Pattern recognition of sequence similarities in globular proteins by Fourier analysis: A novel approach to molecular evolution

The domain of graphs contains only little mathematical structure. That is, most of the basic mathematical operations, actually required by many standard computer vision and pattern recognition algorithms, are not available for graphs. One of the few mathematical concepts that has been successfully transferred from the vector space to the graph domain is distance computation between graphs, commonly referred to as graph matching. Yet, distance-based pattern recognition is basically limited to nearest-neighbor classification. The present chapter reviews a novel approach for graph embedding in vector spaces built upon the concept of graph matching. The key-idea of the proposed embedding method is to use the distances of an input graph to a number of training graphs, termed prototypes, as vectorial description of the graph. That is, all graph matching procedures proposed in the literature during the last decades can be employed in this embedding framework. The rationale for such a graph embedding is to bridge the gap between the high representational power and flexibility of graphs and the large amount of algorithms available for object representations in terms of feature vectors. Hence, the proposed framework can be considered a contribution towards unifying the domains of structural and statistical pattern recognition.

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Reconstructing Phylogenetic Relationships Based on Repeat Sequence Similarities

10.1101/624064 ◽

2019 ◽

Cited By ~ 2

Author(s):

Daniel Vitales ◽

Sònia Garcia ◽

Steven Dodsworth

Keyword(s):

Phylogenetic Relationships ◽

Sequence Similarity ◽

Information Source ◽

Repeat Sequence ◽

Combined Application ◽

Novel Approach ◽

Genome Wide ◽

History Of ◽

Sequence Similarities ◽

Phylogenetic Method

AbstractA recent phylogenetic method based on genome-wide abundance of different repeat types proved to be useful in reconstructing the evolutionary history of several plant and animal groups. Here, we demonstrate that an alternative information source from the repeatome can also be employed to infer phylogenetic relationships among taxa. Specifically, this novel approach makes use of the repeat sequence similarity matrices obtained from the comparative clustering analyses of RepeatExplorer 2, which are subsequently transformed to between-taxa distance matrices. These pairwise matrices are used to construct neighbour-joining trees for each of the top most-abundant clusters and they are finally summarized in a consensus network. This methodology was tested on three groups of angiosperms and one group of insects, resulting in congruent evolutionary hypotheses compared to more standard systematic analyses based on commonly used DNA markers. We propose that the combined application of these phylogenetic approaches based on repeat abundances and repeat sequence similarities could be helpful to understand mechanisms governing genome and repeatome evolution.

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To what degree of voice perturbation are jitter measurements valid? A novel approach with synthesized vowels and visuo-perceptual pattern recognition

Biomedical Signal Processing and Control ◽

10.1016/j.bspc.2011.05.002 ◽

2012 ◽

Vol 7 (1) ◽

pp. 37-42 ◽

Cited By ~ 19

Author(s):

P.H. Dejonckere ◽

A. Giordano ◽

J. Schoentgen ◽

S. Fraj ◽

L. Bocchi ◽

...

Keyword(s):

Pattern Recognition ◽

Novel Approach

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A NOVEL APPROACH TO IMAGE THRESHOLDING BASED ON 2D HOMOGENEITY HISTOGRAM AND MAXIMUM FUZZY ENTROPY

New Mathematics and Natural Computation ◽

10.1142/s1793005711001834 ◽

2011 ◽

Vol 07 (01) ◽

pp. 105-133 ◽

Cited By ~ 1

Author(s):

H. D. CHENG ◽

YANHUI GUO ◽

YINGTAO ZHANG

Keyword(s):

Image Processing ◽

Computer Vision ◽

Pattern Recognition ◽

Set Theory ◽

Fuzzy Set ◽

Fuzzy Set Theory ◽

Fuzzy Entropy ◽

Image Thresholding ◽

Novel Approach ◽

Entropy Principle

Image thresholding is an important topic for image processing, pattern recognition and computer vision. Fuzzy set theory has been successfully applied to many areas, and it is generally believed that image processing bears some fuzziness in nature. In this paper, we employ the newly proposed 2D homogeneity histogram (homogram) and the maximum fuzzy entropy principle to perform thresholding. We have conducted experiments on a variety of images. The experimental results demonstrate that the proposed approach can select the thresholds automatically and effectively. Especially, it not only can process "clean" images, but also can process images with different kinds of noises and images with multiple kinds of noise well without knowing the type of the noise, which is the most difficult task for image thresholding. It will be useful for applications in computer vision and image processing.

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WAVELET ORTHONORMAL DECOMPOSITIONS FOR EXTRACTING FEATURES IN PATTERN RECOGNITION

International Journal of Pattern Recognition and Artificial Intelligence ◽

10.1142/s0218001499000458 ◽

1999 ◽

Vol 13 (06) ◽

pp. 803-831 ◽

Cited By ~ 5

Author(s):

YUAN Y. TANG ◽

JIMING LIU ◽

HONG MA ◽

BING F. LI

Keyword(s):

Pattern Recognition ◽

Wavelet Transform ◽

Two Dimensional ◽

Classification Rate ◽

One Dimensional ◽

Feature Vectors ◽

Novel Approach

In this paper, a novel approach based on the wavelet orthonormal decomposition is presented to extract features in pattern recognition. The proposed approach first reduces the dimensionality of a two-dimensional pattern, and thereafter performs wavelet transform on the derived one-dimensional pattern to generate a set of wavelet transform subpatterns, namely, several uncorrelated functions. Based on these functions, new features are readily computed to represent the original two-dimensional pattern. As an application, experiments were conducted using a set of printed characters with varying orientations and fonts. The results obtained from these experiments have consistently shown that the proposed feature vectors can yield an excellent classification rate in pattern recognition.

