1529480
A compression algorithm for DNA sequences and its applications in genome comparison
We present a lossless compression algorithm, <italic>Gen-Compress</italic>, for DNA sequences, based on searching for approximate repeats. Our algorithm achieves the best compression ratios for benchmark DNA sequences, comparing to other DNA compression programs [3, 7]. Significantly better compression results show that the approximate repeats are one of the main hidden regularities in DNA sequences.
We then describe a theory of measuring the relatedness between two DNA sequences. We propose to use <italic>d</italic>(<italic>x</italic>, <italic>y</italic>) = 1 — <italic>K</italic>(<italic>x</italic>) - <italic>K</italic>(<italic>x</italic>|<italic>y</italic>)/<italic>K</italic>(<italic>xy</italic> to measure the distance of any two sequences, where <italic>K</italic>  stands for Kolmogorov complexity [5]. Here, <italic>K</italic>(<italic>x</italic>) - <italic>K</italic>(<italic>x</italic>|<italic>y</italic>) is the mutual information shared by <italic>x</italic> and <italic>y</italic>. But mutual information is not a distance, there is no triangle inequality. The distance <italic>d</italic>(<italic>x</italic>, <italic>y</italic>) is symmetric. It also satisfies the triangle inequality, and furthermore, it is universal [4].
It has not escaped our notice that the distance measure we have postulated can be immediately used to construct evolutionary trees from DNA sequences, especially those that cannot be aligned, such as complete genomes. With more and more genomes sequenced, constructing trees from genomes becomes possible [1, 2, 6, 8].  Kolmogorov complexity is not computable. We use <italic>GenCompress</italic> to approximate it. We present strong experimental support for this theory, and demonstrate its applicability by correctly constructing a 16S (18S) rRNA tree, and a whole genome tree for several species of bacteria. Larger scale experiments are underway at the University of Waterloo, with very promising results.
8099146
A new compression scheme for color-quantized images
An efficient compression scheme for color-quantized images based on progressive coding of color information has been developed. Instead of sorting color indexes into a linear list struc- ture, a binary-tree structure of color indexes is proposed. With this structure, the new algorithm can progressively recover an image from two colors to all of the colors contained in the original image, i.e., a lossless recovery is achieved. Experimental results showed that it can efficiently compress images in both lossy and lossless cases. Typically for color-quantized Lena image with 256 colors, the algorithm achieved 0.5 bpp below state-of-the-art lossless com- pression methods while preserving the efficient lossy compression. Such a compression scheme is very attractive to many applications that require the ability of fast browsing or progressive transmis- sion, and if necessary, to exactly recover the original image. Index Terms—Color-quantized images, data compression, index sorting, progressive refinement.
12010325
An information-based sequence distance and its application to whole mitochondrial genome phylogeny
MOTIVATION
Traditional sequence distances require an alignment and therefore are not directly applicable to the problem of whole genome phylogeny where events such as rearrangements make full length alignments impossible. We present a sequence distance that works on unaligned sequences using the information theoretical concept of Kolmogorov complexity and a program to estimate this distance.


RESULTS
We establish the mathematical foundations of our distance and illustrate its use by constructing a phylogeny of the Eutherian orders using complete unaligned mitochondrial genomes. This phylogeny is consistent with the commonly accepted one for the Eutherians. A second, larger mammalian dataset is also analyzed, yielding a phylogeny generally consistent with the commonly accepted one for the mammals.


AVAILABILITY
The program to estimate our sequence distance, is available at http://www.cs.cityu.edu.hk/~cssamk/gencomp/GenCompress1.htm. The distance matrices used to generate our phylogenies are available at http://www.math.uwaterloo.ca/~mli/distance.html.
1552680
Shared information and program plagiarism detection
A fundamental question in information theory and in computer science is how to measure similarity or the amount of shared information between two sequences. We have proposed a metric, based on Kolmogorov complexity, to answer this question and have proven it to be universal. We apply this metric in measuring the amount of shared information between two computer programs, to enable plagiarism detection. We have designed and implemented a practical system SID (Software Integrity Diagnosis system) that approximates this metric by a heuristic compression algorithm. Experimental results demonstrate that SID has clear advantages over other plagiarism detection systems. SID system server is online at http://software.bioinformatics.uwaterloo.ca/SID/.
