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Selected Topics in Signal Processing, IEEE Journal of

Issue 3 • Date June 2008

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Displaying Results 1 - 25 of 25
  • Table of contents

    Publication Year: 2008 , Page(s): C1
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  • IEEE Journal of Selected Topics in Signal Processing publication information

    Publication Year: 2008 , Page(s): C2
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  • Introduction to the Issue on Genomic and Proteomic Signal Processing

    Publication Year: 2008 , Page(s): 257 - 260
    Cited by:  Papers (1)
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  • Information-Theoretic Feature Selection in Microarray Data Using Variable Complementarity

    Publication Year: 2008 , Page(s): 261 - 274
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (610 KB) |  | HTML iconHTML  

    The paper presents an original filter approach for effective feature selection in microarray data characterized by a large number of input variables and a few samples. The approach is based on the use of a new information-theoretic selection, the double input symmetrical relevance (DISR), which relies on a measure of variable complementarity. This measure evaluates the additional information that ... View full abstract»

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  • Recovering Sparse Signals Using Sparse Measurement Matrices in Compressed DNA Microarrays

    Publication Year: 2008 , Page(s): 275 - 285
    Cited by:  Papers (40)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1002 KB) |  | HTML iconHTML  

    Microarrays (DNA, protein, etc.) are massively parallel affinity-based biosensors capable of detecting and quantifying a large number of different genomic particles simultaneously. Among them, DNA microarrays comprising tens of thousands of probe spots are currently being employed to test multitude of targets in a single experiment. In conventional microarrays, each spot contains a large number of... View full abstract»

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  • Modeling and Estimation for Real-Time Microarrays

    Publication Year: 2008 , Page(s): 286 - 296
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2056 KB) |  | HTML iconHTML  

    Microarrays are used for collecting information about a large number of different genomic particles simultaneously. Conventional fluorescent-based microarrays acquire data after the hybridization phase. During this phase, the target analytes (e.g., DNA fragments) bind to the capturing probes on the array and, by the end of it, supposedly reach a steady state. Therefore, conventional microarrays at... View full abstract»

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  • Feature Selection for Self-Supervised Classification With Applications to Microarray and Sequence Data

    Publication Year: 2008 , Page(s): 297 - 309
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1437 KB) |  | HTML iconHTML  

    Learning strategies are traditionally divided into two categories: unsupervised learning and supervised learning. In contrast, for feature selection, there are four different categories of training scenarios: (1) unsupervised; (2) (regular) supervised; (3) self-supervised (SS); and (4) doubly supervised. Many genomic applications naturally arise in either (regular) supervised or self-supervised fo... View full abstract»

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  • Signal Processing in Sequence Analysis: Advances in Eukaryotic Gene Prediction

    Publication Year: 2008 , Page(s): 310 - 321
    Cited by:  Papers (19)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (706 KB) |  | HTML iconHTML  

    Genomic sequence processing has been an active area of research for the past two decades and has increasingly attracted the attention of digital signal processing researchers in recent years. A challenging open problem in deoxyribonucleic acid (DNA) sequence analysis is maximizing the prediction accuracy of eukaryotic gene locations and thereby protein coding regions. In this paper, DNA symbolic-t... View full abstract»

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  • A Deterministic Sequential Monte Carlo Method for Haplotype Inference

    Publication Year: 2008 , Page(s): 322 - 331
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (411 KB) |  | HTML iconHTML  

    Sets of single nucleotide polymorphisms (SNPs), or haplotypes, are widely used in the analysis of relationship between genetics and diseases. Due to the cost of obtaining exact haplotype pairs, genotypes which contain the unphased information corresponding to the haplotype pairs in the test subjects are used. Various haplotype inference algorithms have been proposed to resolve the unphased informa... View full abstract»

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  • Latent Periodicities in Genome Sequences

    Publication Year: 2008 , Page(s): 332 - 342
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1443 KB) |  | HTML iconHTML  

    A novel approach is presented for the detection of periodicities in DNA sequences. A DNA sequence can be modelled as a nonstationary stochastic process that exhibits various statistical periodicities over different regions. The coding part of the DNA, for instance, exhibits statistical periodicity with period three. Such regions in DNA are modelled as generated from a collection of information sou... View full abstract»

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  • A DSP Approach for Finding the Codon Bias in DNA Sequences

    Publication Year: 2008 , Page(s): 343 - 356
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1910 KB) |  | HTML iconHTML  

    The detection of different forms of periodicities in DNA sequences has been an active area of research in recent years. Most of the signal processing based methods have primarily focussed on assigning numerical values to the symbolic DNA sequence and then applying spectral analysis tools such as the short-time discrete Fourier transform (ST-DFT) to locate these repeats. A key application of DNA pe... View full abstract»

