15197279
On the complexity of finding common approximate substrings
Problems associated with finding strings that are within a specified Hamming distance of a given set of strings occur in several disciplines. In this paper, we use techniques from parameterized complexity to assess non-polynomial time algorithmic options and complexity for the COMMON APPROXIMATE SUBSTRING (CAS) problem. Our analyses indicate under which parameter restrictions useful algorithms are possible, and include both class membership and parameterized reductions to prove class hardness. In order to achieve fixed-parameter tractability, either a fixed string length or both a fixed size alphabet and fixed substring length are sufficient. Fixing either the string length or the alphabet size and Hamming distance is shown to be necessary, unless W[1] = FPT. An assortment of parameterized class membership and hardness results cover all other parameterized variants, showing in particular the effect of fixing the number of strings.
19034554
SIMPROT: Using an empirically determined indel distribution in simulations of protein evolution
BackgroundGeneral protein evolution models help determine the baseline expectations for the evolution of sequences, and they have been extensively useful in sequence analysis and for the computer simulation of artificial sequence data sets.ResultsWe have developed a new method of simulating protein sequence evolution, including insertion and deletion (indel) events in addition to amino-acid substitutions. The simulation generates both the simulated sequence family and a true sequence alignment that captures the evolutionary relationships between amino acids from different sequences. Our statistical model for indel evolution is based on the empirical indel distribution determined by Qian and Goldstein. We have parameterized this distribution so that it applies to sequences diverged by varying evolutionary times and generalized it to provide flexibility in simulation conditions. Our method uses a Monte-Carlo simulation strategy, and has been implemented in a C++ program named Simprot.ConclusionSimprot will be useful for testing methods of analysis of protein sequence families particularly alignment methods, phylogenetic tree building, detection of recombination and horizontal gene transfer, and homology detection, where knowing the true course of sequence evolution is essential.
7234685
Mining ChIP-chip data for transcription factor and cofactor binding sites
MOTIVATION
Identification of single motifs and motif pairs that can be used to predict transcription factor localization in ChIP-chip data, and gene expression in tissue-specific microarray data.


RESULTS
We describe methodology to identify de novo individual and interacting pairs of binding site motifs from ChIP-chip data, using an algorithm that integrates localization data directly into the motif discovery process. We combine matrix-enumeration based motif discovery with multivariate regression to evaluate candidate motifs and identify motif interactions. When applied to the HNF localization data in liver and pancreatic islets, our methods produce motifs that are either novel or improved known motifs. All motif pairs identified to predict localization are further evaluated according to how well they predict expression in liver and islets and according to how conserved are the relative positions of their occurrences. We find that interaction models of HNF1 and CDP motifs provide excellent prediction of both HNF1 localization and gene expression in liver. Our results demonstrate that ChIP-chip data can be used to identify interacting binding site motifs.


AVAILABILITY
Motif discovery programs and analysis tools are available on request from the authors.
1069327
DWE: Discriminating Word Enumerator
MOTIVATION
Tissue-specific transcription factor binding sites give insight into tissue-specific transcription regulation.


RESULTS
We describe a word-counting-based tool for de novo tissue-specific transcription factor binding site discovery using expression information in addition to sequence information. We incorporate tissue-specific gene expression through gene classification to positive expression and repressed expression. We present a direct statistical approach to find overrepresented transcription factor binding sites in a foreground promoter sequence set against a background promoter sequence set. Our approach naturally extends to synergistic transcription factor binding site search. We find putative transcription factor binding sites that are overrepresented in the proximal promoters of liver-specific genes relative to proximal promoters of liver-independent genes. Our results indicate that binding sites for hepatocyte nuclear factors (especially HNF-1 and HNF-4) and CCAAT/enhancer-binding protein (C/EBPbeta) are the most overrepresented in proximal promoters of liver-specific genes. Our results suggest that HNF-4 has strong synergistic relationships with HNF-1, HNF-4 and HNF-3beta and with C/EBPbeta.