12811258
A Parsimony Approach to Genome-Wide Ortholog Assignment
The assignment of orthologous genes between a pair of genomes is a fundamental and challenging problem in comparative genomics, since many computational methods for solving various biological problems critically rely on bona fide orthologs as input. While it is usually done using sequence similarity search, we recently proposed a new combinatorial approach that combines sequence similarity and genome rearrangement. This paper continues the development of the approach and unites genome rearrangement events and (post-speciation) duplication events in a single framework under the parsimony principle. In this framework, orthologous genes are assumed to correspond to each other in the most parsimonious evolutionary scenario involving both genome rearrangement and (post-speciation) gene duplication. Besides several original algorithmic contributions, the enhanced method allows for the detection of inparalogs. Following this approach, we have implemented a high-throughput system for ortholog assignment on a genome scale, called MSOAR, and applied it to the genomes of human and mouse. As the result will show, MSOAR is able to find 99 more true orthologs than the INPARANOID program did. We have also compared MSOAR with the iterated exemplar algorithm on simulated data and found that MSOAR performed very well in terms of assignment accuracy. These test results indiate that our approach is very promising for genome-wide ortholog assignment.
30296056
Computational inference of regulatory pathways in microbes
We present a computational protocol for inference of regulatory and signaling pathways in a microbial cell, through mining "high-throughput" biological data of various types, literature search, and computer-assisted human inference. This protocol consists of four key components: (a) construction of template pathways for microbial genomes related to the target genome, which have either been thoroughly studied or had a significant amount of relevant experimental data, (b) inference of target pathways for the target genome, by combining the template pathway models and target genome-specific information, (c) assignment of genes of the target genome to each individual functional roles in the pathway model, and (d) validation and refinement of the pathway models using pathway-specific experimental data or other information. To demonstrate the effectiveness of this procedure, we have applied this computational protocol to the construction of the phosphorus assimilation pathways in synechococcus WH8102. In this paper, we present a model of the core component of this pathway and provide our justification in support of the predicted model.
3210423
Verification Approach of Metropolis Design Framework for Embedded Systems
In this paper, we focus on the verification approach of Metropolis, an integrated design framework for heterogeneous embedded systems. The verification approach is based on the formal properties specified in Linear Temporal Logic (LTL) or Logic of Constraints (LOC). Designs may be refined due to synthesis or be abstracted for verification. An automatic abstraction propagation algorithm is used to simplify the design for specific properties. A user-defined starting point may also be used with automatic propagation. Two main verification techniques are implemented in Metropolis the formal verification utilizing the model checker Spin and the simulation trace checking with automatic generated checkers. Translation algorithms from specification models to verification models, as well as algorithms of generated checkers are discussed. We use several case studies to demonstrate our approach for verification of system level designs at multiple levels of abstraction.
8507685
Global and superlinear convergence of the smoothing Newton method and its application to general box constrained variational inequalities
The smoothing Newton method for solving a system of nonsmooth equations F(x) = 0, which may arise from the nonlinear complementarity problem, the variational inequality problem or other problems, can be regarded as a variant of the smoothing method. At the kth step, the nonsmooth function F is approximated by a smooth function f(.,∈ κ ), and the derivative of f(.,∈ κ ) at x k is used as the Newton iterative matrix. The merits of smoothing methods and smoothing Newton methods are global convergence and convenience in handling. In this paper, we show that the smoothing Newton method is also superlinearly convergent if F is semismooth at the solution and f satisfies a Jacobian consistency property. We show that most common smooth functions, such as the Gabriel-More function, have this property. As an application, we show that for box constrained variational inequalities if the involved function is P- uniform, the iteration sequence generated by the smoothing Newton method will converge to the unique solution of the problem globally and superlinearly (quadratically).
2587881
Isomap Based on the Image Euclidean Distance
Scientists find that the human perception is based on the similarity on the manifold of data set. Isometric feature mapping (isomap) is one of the representative techniques of manifold. It is intuitive, well understood and produces reasonable mapping results. However, if the input data for manifold learning are corrupted with noises, the isomap algorithm is topologically unstable. In this paper, we present an improved manifold learning method when the input data are images - the image Euclidean distance based isomap (imisomap), in which we use a new distance for images called image Euclidean distance (IMED). Experimental results demonstrate a consistent performance improvement of the algorithm imisomap over the traditional isomap based on Euclidean distance
7760066
Assertion-based design exploration of DVS in network processor architectures
With the scaling of technology and higher requirements on performance and functionality, power dissipation is becoming one of the major design considerations in the development of network processors. We use an assertion-based methodology for system-level power/performance analysis to study two dynamic voltage scaling (DVS) techniques, traffic-based DVS and execution-based DVS, in a network processor model. Using the automatically generated distribution analyzers, we analyze the power and performance distributions and study their trade-offs for the two DVS policies with different parameter settings, such as threshold values and window sizes. We discuss the optimal configurations of the two DVS policies under different design requirements. By a set of experiments, we show that the assertion-based trace analysis methodology is an efficient tool that can help a designer easily compare and study optimal architectural configurations in a large design space.
3763580
Extracting Features from Web Search Returned Hits for Hierarchical Classification