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The paper provides theoretical justification for the " 3-periodicity property " observed in protein coding regions within genomic DNA sequences. We propose a new classification criteria improving upon traditional frequency based approaches for identification of coding regions. Experimental studies indicate superior performance compared with other algorithms(More)
While the well-known Transport Control Protocol (TCP) is a <i>de facto</i> standard for reliable communication on the Internet, and performs well in practice, the question "how good is the TCP/IP congestion control algorithm?" is not completely resolved. In this paper, we provide some answers to this question using the competitive analysis framework. First,(More)
Flow cytometry (FC) is a powerful technology for rapid multivariate analysis and functional discrimination of cells. Current FC platforms generate large, high-dimensional datasets which pose a significant challenge for traditional manual bivariate analysis. Automated mul-tivariate clustering, though highly desirable, is also stymied by the critical(More)
Existing Discrete Fourier transform (DFT)-based algorithms for identifying protein coding regions in DNA sequences[9, 2, 3, 7] exploit the empirical observation that the spectrum of protein coding regions of length N nucleotides has a peak at frequency k = N/3. In this paper , we prove the aforementioned and several other empirical observations attributed(More)
We present a model-based clustering method, SWIFT (Scalable Weighted Iterative Flow-clustering Technique), for digesting high-dimensional large-sized datasets obtained via modern flow cytometry into more compact representations that are well-suited for further automated or manual analysis. Key attributes of the method include the following: (a) the analysis(More)
A multistage clustering and data processing method, SWIFT (detailed in a companion manuscript), has been developed to detect rare subpopulations in large, high-dimensional flow cytometry datasets. An iterative sampling procedure initially fits the data to multidimensional Gaussian distributions, then splitting and merging stages use a criterion of(More)
Two of the most important factors in the design of any processor are speed and energy consumption. In this paper, we propose a new cache architecture that results in a faster memory access and lower energy consumption. Our proposed architecture does not require any changes to the processor architecture, it only assume the existence of a BTB. Using(More)