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  • Nonstationary Analysis of Coding and Noncoding Regions in Nucleotide Sequences

    Publication Year: 2008 , Page(s): 357 - 364
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (666 KB) |  | HTML iconHTML  

    Previous statistical analysis efforts of DNA sequences revealed that noncoding regions exhibit long-range power law correlations, whereas coding regions behave like random sequences or sustain short-range correlations. A great deal of debate on the presence or absence of long-range correlations in nucleotide sequences, and more specifically in coding regions, has ensued. These results were obtaine... View full abstract»

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  • Efficient Updating of Biological Sequence Analyses

    Publication Year: 2008 , Page(s): 365 - 377
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (751 KB) |  | HTML iconHTML  

    We present a novel approach for reducing the computational complexity of updating homologies produced by a wide class of popular state-of-the-art algorithms in comparative computational biology. The algorithms that we consider use hidden Markov models (HMMs) and a Viterbi recursion to evaluate matches between sequences, or between a sequence and models. Such updates occur frequently in practice as... View full abstract»

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  • Identification of Hot-Spot Locations in Proteins Using Digital Filters

    Publication Year: 2008 , Page(s): 378 - 389
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1028 KB) |  | HTML iconHTML  

    A technique for the identification of hot-spot locations in proteins using digital filters is described. In this technique, the characteristic frequency of the protein sequence of interest is first determined from the consensus spectrum of the corresponding functional group. The sequence is then filtered by using a specialized narrowband bandpass digital filter in order to select the characteristi... View full abstract»

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  • Optimal Design of a Molecular Recognizer: Molecular Recognition as a Bayesian Signal Detection Problem

    Publication Year: 2008 , Page(s): 390 - 399
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (600 KB) |  | HTML iconHTML  

    Numerous biological functions-such as enzymatic catalysis, the immune response system, and the DNA-protein regulatory network-rely on the ability of molecules to specifically recognize target molecules within a large pool of similar competitors in a noisy biochemical environment. Using the basic framework of signal detection theory, we treat the molecular recognition process as a signal detection ... View full abstract»

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  • Fast Structural Alignment of RNAs by Optimizing the Adjoining Order of Profile-csHMMs

    Publication Year: 2008 , Page(s): 400 - 411
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1136 KB) |  | HTML iconHTML  

    A novel RNA structural alignment method has been proposed based on profile-csHMMs. In principle, the profile-csHMM based approach can handle any kind of RNA secondary structures including pseudoknots, and it has been shown that the proposed approach can find highly accurate RNA alignments. In order to find the optimal alignment, the method employs the SCA algorithm that can be used for finding the... View full abstract»

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  • Optimal Intervention in Asynchronous Genetic Regulatory Networks

    Publication Year: 2008 , Page(s): 412 - 423
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (309 KB) |  | HTML iconHTML  

    There is an ongoing effort to design optimal intervention strategies for discrete state-space synchronous genetic regulatory networks in the context of probabilistic Boolean networks; however, to date, there has been no corresponding effort for asynchronous networks. This paper addresses this issue by postulating two asynchronous extensions of probabilistic Boolean networks and developing control ... View full abstract»

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  • Intrinsically Multivariate Predictive Genes

    Publication Year: 2008 , Page(s): 424 - 439
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (3198 KB) |  | HTML iconHTML  

    Canalizing genes possess such broad regulatory power, and their action sweeps across a such a wide swath of processes that the full set of affected genes are not highly correlated under normal conditions. When not active, the controlling gene will not be predictable to any significant degree by its subject genes, either alone or in groups, since their behavior will be highly varied relative to the... View full abstract»

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  • IEEE Journal of Selected Topics in Signal Processing Information for authors

    Publication Year: 2008 , Page(s): 440
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  • Special issue on advanced signal processing for GNSS and robust navigation

    Publication Year: 2008 , Page(s): 441
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  • Special issue on managing complexity in multiuser MIMO systems

    Publication Year: 2008 , Page(s): 442
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  • IEEE International Conference on Acoustics, Speech, and Signal Processing

    Publication Year: 2008 , Page(s): 443
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  • IEEE International Symposium on Broadband Multimedia Systems and Broadcasting

    Publication Year: 2008 , Page(s): 444
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  • IEEE Signal Processing Society Information

    Publication Year: 2008 , Page(s): C3
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  • Blank page [back cover]

    Publication Year: 2008 , Page(s): C4
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Aims & Scope

The Journal of Selected Topics in Signal Processing (J-STSP) solicits special issues on topics that cover the entire scope of the IEEE Signal Processing Society including the theory and application of filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals by digital or analog devices or techniques.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Fernando Pereira
Instituto Superior Técnico