19601656
A mutation-sensitive approach for locating conserved gene pairs between related species
This paper proposes a new approach for solving the whole genome alignment problem. Our approach is based on a new structural optimization problem (called the MUM selection problem) related to mutations via reversals and transpositions. We have devised a practical algorithm for this optimization problem and have evaluated the algorithm using 15 pairs of human and mouse chromosomes. The results show that our algorithm is both effective and efficient. More specifically, our algorithm can reveal 91% of the conserved gene pairs that have been reported in the literature. When compared to existing software MUMmer and MaxMinCluster , our algorithm uncovers 15% and 7% more genes on average, respectively. The sensitivity of our algorithm is also slightly higher. The paper concludes with a remark on the computational hardness of the MUM selection problem.
18562701
Compressed Index for a Dynamic Collection of Texts
Let T be a string with n characters over an alphabet of bounded size. The recent breakthrough on compressed indexing allows us to build an index for T in optimal space (i.e., O(n) bits), while supporting very efficient pattern matching [2,4]. This paper extends the work on optimal-space indexing to a dynamic collection of texts. Precisely, we give a compressed index using O(n) bits where n is the total length of texts, such that searching for a pattern P takes O(|P|log n + occ log2 n) time where occ is the number of occurrences, and inserting or deleting a text T takes O(|T|log n) time.
8031191
Dynamic dictionary matching and compressed suffix trees
Recent breakthrough in compressed indexing data structures has reduced the space for indexing a text (or a collection of texts) of length <i>n</i> from <i>O</i>(<i>n</i> log <i>n</i>) bits to <i>O</i>(<i>n</i>) bits, while allowing very efficient pattern matching [10, 13]. Yet the compressed nature of such indices also makes them difficult to update dynamically. This paper presents the first <i>O</i>(<i>n</i>)-bit representation of a suffix tree for a dynamic collection of texts whose total length is <i>n</i>, which supports insertion and deletion of a text <i>T</i> in <i>O</i>(|<i>T</i> | log<sup>2</sup> <i>n</i>) time, as well as all suffix tree traversal operations, including forward and backward suffix links. This work can be regarded as a generalization of the compressed representation of static texts. Our new suffix tree representation serves as a core part in a compact solution for the dynamic dictionary matching problem, i.e., providing an <i>O</i>(<i>d</i>)-bit data structure for a dynamic collection of patterns of total length <i>d</i> that can support the dictionary matching query efficiently. When compared with the <i>O</i>(<i>d</i> log <i>d</i>)-bit suffix tree based solution of Amir <i>et al.</i>, the compact solution increases the query time by roughly a factor of log <i>d</i> only. In the study of the above results, we also derive the first <i>O</i>(<i>n</i>)-bit representation for maintaining <i>n</i> pairs of balanced parentheses in <i>O</i>(log <i>n</i>/log log <i>n</i>) time per operation, matching the time complexity of the previous <i>O</i>(<i>n</i> log <i>n</i>)-bit solution.
34112863
Compressed Indexes for Approximate String Matching
We revisit the problem of indexing a string S[1..n] to support searching all substrings in S that match a given pattern P[1..m] with at most k errors. Previous solutions either require an index of size exponential in k or need Ω(mk) time for searching. Motivated by the indexing of DNA sequences, we investigate space efficient indexes that occupy only O(n) space. For k = 1, we give an index to support matching in O(m + occ + logn loglogn) time. The previously best solution achieving this time complexity requires an index of size O(n logn). This new index can be used to improve existing indexes for k ≥2 errors. Among others, it can support matching with k=2 errors in O(m logn loglogn + occ) time.
15971365
Efficiency of Data Distribution in BitTorrent-Like Systems
BitTorrent (BT) in practice is a very efficient method to share data over a network of clients. In this paper we extend the recent work of Arthur and Panigrahy [1] on modelling the distribution of individual data blocks in BT systems, aiming at a better understanding of why BT can achieve a high degree of parallelism. In particular, we include in our study several new network features that BT systems are using, as well as different local heuristics for routing data blocks in each client. We conduct simulations to figure out to what extent the new network features and routing heuristics would affect the distribution efficiency. Our findings confirm that for the primitive network setting studied in [1], it does require i¾?(blogn) phases for nclients to download bdata blocks. More interestingly, our work suggests that for the more realistic network setting, the heuristics Random and Rarest Block First both allow nclients to download bblocks in b+ O(logn) phases. We believe that the latter bound better reflects the high degree of parallelism of BT observed in reality. It is also worth-mentioning that b+ lognis the smallest possible number of phases needed; it is interesting to see that some simple local routing heuristics have a performance so close to the optimal.
