16829828
Algorithms for Imperfect Phylogeny Haplotyping (IPPH) with a Single Homoplasy or Recombination Event
The haplotype inference (HI) problem is the problem of inferring 2n haplotype pairs from n observed genotype vectors. This is a key problem that arises in studying genetic variation in populations, for example in the ongoing HapMap project [5]. In order to have a hope of finding the haplotypes that actually generated the observed genotypes, we must use some (implicit or explicit) genetic model of the evolution of the underlying haplotypes. The Perfect Phylogeny Haplotyping (PPH) model was introduced in 2002 [9] to reflect the “neutral coalescent” or “perfect phylogeny” model of haplotype evolution. The PPH problem (which can be solved in polynomial time) is to determine whether there is an HI solution where the inferred haplotypes can be derived on a perfect phylogeny (tree). 
 
Since the introduction of the PPH model, several extensions and modifications of the PPH model have been examined. The most important modification, to model biological reality better, is to allow a limited number of biological events that violate the perfect phylogeny model. This was accomplished implicitly in [7,12] with the inclusion of several heuristics into an algorithm for the PPH problem [8]. Those heuristics are invoked when the genotype data cannot be explained with haplotypes that fit the perfect phylogeny model. In this paper, we address the issue explicitly, by allowing one recombination or homoplasy event in the model of haplotype evolution. We formalize the problems and provide a polynomial time solution for one problem, using an additional, empirically-supported assumption. We present a related framework for the second problem which gives a practical algorithm. We believe the second problem can be solved in polynomial time.
14072276
An Efficient Algorithm for Statistical Multiple Alignment on Arbitrary Phylogenetic Trees
We present an efficient algorithm for statistical multiple alignment based on the TKF91 model of Thorne, Kishino, and Felsenstein (1991) on an arbitrary k-leaved phylogenetic tree. The existing algorithms use a hidden Markov model approach, which requires at least O( radical 5(k)) states and leads to a time complexity of O(5(k)L(k)), where L is the geometric mean sequence length. Using a combinatorial technique reminiscent of inclusion/exclusion, we are able to sum away the states, thus improving the time complexity to O(2(k)L(k)) and considerably reducing memory requirements. This makes statistical multiple alignment under the TKF91 model a definite practical possibility in the case of a phylogenetic tree with a modest number of leaves.
16612931
Efficient computation of close lower and upper bounds on the minimum number of recombinations in biological sequence evolution
MOTIVATION
We are interested in studying the evolution of DNA single nucleotide polymorphism sequences which have undergone (meiotic) recombination. For a given set of sequences, computing the minimum number of recombinations needed to explain the sequences (with one mutation per site) is a standard question of interest, but it has been shown to be NP-hard, and previous algorithms that compute it exactly work either only on very small datasets or on problems with special structure.


RESULTS
In this paper, we present efficient, practical methods for computing both upper and lower bounds on the minimum number of needed recombinations, and for constructing evolutionary histories that explain the input sequences. We study in detail the efficiency and accuracy of these algorithms on both simulated and real data sets. The algorithms produce very close upper and lower bounds, which match exactly in a surprisingly wide range of data. Thus, with the use of new, very effective lower bounding methods and an efficient algorithm for computing upper bounds, this approach allows the efficient, exact computation of the minimum number of needed recombinations, with high frequency in a large range of data. When upper and lower bounds match, evolutionary histories found by our algorithm correspond to the most parsimonious histories.


AVAILABILITY
HapBound and SHRUB, programs implementing the new algorithms discussed in this paper, are available at http://wwwcsif.cs.ucdavis.edu/~gusfield/lu.html
40339335
Algorithms to Distinguish the Role of Gene-Conversion from Single-Crossover Recombination in the Derivation of SNP Sequences in Populations
Meiotic recombination is a fundamental biological event and one of the principal evolutionary forces responsible for shaping genetic variation within species. In addition to its fundamental role, recombination is central to several critical applied problems. The most important example is “association mapping” in populations, which is widely hoped to help find genes that influence genetic diseases [3, 4]. Hence, a great deal of recent attention has focused on problems of inferring the historical derivation of sequences in populations when both mutations and recombinations have occurred. In the algorithms literature, most of that recent work has been directed to single-crossover recombination. However, gene-conversion is an important, and more common, form of (two-crossover) recombination which has been much less investigated in the algorithms literature. 
 
In this paper we explicitly incorporate gene-conversion into discrete methods to study historical recombination. We are concerned with algorithms for identifying and locating the extent of historical crossing-over and gene-conversion (along with single-nucleotide mutation), and problems of constructing full putative histories of those events. The novel technical issues concern the incorporation of gene-conversion into recently developed discrete methods [20, 26] that compute lower and upper-bound information on the amount of needed recombination without gene-conversion. We first examine the most natural extension of the lower bound methods from [20], showing that the extension can be computed efficiently, but that this extension can only yield weak lower bounds. We then develop additional ideas that lead to higher lower bounds, and show how to solve, via integer-linear programming, a more biologically realistic version of the lower bound problem. We also show how to compute effective upper bounds on the number of needed single-crossovers and gene-conversions, along with explicit networks showing a putative history of mutations, single-crossovers and gene-conversions. 
 