AVAILABILITY
Programs are available for use over the Web at http://rulai.cshl.edu/tools/dwe.
716092
Complexity of Approximating Closest Substring Problems
The closest substring problem, where a short string is sought that minimizes the number of mismatches between it and each of a given set of strings, is a minimization problem with a polynomial time approximation scheme [6]. In this paper, both this problem and its maximization complement, where instead the number of matches is maximized, are examined and bounds on their hardness of approximation are proved. Related problems differing only in their objective functions, seeking either to maximize the number of strings covered by the substring or maximize the length of the substring, are also examined and bounds on their approximability proved. For this last problem of length maximization, the approximation bound of 2 is proved to be tight by presenting a 2-approximation algorithm.
42361348
Analysis of the Optimal, Look-Ahead Demand Paging Algorithms
We express the future behavior of programs that may be described by two common program behavior models, the independent reference model and the LRU stack model, by a discrete time Markov chain. Using this Markov chain model, we are able to calculate the theoretical minimum number of page faults for a program representable by either of these models in either a fixed or variable size memory. The behavior of optimal look-ahead and optimal realizable demand paging algorithms are compared, and it is seen that look-ahead paging demonstrates an inherent advantage sufficient to account for the differences observed between currently implemented demand paging algorithms and theoretically optimal algorithms.
14908018
Operating System Modifications for Task-Based Speed and Voltage
This paper describes RightSpeed, a task-based speed and voltage scheduler for Windows 2000. It takes advantage of the ability of certain processors, such as those from Transmeta and AMD, to dynamically change speed and voltage and thus to save energy while running more slowly. RightSpeed uses PACE, an algorithm that computes the most energy efficient way to meet task deadlines with high probability. Since most applications do not provide enough data about tasks, such as task deadlines, for PACE to work, RightSpeed uses simple and efficient heuristics to automatically detect task characteristics for such applications. RightSpeed has only 1.2% background overhead and its operations take only a few microseconds each. It even performs PACE calculation, which is quite complicated, in only 4.4 µs on average due to our extensive optimizations. RightSpeed is effective at meeting performance targets set by applications to within 1.5%. Although the PACE calculator does not save energy for the current generation of processors due to their limited range of worthwhile speed and voltage settings, we expect future processors to have greater such ranges, enabling PACE to reduce CPU energy consumption by 6.1‐8.7% relative to the best standard algorithm. Furthermore, with PACE, giving a processor the ability to run at additional, higher speeds and voltages reduces overall energy consumption.
20370847
A Set Probability Technique for Detecting Relative Time Order Across Multiple Neurons
With the development of multielectrode recording techniques, it is possible to measure the cell firing patterns of multiple neurons simultaneously, generating a large quantity of data. Identification of the firing patterns within these large groups of cells is an important and a challenging problem in data analysis. Here, we consider the problem of measuring the significance of a repeat in the cell firing sequence across arbitrary numbers of cells. In particular, we consider the question, given a ranked order of cells numbered 1 to N, what is the probability that another sequence of length n contains j consecutive increasing elements? Assuming each element of the sequence is drawn with replacement from the numbers 1 through N, we derive a recursive formula for the probability of the sequence of length j or more. For n < 2j, a closed-form solution is derived. For n 2j, we obtain upper and lower bounds for these probabilities for various combinations of parameter values. These can be computed very quickly. For a typical case with small N (<10) and large n (<3000), sequences of 7 and 8 are statistically very unlikely. A potential application of this technique is in the detection of repeats in hippocampal place cell order during sleep. Unlike most previous articles on increasing runs in random lists, we use a probability approach based on sets of overlapping sequences.
7418837
Lower bounds for collusion-secure fingerprinting
Collusion-secure fingerprinting codes are an important primitive used by many digital watermarking schemes [1, 10, 9]. Boneh and Shaw [3] define a model for these types of codes and present an explicit construction. Their code has length <i>O</i>(<i>c</i><sup>3</sup> log(l/ε)) and attains security against coalitions of size <i>c</i> with ε error. Boneh and Shaw also present a lower bound of Ω (<i>c</i><sup>3</sup>log(1/<i>c</i>ε)) on the length of any collusion-secure code.We give new lower bounds on the length of collusion-secure codes by analyzing a weighted coinflipping strategy for the coalition. As an illustration of our methods, we give a simple proof that the Boneh-Shaw construction cannot be asymptotically improved. Next, we prove a general lower bound: no secure code can have length <i>O</i>(<i>c</i><sup>2</sup>1og(1/<i>c</i>ε)), which improves the previous known bound by a factor of <i>c</i>. In particular, we show that any secure code will have length Ω(<i>c</i><sup>2</sup> log(1/<i>c</i>ε)) as long as log(l/ε) ≥ <i>K</i> <i>k</i> log <i>c</i>, where <i>K</i> is a constant and <i>k</i> is the number of columns in the code (in some sense, a measure of the code's complexity). Finally, we describe a general paradigm for constructing fingerprinting codes which encompasses the construction of [3], and show that no secure code that follows this paradigm can have length <i>O</i>((c<sup>3</sup>/log c) log(1/<i>c</i>ε)) follows this (again, by showing a lower bound for large values of ln(1/ε)). This suggests that any attempts at improvement should be directed toward techniques that lie outside our paradigm.
7100956
Scheduling techniques for reducing processor energy use in MacOS
The CPU is one of the major power consumers in a portable computer, and considerable power can be saved by turning off the CPU when it is not doing useful work. In Apple's MacOS, however, idle time is often converted to busy waiting, and generally it is very hard to tell when no useful computation is occurring. In this paper, we suggest several heuristic techniques for identifying this condition, and for temporarily putting the CPU in a low‐power state. These techniques include turning off the processor when all processes are blocked, turning off the processor when processes appear to be busy waiting, and extending real time process sleep periods. We use trace‐driven simulation, using processor run interval traces, to evaluate the potential energy savings and performance impact. We find that these techniques save considerable amounts of processor energy (as much as 66%), while having very little performance impact (less than 2% increase in run time). Implementing the proposed strategies should increase battery lifetime by approximately 20% relative to Apple's current CPU power management strategy, since the CPU and associated logic are responsible for about 32% of power use; similar techniques should be applicable to operating systems with similar behavior.