15069863
Non-migratory online deadline scheduling on multiprocessors
In this paper we consider multiprocessor scheduling with hard deadlines and investigate the cost of eliminating migration in the online setting. Let I be any set of jobs that can be completed by some migratory offline schedule on m processors. We show that I can also be completed by a non-migratory online schedule using m speed-5.828 processors (i.e., processors of 5.828 times faster). This result supplements the previous results that I can also be completed by a non-migratory offline schedule using 6m unit-speed processors [8] or a migratory online schedule using m speed-2 processors [13]. Our result is based on a simple conservative scheduling algorithm called PARK which commits a processor to a job only when the processor has zero commitment before its deadline. A careful analysis of PARK further shows that the processor speed can be reduced arbitrarily close to 1 by exploiting more processors (say, using 16m speed-1.8 processors). PARK also finds application in overloaded systems; it gives the first online non-migratory algorithm that can exploit moderately faster processors to match the performance of any migratory offline algorithm.
3053066
Sensitivity Analysis in Bayesian Networks: From Single to Multiple Parameters
Previous work on sensitivity analysis in Bayesian networks has focused on single parameters, where the goal is to understand the sensitivity of queries to single parameter changes, and to identify single parameter changes that would enforce a certain query constraint. In this paper, we expand the work to multiple parameters which may be in the CPT of a single variable, or the CPTs of multiple variables. Not only do we identify the solution space of multiple parameter changes that would be needed to enforce a query constraint, but we also show how to find the optimal solution, that is, the one which disturbs the current probability distribution the least (with respect to a specific measure of disturbance). We characterize the computational complexity of our new techniques and discuss their applications to developing and debugging Bayesian networks, and to the problem of reasoning about the value (reliability) of new information.
10310314
Sensitivity Analysis in Markov Networks
This paper explores the topic of sensitivity analysis in Markov networks, by tackling questions similar to those arising in the context of Bayesian networks: the tuning of parameters to satisfy query constraints, and the bounding of query changes when perturbing network parameters. Even though the distribution induced by a Markov network corresponds to ratios of multi-linear functions, whereas the distribution induced by a Bayesian network corresponds to multi-linear functions, the results we obtain for Markov networks are as effective computationally as those obtained for Bayesian networks. This similarity is due to the fact that conditional probabilities have the same functional form in both Bayesian and Markov networks, which turns out to be the more influential factor. The major difference we found, however, is in how changes in parameter values should be quantified, as such parameters are interpreted differently in Bayesian networks and Markov networks.
17538498
Reasoning about Bayesian Network Classifiers
Bayesian network classifiers are used in many fields, and one common class of classifiers are naive Bayes classifiers. In this paper, we introduce an approach for reasoning about Bayesian network classifiers in which we explicitly convert them into Ordered Decision Diagrams (ODDS), which are then used to reason about the properties of these classifiers. Specifically, we present an algorithm for converting any naive Bayes classifier into an ODD, and we show theoretically and experimentally that this algorithm can give us an ODD that is tractable in size cvcn given an intractable number of instances. Since ODDS are tractable representations of classifiers, our algorithm allows us to efficiently test the equivalence of two naive Bayes classifiers and characterize discrepancies between them. We also show a number of additional results including a count of distinct classifiers that can be induced by changing some CPT in a naive Bayes classifier, and the range of allowable changes to a CPT which keeps the current classifier unchanged.
2565301
Visualizing input and output analysis for simulation (VINOAS)
Abstract Input analysis which involves a large amount of statistical analysis is one of the major steps in simulation. A software package with a well-designed user-friendly graphical window interface has been developed to assist modelers in identifying the underlying statistical distribution of the input data. It integrates techniques for assessing sample independence, hypothesizing families of distributions, estimation of parameters, and performing goodness-of-fit tests in a graphical environment. This allows the modelers to use the package in an interactive way and efforts can be saved in specifying the input probability distribution.
18001156
A thermally actuated polymer micro robotic gripper for manipulation of biological cells
The development of a novel polymer-based micro robotic gripper that can be actuated in a liquid medium is presented in this paper. The basic structure for the gripper is a trimorph thermal actuator with a platinum metal heater encapsulated by poly-para-xylene C (parylene C) polymer layers. Due to the large difference of thermal expansion coefficients of the different layers, the actuator can be actuated with much large deflection than conventional MEMS actuators. We have developed actuators operating in liquid environment (e.g., DI water) with only 3 V at /spl sim/33 mA input to achieve full deflection (90/spl deg/ change of tip direction). The actuators were also observed to response to 3 Hz square wave input in water with no visible delay. The temperature of the actuators at full deflection was estimated to be about 60/spl deg/C, which is much lower than the typical requirement of >100/spl deg/C to actuate other conventional MEMS actuators. Actuators with dimensions of /spl sim/2 mm/spl times/100/spl mu/m/spl times/0.6/spl mu/m were used to capture Danio rerio follicles (/spl sim/800/spl mu/m average cell diameter) in water. The design, fabrication process, and experimental results for these actuators are presented in this paper.