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.
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.
14019711
Fixed-parameter tractability and data reduction for multicut in trees
We study an NP-complete (and MaxSNP-hard) communication problem on tree networks, the so-called Multicut in Trees: given an undirected tree and some pairs of nodes of the tree, find out whether there is a set of at most k tree edges whose removal separates all given pairs of nodes. Multicut has been intensively studied for trees as well as for general graphs mainly from the viewpoint of polynomialtime approximation algorithms. By way of contrast, we provide a simple fixed-parameter algorithm for Multicut in Trees showing ∗Supported by the Deutsche Forschungsgemeinschaft (DFG), Emmy Noether research group PIAF (fixed-parameter algorithms), NI 369/4. Parts of this work have been done while the authors were at the Universität Tübingen.
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.
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.

8023010
PROSPECT-PSPP: an automatic computational pipeline for protein structure prediction
Knowledge of the detailed structure of a protein is crucial to our understanding of the biological functions of that protein. The gap between the number of solved protein structures and the number of protein sequences continues to widen rapidly in the post-genomics era due to long and expensive processes for solving structures experimentally. Computational prediction of structures from amino acid sequence has come to play a key role in narrowing the gap and has been successful in providing useful information for the biological research community. We have developed a prediction pipeline, PROSPECT-PSPP, an integration of multiple computational tools, for fully automated protein structure prediction. The pipeline consists of tools for (i) preprocessing of protein sequences, which includes signal peptide prediction, protein type prediction (membrane or soluble) and protein domain partition, (ii) secondary structure prediction, (iii) fold recognition and (iv) atomic structural model generation. The centerpiece of the pipeline is our threading-based program PROSPECT. The pipeline is implemented using SOAP (Simple Object Access Protocol), which makes it easier to share our tools and resources. The pipeline has an easy-to-use user interface and is implemented on a 64-node dual processor Linux cluster. It can be used for genome-scale protein structure prediction. The pipeline is accessible at http://csbl.bmb.uga.edu/protein_pipeline.
15601163
High Efficiency Digital Halftoning with Two-Element Error Kernel
A high efficiency and good quality error-diffused halftoning is proposed in this paper. An objective halftone image quality evaluation method based on human visual system obtained by least-mean-square is also introduced. The error diffusion algorithm, first introduced by Floyd and Steinberg in 1975, is currently the most popular method of digital halftoning. However, some annoying shortcomings, such as patches of regular textures, worm effect, and computational complexity still need to be improved. Ostromoukhov proposed a three-element error diffusion solving the problems described above, and achieved excellent performance. In this paper, we further reduced the complexity with the proposed two-element error diffusion by cooperating with the proposed LMS-trained quality evaluation. As demonstrated in experiments, the proposed technique further reduced the complexity by 33% compared to Ostromoukhov's method, and it is still comparable in image quality.
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.
43856313
The waiting time distribution for a TDMA model with a finite buffer
Detailed analytic formulas for the density and probability distribution of the waiting time in a TDMA model with a finite buffer is obtained. On successive intervals of length equal to the duration of a slot, the density is expressed as (infinite) linear combinations 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.
14231112
A Transparent Collaborative Integration Approach for Ad Hoc Product Data
Product data integration is an essential issue for many e-commerce interoperable business systems. Core to this issue is how to maintain semantic consistency between heterogeneous product data that are semantically different in structure, concept and context. To resolve the issue, this paper proposes a transparent collaborative integration approach, which is built on a layered framework of messaging, structure, concept and collaboration. The key to this framework is three collaboration engines, which resolves semantic consistency issues between millions of contextual vocabularies of SMEs