification is a function that matches a new object with one of the predefined classes. Document classification is characterized by the large number of attributes involved in the objects (documents). The traditional method of building a single classifier to do all the classification work would incur a high overhead. Hierarchical classification is a more efficient method -- instead of a single classifier, we use a set of classifiers distributed over a class taxonomy, one for each internal node. However, once a misclassification occurs at a high level class, it may result in a class that is far apart from the correct one. An existing approach to coping with this problem requires terms also to be arranged hierarchically. In this paper, instead of overhauling the classifier itself, we propose mechanisms to detect misclassification and take appropriate actions. We then discuss an alternative that masks the misclassification based on a well known software fault tolerance technique. Our experiments show our algorithms represent a good trade-off between speed and accuracy in most applications.
6797006
Exploring web browser history comparisons
This work explores how comparing web navigation histories between two people and presenting the results to them might allow them to gain insight about each other. We developed a prototype that presents web matches sorted according to frequency, recency, and web site. Interviews with users of the prototype suggest that common interests and preferences can be inferred from these comparisons.
17319139
Unobtrusive but invasive: using screen recording to collect field data on computer-mediated interaction
We explored the use of computer screen plus audio recording as a methodological approach for collecting empirical data on how teams use their computers to coordinate work. Screen recording allowed unobtrusive collecting of a rich record of actual computer work activity in its natural work setting. The embedded nature of screen recording on laptops made it easy to follow the user's mobility among various work sites. However, the invasiveness of seeing all of the user's interactions with and through the computer raised privacy concerns that made it difficult to find people to agree to participate in this type of detailed study. We discuss measures needed to develop trust with the researchers to enable access to this rich, empirical data of computer usage in the field.
4300632
Keyword Extraction Using Support Vector Machine
This paper is concerned with keyword extraction. By keyword extraction, we mean extracting a subset of words/phrases from a document that can describe the ‘meaning' of the document. Keywords are of benefit to many text mining applications. However, a large number of documents do not have keywords and thus it is necessary to assign keywords before enjoying the benefit from it. Several research efforts have been done on keyword extraction. These methods make use of the ‘global context information', which makes the performance of extraction restricted. A thorough and systematic investigation on the issue is thus needed. In this paper, we propose to make use of not only ‘global context information', but also ‘local context information' for extracting keywords from documents. As far as we know, utilizing both ‘global context information' and ‘local context information' in keyword extraction has not been sufficiently investigated previously. Methods for performing the tasks on the basis of Support Vector Machines have also been proposed in this paper. Features in the model have been defined. Experimental results indicate that the proposed SVM based method can significantly outperform the baseline methods for keyword extraction. The proposed method has been applied to document classification, a typical text mining processing. Experimental results show that the accuracy of document classification can be significantly improved by using the keyword extraction method.