2388533
Probe Matrix Problems: Totally Balanced Matrices
Let be a class of 0/1-matrices. A 0/1/ i¾?-matrix Awhere the i¾?s induce a submatrix is a probe matrixof if the i¾?s in Acan be replaced by 0s and 1s such that Abecomes a member of . We show that for being the class of totally balanced matrices, it can be decided in polynomial time whether Ais a probe totally balanced matrix. On our route toward proving this main result, we also prove that so-called partitioned probe strongly chordal graphs and partitioned probe chordal bipartite graphs can be recognized in polynomial time.
9767043
The Computational Complexity of Avoiding Forbidden Submatrices by Row Deletions
We initiate a systematic study of the ROW DELETION(B) problem on matrices: Given an input matrix A and a fixed "forbidden submatrix" B, the task is to remove a minimum number of rows from A such that no row or column permutation of B occurs as a submatrix in the resulting matrix. An application of this problem can be found, for instance, in the construction of perfect phylogenies. Establishing a strong connection to variants of the NP-complete HITTING SET problem, we describe and analyze structural properties of B that make ROW DELETION(B)NP-complete. On the positive side, the close relation with HITTING SET problems yields constant-factor polynomial-time approximation algorithms and fixed-parameter tractability results.
14425036
Parameterized Intractability of Distinguishing Substring Selection
Abstract
A central question in computational biology is the design of genetic
markers to distinguish between two given sets of (DNA) sequences. This question is formalized as 
the NP-complete Distinguishing Substring Selection problem (DSSS for short) which asks, given a set of "good" strings and a set of "bad" strings, for a solution string which is, with respect to the Hamming metric, "away" from the good strings and "close" to the bad strings. More precisely, given integers dg, db, and L, we ask for a length-L string s such that s has Hamming distance at least dg to every length-L substring of the good strings and such that every bad string has a length-L substring with Hamming distance at most db to s. Studying the parameterized complexity of DSSS, we show that, already for binary alphabet, DSSS is W[1]-hard with respect to its natural parameters. This, in particular, implies that a recently given polynomial-time approximation scheme (PTAS) by Deng et al. cannot be replaced by a so-called efficient polynomial-time approximation scheme (EPTAS) unless an unlikely collapse in parameterized complexity theory occurs. This is seemingly the first computational biology problem for which such a border between PTAS (which exists) and EPTAS (which is unlikely to exist) could be established. By way of contrast, for a special case of DSSS, we present an exact fixed-parameter algorithm solving the problem efficiently. In this way we also exhibit a sharp border between fixed-parameter tractability and intractability results.

6020472
Compression-based fixed-parameter algorithms for feedback vertex set and edge bipartization
We show that the NP-complete Feedback Vertex Set problem, which asks for the smallest set of vertices to remove from a graph to destroy all cycles, is deterministically solvable in O(c^[email protected]?m) time. Here, m denotes the number of graph edges, k denotes the size of the feedback vertex set searched for, and c is a constant. We extend this to an algorithm enumerating all solutions in O(d^[email protected]?m) time for a (larger) constant d. As a further result, we present a fixed-parameter algorithm with runtime O(2^[email protected]?m^2) for the NP-complete Edge Bipartization problem, which asks for at most k edges to remove from a graph to make it bipartite.
14944633
On Exact and Approximation Algorithms for Distinguishing Substring Selection
The NP-complete Distinguishing Substring Selection problem (DSSS for short) asks, given a set of “good” strings and a set of “bad” strings, for a solution string which is, with respect to Hamming metric, “away” from the good strings and “close” to the bad strings.