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Molecular evolution of the Escherichia coli chromosome. II. Clonal segments.

Genetics ◽

10.1093/genetics/120.2.359 ◽

1988 ◽

Vol 120 (2) ◽

pp. 359-366

Author(s):

R Milkman ◽

A Stoltzfus

Keyword(s):

Escherichia Coli ◽

Molecular Evolution ◽

High Frequency ◽

Favorable Alleles ◽

Chromosomal Fragment ◽

A Cell ◽

Recent Origin ◽

Chromosome Ii ◽

Sequence Similarities ◽

Low Rate

Abstract Remarkable sequence similarities in the trp region among Escherichia coli strains of diverse natural origins imply the existence of worldwide clones of very recent origin. This in turn implies a low rate of fixation of new universally favorable alleles, which carry adjacent stretches of chromosome to high frequency. These clonal segments begin as entire chromosomes; recombination shortens them progressively by substituting less closely related homologous DNA. The rate of this recombination, comprising the introduction of a homologous chromosomal fragment to a cell and the replacement of part of the original chromosome, is estimated from observations.

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The PIC-TDD Framework of Test Data Design for Pattern Recognition Systems

International Journal of Advanced Pervasive and Ubiquitous Computing ◽

10.4018/ijapuc.2014100104 ◽

2014 ◽

Vol 6 (4) ◽

pp. 43-62

Author(s):

Xiangdong Wang ◽

Ying Yang ◽

Hong Liu ◽

Yueliang Qian

Keyword(s):

Pattern Recognition ◽

Test Data ◽

Random Sampling ◽

Random Variable ◽

Unbiased Estimation ◽

Novel Approach ◽

Pattern Recognition Systems ◽

Recognition Systems ◽

News Segmentation ◽

Data Design

In this paper, a new approach is proposed for the design of test data for pattern recognition systems. In the theoretical framework put forward, performance on the population of data is viewed as expectation of a random variable, and the purpose of test is to estimate the parameter. While the most popular method of test data design is random sampling, a novel approach based on performance influencing classes is proposed, which can achieve unbiased estimation and the variance of estimation is much lower than that from random sample. The method is applied to the evaluation of systems for broadcasting news segmentation, and experimental results show the advantages over the random sampling approach.

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Abstract 15541: Novel Molecular Entity for Effective Cardiac Regeneration: 5’ppp Microrna Induces Reprogramming and Accelerates Cardiomyocyte Maturation

Circulation ◽

10.1161/circ.142.suppl_3.15541 ◽

2020 ◽

Vol 142 (Suppl_3) ◽

Author(s):

Jiabiao Hu ◽

Conrad Hodgkinson ◽

Syeda S Baksh ◽

Richard E Pratt ◽

Victor J Dzau

Keyword(s):

Pattern Recognition ◽

Cardiac Regeneration ◽

Molecular Entity ◽

Rna Molecules ◽

Novel Approach ◽

Nfkb Activation ◽

Recognition Receptor ◽

Modest Effect

We have shown that miR combo directly reprograms fibroblasts into cardiomyocytes. However, both in vitro and in vivo, the generated cardiomyocytes are immature. Recently, we discovered that cardiomyocyte maturation is enhanced by NFkB activation. While miR combo initiates reprogramming, the effect on NFkB activity is modest. Therefore, miR combo only has a modest effect on maturation. We have now made an important discovery that 5’triphosphorylation (5’ppp) of RNA molecules markedly enhance NFkB activation; leading to increased and accelerated maturation of reprogramed cardiomyocytes. The addition of 5’ppp-RNA increased the number of mature cardiomyocytes by 4-fold (N=5, P<0.05). Moreover, 5’ppp-RNA also accelerated the appearance of mature cardiomyocyte mRNAs (1 day after transfection vs 4 days for unmodified RNA). Importantly, these effects were lost when the 5’ppp moiety was removed. Knockdown studies suggest that 5’ppp-RNA binds to the Pattern Recognition Receptor Rig1. MNase-seq and ChIP-seq analysis suggests that 5’ppp-RNA activates YY1 (N=4, P<0.001). We next asked if 5’ppp modification of the miRNAs within miR combo would also enhance cardiomyocyte maturation; thus, providing a single molecular entity that can initiate reprogramming and accelerate maturation of cardiomyocytes. Indeed, 5’ppp modification of the miR combo miR-1 increased the expression of the mature cardiomyocyte markers Actn2 (4-fold, N=3, P<0.05) and Myh6 (4-fold, N=3, P<0.05). In conclusion, 5’ppp-miR combo is a novel approach that has the advantage of both initiating reprogramming and accelerating cardiomyocyte maturation and should lead to more effective cardiac regeneration and restore cardiac function.

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