33918362
Approximation Algorithms for the Selection of Robust Tag SNPs
Recent studies have shown that the chromosomal recombination only takes places at some narrow hotspots. Within the chromosomal region between these hotspots (called haplotype block), little or even no recombination occurs, and a small subset of SNPs (called tag SNPs) is sufficient to capture the haplotype pattern of the block. In reality, the tag SNPs may be genotyped as missing data, and we may fail to distinguish two distinct haplotypes due to the ambiguity caused by missing data. In this paper, we formulate this problem as finding a set of SNPs (called robust tag SNPs) which is able to tolerate missing data. To find robust tag SNPs, we propose two greedy and one LP-relaxation algorithms which give solutions of \((m+1)\ln\frac{K(K-1)}{2}\), \(\ln((m+1)\frac{K(K-1)}{2})\), and O(mln K) approximation respectively, where m is the number of SNPs allowed for missing data and K is the number of patterns in the block.
8315237
Local Lazy Regression: Making Use of the Neighborhood to Improve QSAR Predictions
Traditional quantitative structure-activity relationship (QSAR) models aim to capture global structure-activity trends present in a data set. In many situations, there may be groups of molecules which exhibit a specific set of features which relate to their activity or inactivity. Such a group of features can be said to represent a local structure-activity relationship. Traditional QSAR models may not recognize such local relationships. In this work, we investigate the use of local lazy regression (LLR), which obtains a prediction for a query molecule using its local neighborhood, rather than considering the whole data set. This modeling approach is especially useful for very large data sets because no a priori model need be built. We applied the technique to three biological data sets. In the first case, the root-mean-square error (RMSE) for an external prediction set was 0.94 log units versus 0.92 log units for the global model. However, LLR was able to characterize a specific group of anomalous molecules with much better accuracy (0.64 log units versus 0.70 log units for the global model). For the second data set, the LLR technique resulted in a decrease in RMSE from 0.36 log units to 0.31 log units for the external prediction set. In the third case, we obtained an RMSE of 2.01 log units versus 2.16 log units for the global model. In all cases, LLR led to a few observations being poorly predicted compared to the global model. We present an analysis of why this was observed and possible improvements to the local regression approach.
2057857
Gene-finding via tandem mass spectrometry
We propose a new gene-finding methodology that combines high performance liquid chromatograph (HPLC)-tandem mass spectrometry experiments with a fast computer algorithm to locate coding regions and introns. Proteins are first extracted from cells and digested by enzymes, and then the resulting peptides are separated and analyzed by HPLC-tandem mass spectrometry. We designed an algorithm to find DNA coding sequences, corresponding to open reading frames (ORF), in the genome such that their translated amino acid sequences are optimally correlated with these tandem mass spectra. In this algorithm, we also allow one gap, corresponding to an intron, between two DNA coding sequences, such that their concatenation becomes one coding sequence. Finally, the algorithm assembles these candidate coding sequences and introns into gene structures. Our algorithm was implemented to predict genes on 4 contigs with a total of 123 kbps using two sets of simulated digestion- HPLC-tandem mass spectrometry data of 2523 Caenorhabditis elegans Chromosome IV proteins, digested by trypsin and Asp-N respectively. Among 15 annotated genes in the forward strand, all 98 exons are hit by the predicted no-gap coding sequences, and 60 out of 83 introns are correctly predicted. We also tested gene structure prediction in a contig containing 3 genes. Combining splicing site predictions with predicted coding sequences and introns, we found all 3 gene structures.
10712046
Algorithms for identifying protein cross-links via tandem mass spectrometry
Cross-linking technology combined with tandem mass spectrometry (MS-MS) is a powerful method that provides a rapid solution to the discovery of protein-protein interactions and protein structures. We studied the problem of detecting cross-linked peptides and cross-linked amino acids from tandem mass spectral data. Our method consists of two steps: the first step finds two protein subsequences whose mass sum equals a given mass measured from the mass spectrometry; and the second step finds the best cross-linked amino acids in these two peptide sequences that are optimally correlated to a given tandem mass spectrum. We designed fast and space-efficient algorithms for these two steps, and implemented and tested them on experimental data of cross-linked Hemoglobin proteins.