We validate the significance of these methods by showing that they can be effectively used to distinguish simulation-derived sequences generated without gene-conversion from sequences that were generated with gene-conversion. We apply the methods to recently studied sequences of Arabidopsis thaliana, identifying many more regions in the sequences than were previously identified [22], where gene-conversion may have played a significant role. Demonstration software is available at www.cs. ucdavis.edu/~gusfield.
11873336
A concise necessary and sufficient condition for the existence of a galled-tree
Galled-trees are a special class of graphical representation of evolutionary history that has proven amenable to efficient, polynomial-time algorithms. The goal of this paper is to construct a concise necessary and sufficient condition for the existence of a galled-tree for M, a set of binary sequences that purportedly have evolved in the presence of recombination. Both root-known and root-unknown cases are considered here
1233583
Minimum Recombination Histories by Branch and Bound
Recombination plays an important role in creating genetic diversity within species, and inferring past recombination events is central to many problems in genetics. Given a set M of sampled sequences, finding an evolutionary history for M with the minimum number of recombination events is a computationally very challenging problem. In this paper, we present a novel branch and bound algorithm for tackling that problem. Our method is shown to be far more efficient than the only preexisting exact method, described in [1]. Our software implementing the algorithm discussed in this paper is publicly available.
7172331
Enhanced Strict Multilevel Successive Elimination Algorithm for Fast Motion Estimation
This paper presents an enhanced strict multilevel successive elimination algorithm (EMSEA) for fast block-matching motion estimation, which is based on the previous strict multilevel successive elimination algorithm (SMSEA) (Song et al., 2006). Different to the SMSEA algorithm with fixed parameters, in EMSEA algorithm, the whole search area is divided into two regions and each region has its own parameters. Therefore, the computation complexity of SMSEA algorithm can be further decreased. Experiments show that the proposed EMSEA algorithm can reduce 16.2% of the SMSEA computation and maintain almost the same image quality, which is better than the TSS and DS algorithms.
11425513
Graceful degradation of loss-tolerant QoS using (m, k)-firm constraints in guaranteed rate networks
The Weighted Fair Queueing (WFQ) scheduling algorithm and its variants can be used to provide real-time guarantees by making bandwidth reservation. However, while hard guarantees are based on a peak workload model that leads to underutilize network resources, soft guarantees, based on average workload model, are not always sufficient to maintain acceptable Quality-of-Service (QoS) since consecutive packet losses or deadline misses may occur, which are not suitable for real-time applications. In this paper, we propose a trade-off between hard and soft real-time guarantees to maintain an acceptable QoS in overload conditions and efficiently maximize the utilization of network resources. The key to our solution is based on the fact that many real-time applications, such as voice and video, are loss-tolerant. The loss profile must be well defined, and such a profile can be easily specified using the (m,k)-firm model. Therefore, we propose the (m,k)-WFQ algorithm to take into account (m,k)-firm timing constraints to provide delay guarantees of at least m packets out of any k consecutive packets without violating bandwidth fairness or misusing network resources. Using the Network Calculus theory, an analytic study gives the deterministic delay bound provided by the (m,k)-WFQ algorithm for upper bounded arrival curve traffic. We extend our analytic results for guaranteed-rate networks, such as the IntServ QoS model and ATM networks, and the DiffServ QoS model. Analytic results and simulations show a noticeable improvement in delay guarantee made by (m,k)-WFQ compared to WFQ without much degradation of bandwidth fairness.
6822921
Unsupervised Learning of Human Motion
An unsupervised learning algorithm that can obtain a probabilistic model of an object composed of a collection of parts (a moving human body in our examples) automatically from unlabeled training data is presented. The training data include both useful "foreground" features as well as features that arise from irrelevant background clutter - the correspondence between parts and detected features is unknown. The joint probability density function of the parts is represented by a mixture of decomposable triangulated graphs which allow for fast detection. To learn the model structure as well as model parameters, an EM-like algorithm is developed where the labeling of the data (part assignments) is treated as hidden variables. The unsupervised learning technique is not limited to decomposable triangulated graphs. The efficiency and effectiveness of our algorithm is demonstrated by applying it to generate models of human motion automatically from unlabeled image sequences, and testing the learned models on a variety of sequences.
7144496
Loss-tolerant QoS using firm constraints in guaranteed rate networks
We propose a trade-off between hard and soft real-time guarantees to maintain an acceptable QoS guarantee in overload condition and maximize efficiently the utilization of network resources. The key of our solution is that many real-time applications are loss-tolerant, but the loss profile must be well defined since successive packet losses are not suitable. We use the concept of (m,k)-firm timing constraints to define a novel guaranteed loss-tolerant QoS. Therefore, we extend the basic WFQ algorithm to take into account the firm timing constraints to provide lower delay guarantees without violating bandwidth fairness or misusing network resources. The proposal is called (m,k)-WFQ. Using network calculus formalism, analytic study gives the deterministic delay bound provided by the (m,k)-WFQ algorithm for upper bounded arrival curve traffic. Theoretical results and simulations show a noticeable improvement on delay guarantee made by (m,k)-WFQ compared to standard WFQ algorithm without much degrading bandwidth fairness.
3032576
Generative models for name disambiguation
Name ambiguity is a special case of identity uncertainty where one person can be referenced by multiple name variations in different situations or evenshare the same name with other people. In this paper, we present an efficient framework by using two novel topic-based models, extended from Probabilistic Latent Semantic Analysis (PLSA) and Latent Dirichlet Allocation (LDA). Our models explicitly introduce a new variable for persons and learn the distribution of topics with regard to persons and words. Experiments indicate that our approach consistently outperforms other unsupervised methods including spectral and DBSCAN clustering. Scalability is addressed by disambiguating authors in over 750,000 papers from the entire CiteSeer dataset.