1715544
Pattern matching for arc-annotated sequences
We study pattern matching for arc-annotated sequences. An O(nm) time algorithm is given for the problem to determine whether a length m sequence with nested arc annotation is an arc-preserving subsequence (aps) of a length n sequence with nested arc annotation, called APS(NESTED,NESTED). Arc-annotated sequences and, in particular, those with nested arc annotation are motivated by applications in RNA structure comparison. Our algorithm generalizes results for ordered tree inclusion problems and it is useful for recent fixed-parameter algorithms for LAPCS(NESTED,NESTED), which is the problem of computing a longest arc-preserving common subsequence of two sequences with nested arc annotations. In particular, the presented dynamic programming methodology implies a quadratic-time algorithm for an open problem posed by Vialette.
13379605
Protein Fold Recognition Through Application of Residual Dipolar Coupling Data
Residual dipolar coupling (RDC) represents one of the most exciting emerging NMR techniques for studying protein structures. However, solving a protein structure using RDC data alone is a highly challenging problem as it often requires that the starting structure model be close to the actual structure of a protein, for the structure calculation procedure to be effective. We report in this paper a computer program, RDC-PROSPECT, for identification of a structural homolog or analog of a target protein in PDB, which best matches the 15N-1H RDC data of the protein recorded in a single ordering medium. The identified structural homolog/analog can then be used as a starting model for RDC-based structure calculation. Since RDC-PROSPECT uses only RDC data and predicted secondary structure information, its performance is virtually independent of sequence similarity between a target protein and its structural homolog/analog, making it applicable to protein targets out of the scope of current protein threading techniques. We have tested RDC-PROSPECT on all 15N-1H RDC data (representing 33 proteins) available in the BMRB database and the literature. The program correctly identified the structural folds for approximately 80% of the target proteins, significantly better than previously reported results, and achieved an average alignment accuracy of 97.9% residues within 4-residue shift. Through a careful algorithmic design, RDC-PROSPECT is at least one order of magnitude faster than previously reported algorithms for principal alignment frame search, making our algorithm fast enough for large-scale applications.
5572698
Concept exchange: constructing interoperable electronic product catalogues in an emergent environment
Research in interoperability of electronic product catalogues has primarily focused on resolving semantic conflicts arisen from the heterogeneously designed electronic product catalogues. We argue that while existing integration strategies providing static connections between various heterogeneous catalogues over mediating ontologies, ontologies themselves exhibit heterogeneity and lack of evolvability. What's more, reclassifying terms to link public ontologies is very difficult to avoid inaccuracy problem that is critical to electronic commerce. This paper highlights the problems of flexibility, exactness and evolvability that have received little attention in the literature and provides an overview of the concept exchange approach to interoperability. It illustrates why this is able to better solve the identified problems, presents the different features compared with other approaches and suggests how the concept exchange framework is working.
6234679
A Model-based Approach to Hair Region Segmentation
Hair regions represent an important external feature in many tasks involving the processing of human faces. Currently, the task of locating the hair region in a facial image requires manual intervention. In this paper we examine the different aspects of the hair region segmentation problem and develop an automatic system for such a problem. The system incorporates the human knowledge on where the hair is usually located in a facial image. Segmentation is performed via the classification of image pixels and is based on both textural and geometrical features. Experiments have shown that the segmentation results are generally satisfactory and are at least comparable to the performance of manual extraction.
10065672
The waiting time distribution for a TDMA model with a finite buffer and state-dependent service
We obtain detailed analytic formulas for the density and probability distribution of the waiting time in a time-division multiple-access (TDMA) model with a finite buffer and state-dependent service. On successive intervals of length equal to the duration of a slot, the density is expressed as a linear combination of beta densities with positive coefficients. A recursive scheme, obtained by a matrix-analytic derivation, allows for the highly efficient computations of the coefficient sequences. An expression for the mean waiting time is derived using the classical queueing formula L=/spl lambda/W. We also demonstrate that our methodology provides a concise treatment of various special cases that have been studied over the past half century.
41178770
On matching coefficients
Abstract Explicit formulae are derived for the first four coefficients of the matching polynomial of a graph in terms of properties of the graph. An explicit formula is also derived for the number of triangles in the complement of a graph in terms of the parameters of the graph. Also, some extremal properties of regular multipartite graphs are identified.