31567164
Prediction of protein function using protein-protein interaction data
Assigning functions to novel proteins is one of the most important problems in the post-genomic era. We develop a novel approach that applies the theory of Markov random fields to infer a protein's functions using protein-protein interaction data and the functional annotations of its interaction protein partners. For each function of interest and a protein, we predict the probability that the protein has that function using Bayesian approaches. Unlike in other available approaches for protein annotation where a protein has or does not have a function of interest, we give a probability for having the function. This probability indicates how confident we are about the prediction. We apply our method to predict cellular functions (43 categories including a category "others") for yeast proteins defined in the Yeast Proteome Database, using the protein-protein interaction data from the Munich Information Center for Protein Sequences. We show that our approach outperforms other available methods for function prediction based on protein interaction data.
2822926
Sorting with Fixed-length Reversals
Abstract A popular puzzle TOP-SPIN consists of a permutation of 20 numbered disks on an oval track, with a turnstile capable of reversing a string of 4 consecutive disks. The goal is to sort the disks into identity permutation using reversals. We consider the more general case of sorting n element permutations with a turnstile of size k. The problem of computing the reversal distances is of considerable importance in reconstructing the evolutionary history of the genome. The minimum reversal sequence sorting the one genome to another corresponds to the most likely evolutionary path between them. We give a complete solution for all n and k, of the number of equivalence classes of n-permutations under k-reversal, for both permutations and circular permutations. We also prove the upper and lower bounds on the reversal distances between two permutations.
1214419
On the Axiomatizability of Priority
This paper studies the equational theory of bisimulation equivalence over the process algebra BCCSP extended with the priority operator of Baeten, Bergstra and Klop. It is proven that, in the presence of an infinite set of actions, bisimulation equivalence has no finite, sound, ground-complete equational axiomatization over that language. This negative result applies even if the syntax is extended with an arbitrary collection of auxiliary operators, and motivates the study of axiomatizations using conditional equations. In the presence of an infinite set of actions, it is shown that, in general, bisimulation equivalence has no finite, sound, ground-complete axiomatization consisting of conditional equations over BCCSP. Sufficient conditions on the priority structure over actions are identified that lead to a finite, ground-complete axiomatization of bisimulation equivalence using conditional equations
1816267
From Region Encoding To Extended Dewey: On Efficient Processing of XML Twig Pattern Matching
Finding all the occurrences of a twig pattern in an XML database is a core operation for efficient evaluation of XML queries. A number of algorithms have been proposed to process a twig query based on region encoding labeling scheme. While region encoding supports efficient determination of structural relationship between two elements, we observe that the information within a single label is very limited. In this paper, we propose a new labeling scheme, called extended Dewey. This is a powerful labeling scheme, since from the label of an element alone, we can derive all the elements names along the path from the root to the element. Based on extended Dewey, we design a novel holistic twig join algorithm, called TJFast. Unlike all previous algorithms based on region encoding, to answer a twig query, TJFast only needs to access the labels of the leaf query nodes. Through this, not only do we reduce disk access, but we also support the efficient evaluation of queries with wildcards in branching nodes, which is very difficult to be answered by algorithms based on region encoding. Finally, we report our experimental results to show that our algorithms are superior to previous approaches in terms of the number of elements scanned, the size of intermediate results and query performance.
15877902
Tree logic with recursion and model checking algorithm
Semi-structured data plays an increasingly important role in the exchange of information between globally distributed applications, which invokes renewed interests in typed programming languages that can manipulate tree-like data structures. Tree logic, inherited from ambient logic, is introduced as the formal foundation of related programming language and type systems. In this paper, we introduce recursion into such logic system, which can describe the tree data more clearly and concisely. By making a distinction between proposition and predicate, a concise semantics interpretation for our modal logic is given. We also develop a model checking algorithm for the logic without . operator. The correctness of the algorithm is shown. Such work can be seen as the basis of the semi-structured data processing language and more flexible type system.
17694458
Optimal broadcasting on incomplete star graph interconnection networks
Broadcasting is an important collective communication operation in many applications which use parallel computing. In this paper, we focus on designing broadcasting algorithms for general incomplete star graphs. We propose two optimal one-to-all broadcasting algorithms for incomplete star graphs with a single-port communication model. An incomplete star graph with N nodes, where (n - 1)! < N < n!, is a subgraph of an n-dimensional star graph. The first scheme is single-message one-to-all broadcasting that takes O(nlogn) steps. The second one is multi-message one-to-all broadcasting that takes O(nlogn + m) steps.
17692093
Life after Video Coding Standards: Rate Shaping and Error Concealment
Is there life after video coding standards? One might think that research has no room to advance with the video coding standards already defined. On the contrary, exciting research opportunities arise after the standards are specified. In this paper, we introduce two standard-related research areas: rate shaping and error concealment, as examples of interesting research that finds its context in standards. Experiment results are also shown.