Indexing Scheme and Similarity Measures for Macromolecular Sequences

Raychaudhury, Chandan; Nandy, Ashesh

doi:10.1021/ci980077v

Cited by 63 publications

(52 citation statements)

References 5 publications

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“…Table 19 suggests that amino acid pairs having differences of 12 and 0 can be ignored, as they represent individual (chance) alignments at great separations. Thus there are a short segment with the difference of 21, a sizable segment (24,23), (25,24), (30,29), (31,30), (32,31), (33,32), (34,33), (35,34), (36,35), (39,38), (42,41), (44,43), (45,44), (46,45), (47, 46), (48,47), (49,48), (50,49), (51,50), (52,51), (55,54), (56,55), (59,58), (60,59), (61,60), …”

Section: Exact Solution To the Protein Alignment Problemmentioning

confidence: 99%

“…[6,7,35,36] For early developments of graphical bioinformatics, see the review article by A. Roy, C. Raychaudhury, and A. Nandy. [8] In the year 2000, graphical bioinformatics saw an important novelty that resulted in the expansion from this so-far essentially qualitative graphical bioinformatics, a visual discipline, into a quantitative discipline of graphical bioinformatics, defined by the numerical characterization of DNA.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Milestones in graphical bioinformatics

Randić

Novič

Plavšić

2013

Int J of Quantum Chemistry

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After reviewing the field of graphical bioinformatics, we have selected two dozen of the most significant publications that represent milestones of graphical bioinformatics. These publications can be viewed as forming the backbone of graphical bioinformatics, the branch of bioinformatics that initiates analysis of DNA, RNA, and proteins by considering various graphical representations of these sequences. Graphical bioinformatics, a division of bioinformatics that analyzes sequences of DNA, RNA, proteins, and proteomics maps by developing and using tools of discrete mathematics and graph theory in particular, has expanded since the year 2000, although pioneering contributions date back to Hamory (1983) and Jeffrey (1990). We chronologically follow the development of graphical bioinformatics, without assuming that readers are familiar with discrete mathematics or graph theory. Readers unfamiliar with graph theory may even have some advantage over those who have been only superficially exposed to graph theory, inview of wide misconceptions and misinformation about chemical graph theory among quantum chemists, physical chemists, and medicinal chemists in past decades. © 2013 Wiley Periodicals, Inc.

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Section: Exact Solution To the Protein Alignment Problemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Milestones in graphical bioinformatics

Randić

Novič

Plavšić

2013

Int J of Quantum Chemistry

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“…Raychaudhury and Nandy proposed mean x and y coordinate values, and the radius of the graph as descriptors of DNA sequences [140]. Guo and Nandy introduced also improved mean x and y coordinate values, and the radius of the graph, reducing the degeneracy of the previously defined descriptors of DNA sequences [141].…”

Section: Numerical Representations Of Dna Sequencesmentioning

confidence: 99%

Graphical and numerical representations of DNA sequences: statistical aspects of similarity

Bielińska-Wąż¹

2011

J Math Chem

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New approaches aiming at a detailed similarity/dissimilarity analysis of DNA sequences are formulated. Several corrections that enrich the information which may be derived from the alignment methods are proposed. The corrections take into account the distributions along the sequences of the aligned bases (neglected in the standard alignment methods). As a consequence, different aspects of similarity, as for example asymmetry of the gene structure, may be studied either using new similarity measures associated with four-component spectral representation of the DNA sequences or using alignment methods with corrections introduced in this paper. The corrections to the alignment methods and the statistical distribution moment-based descriptors derived from the four-component spectral representation of the DNA sequences are applied to similarity/dissimilarity studies of β-globin gene across species. The studies are supplemented by detailed similarity studies for histones H1 and H4 coding sequences. The data are described according to the latest version of the EMBL database. The work is supplemented by a concise review of the state-of-art graphical representations of DNA sequences.

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“…Gates [3] used the four cardinal directions to represent A, T, C and G and a DNA sequence can be plot points on the graph. In Nandy's method [4], if the base was an adenine the graph will be added one step in the negative x-direction and guanine, cytosine and thymine are separated represented by one step in positive xdirection, positive y-direction and negative y-direction. The Gates method [3] and Lenong Morgenthaler method [5] prescribed the GTCA and CTAG reading clockwise.…”

Section: Introductionmentioning

confidence: 99%

“…The Gates method [3] and Lenong Morgenthaler method [5] prescribed the GTCA and CTAG reading clockwise. The 2-D method have already been used in various researches by Nandy [4] [6] [7], Raychaudhury and Nandy [4], Nandy and Basak [8], Wu, Liew, Yan, and Yang [9], Yao, Nan and Wang [10] and Ghosh, Roy, Adhya and Nandy [11]. But almost all of these methods produced overlapping paths that caused degeneracy.…”

Section: Introductionmentioning

confidence: 99%

A New Method to Digitize DNA Sequence

Xu¹,

Zhu²

2017

JBM

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The global description uses composition, transition and distribution to describe an amino acid sequence and has been widely adopted in various fields. Here we integrate it with properties of nucleic acid and form a new method to digitize DNA sequence. Through this method we can use a 39-dimession vector to represent a DNA sequence. We use the exon-1 of β-Globin genes of eight species to verify this method and compare with other methods. A similar result with other method proves that this method is persuading. This method provides a new strategy to digitize DNA sequence and generates DNA sequence descriptor vector. It is different from other methods and this method only produces a 39-dimession vector and not depends on the length of DNA sequence.

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Indexing Scheme and Similarity Measures for Macromolecular Sequences

Cited by 63 publications

References 5 publications

Milestones in graphical bioinformatics

Milestones in graphical bioinformatics

Graphical and numerical representations of DNA sequences: statistical aspects of similarity

A New Method to Digitize DNA Sequence

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