7682350
Incremental genetic K-means algorithm and its application in gene expression data analysis
BackgroundIn recent years, clustering algorithms have been effectively applied in molecular biology for gene expression data analysis. With the help of clustering algorithms such as K-means, hierarchical clustering, SOM, etc, genes are partitioned into groups based on the similarity between their expression profiles. In this way, functionally related genes are identified. As the amount of laboratory data in molecular biology grows exponentially each year due to advanced technologies such as Microarray, new efficient and effective methods for clustering must be developed to process this growing amount of biological data.ResultsIn this paper, we propose a new clustering algorithm, Incremental Genetic K-means Algorithm (IGKA). IGKA is an extension to our previously proposed clustering algorithm, the Fast Genetic K-means Algorithm (FGKA). IGKA outperforms FGKA when the mutation probability is small. The main idea of IGKA is to calculate the objective value Total Within-Cluster Variation (TWCV) and to cluster centroids incrementally whenever the mutation probability is small. IGKA inherits the salient feature of FGKA of always converging to the global optimum. C program is freely available at http://database.cs.wayne.edu/proj/FGKA/index.htm.ConclusionsOur experiments indicate that, while the IGKA algorithm has a convergence pattern similar to FGKA, it has a better time performance when the mutation probability decreases to some point. Finally, we used IGKA to cluster a yeast dataset and found that it increased the enrichment of genes of similar function within the cluster.
7907707
Fast search in DNA sequence databases using punctuation and indexing
Exact pattern searching in DNA sequence databases has applications in identification of highly conserved regulatory sequences, the design of hybridization probes, and improving performance of approximate homology searching tools such as BLAST and BLAT. We propose a new pattern searching algorithm, Compressed-Punctuated-Boyer-Moore (cp-BM), to enhance exact pattern match searches of DNA sequences. cp-BM encodes two bits to represent each A, T, C, G character (4-character 8 bit (4C8B) compression), plus punctuator characters to indicate unambiguously the encoding frame of the compressed target sequence, thereby solving the misalignment problem in searching patterns with ordinary 4C8B compression. cp-BM searches DNA patterns at least 6 times faster than AGREP for pattern lengths ≥ 128 and between 2-fold and 5-fold faster than d-BM for all pattern lengths. cp-BM's performance is enhanced by punctuator indexing and multiple punctuators, especially for short sequences, yielding greater than 10-fold enhancements compared to d-BM and AGREP. In addition, cp-BM outperformed BLAT for sequences 64 or more bases in length, and was more than three-fold faster for 256 base sequences.
16579446
Mining Correlation between Motifs and Gene Expression
One of the major challenges in the post-genomic era is to determine all DNA-binding transcription factors (TFs) and their regulatory binding sites (motifs) within the genomes. To discover the relationship between the motifs and changes in gene expression, we propose a new algorithm, co-miner (correlation miner). Correlation rules are generated based on the expression profiles of genes with significant expression change through the time course of gene expression. Thus, we may consider the change in gene expression to be causatively associated with the transcription binding sites in the upstream sequences. In addition, we introduce partition and constraint pushing techniques to improve the performance and demonstrate their effectiveness by our experiments. By applying co-miner to a yeast dataset, the relationships between motifs and gene expression revealed by co-miner are confirmed in the literature.
1552056
Pama: a Fast String Matching Algorithm
String matching is a fundamental operation in computer science, and its performance has great impact on many applications including database query, text processing, DNA and protein sequence analysis. In this paper, we propose a fast string matching algorithm, PAMA (PAttern MAtching). The shift rule used by PAMA not only subsumes both the bad character rule and the good suffix rule employed by the well-known Boyer-Moore algorithm, but also employs an additional key observation to enable faster shifting during the string matching process. Theoretically, we prove that from the same alignment, the next shift of PAMA will be at least as much as that of the Boyer-Moore algorithm. Experimentally, we show that PAMA indeed significantly outperforms the original Boyer-Moore algorithm in almost all cases, and outperforms other Boyer-Moore variants such as Tuned-BM, Turbo-BM and Horspool for long patterns (length ≥ 128) or for small alphabets (size < 8).
1334946
Program counter based techniques for dynamic power management
Reducing energy consumption has become one of the major challenges in designing future computing systems. We propose a novel idea of using program counters to predict I/O activities in the operating system. We present a complete design of program-counter access predictor (PCAP) that dynamically learns the access patterns of applications and predicts when an I/O device can be shut down to save energy. PCAP uses path-based correlation to observe a particular sequence of program counters leading to each idle period, and predicts future occurrences of that idle period. PCAP differs from previously proposed shutdown predictors in its ability to: (1) correlate I/O operations to particular behavior of the applications and users, (2) carry prediction information across multiple executions of the applications, and (3) attain better energy savings while incurring low mispredictions.
10102267
Parallel Randomized Support Vector Machine
A parallel support vector machine based on randomized sampling technique is proposed in this paper. We modeled a new LP-type problem so that it works for general linear-nonseparable SVM training problems unlike the previous work [2]. A unique priority based sampling mechanism is used so that we can prove an average convergence rate that is so far the fastest bounded convergence rate to the best of our knowledge. The numerical results on synthesized data and a real geometric database show that our algorithm has good scalability.
2807541
IDEA:: an infrastructure for detection-based adaptive consistency control in replicated services
In Internet-scale distributed and replicated services, poor consistency results in poor QoS or even monetary loss. Recent research focuses on enforcing a certain consistency level, instead of perfect consistency, to strike a balance between consistency guarantee and system's scalability. In this paper, we argue that it is equally, if not more, important to achieve adaptability. I.e., the system adjusts its consistency level on the fly to suit applications. ongoing need. This paper presents IDEA (an Infrastructure for DEtection-based Adaptive consistency control), a protocol that adaptively controls consistency in replicated services by detecting inconsistency among nodes in a timely manner via an inconsistency detection framework and resolving the detected inconsistencies efficiently when necessary. Through experimentation on Planet-Lab, IDEA is evaluated from two aspects: its adaptive interface and its performance of inconsistency resolution. Results show that IDEA achieves adaptability by adjusting the consistency level according to users. preference on-demand, and it achieves low inconsistency resolution delay and incurs minimal communication cost.
5344006
Min/max on-chip inductance models and delay metrics
This paper proposes an analytical inductance extraction model for characterizing min/max values of typical on-chip global intercon-nect structures, and a corresponding delay metric that can be used to provide RLC delay prediction from physical geometries. The model extraction and analysis is efficient enough to be used within optimization and physical design exploration loops. The analytical min/max inductance approximations also provide insight into the effects caused by inductances.
6121809
Tree-like counterexamples in model checking
Counter examples for specification violations provide engineers with important debugging information. Although counterexamples are considered one of the main advantages of model checking, state-of the art model checkers are restricted to relatively simple counterexamples, and surprisingly little research effort has been put into counterexamples. In this paper, we introduce a new general framework for counterexamples. The paper has three main contributions: (i) We determine the general form of ACTL counterexamples. To this end, we investigate the notion of counterexample and show that a large class of temporal logics beyond ACTL admits counterexamples with a simple tree-like transition relation. We show that the existence of tree-like counterexamples is related to a universal fragment of extended branching time logic based on w-regular temporal operators. (ii) We present new symbolic algorithms to generate tree-like counterexamples for ACTL specifications. (iii) Based on tree-like counterexamples we extend the abstraction refinement methodology developed recently by Clarke et al. (CAV'2000) to full ACTL. This demonstrates the conceptual simplicity and elegance of tree-like counterexamples.