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Ramakrishna Ramaswamy

dblp:53/2721 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2004
0000-0002-9085-8224ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
2 papers
Bioinformatics and computational biology · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
genomics
0.122004
Spectral Repeat Finder (SRF): identification of repetitive sequences using Fourier transformation · Bioinform. 2004
Prediction of probable genes by Fourier analysis of genomic sequences · Comput. Appl. Biosci. 1997
Bioinformatics and computational biology › sequence analysis
repeat detection
0.012004
Spectral Repeat Finder (SRF): identification of repetitive sequences using Fourier transformation · Bioinform. 2004
Bioinformatics and computational biology › genome annotation
gene prediction
0.011997
Prediction of probable genes by Fourier analysis of genomic sequences · Comput. Appl. Biosci. 1997
Bioinformatics and computational biology
sequence analysis
0.012004
Spectral Repeat Finder (SRF): identification of repetitive sequences using Fourier transformation · Bioinform. 2004
Bioinformatics and computational biology › sequence analysis
sequence visualization
0.012004
Spectral Repeat Finder (SRF): identification of repetitive sequences using Fourier transformation · Bioinform. 2004

Methods — techniques the papers use, named apart from their topics

sliding window analysis · 0.0discrete fourier transform · 0.0spectral analysis · 0.0fourier analysis · 0.0
YearPublicationVenuePosition
2004 Spectral Repeat Finder (SRF): identification of repetitive sequences using Fourier transformation
abstract
MOTIVATION: Repetitive DNA sequences, besides having a variety of regulatory functions, are one of the principal causes of genomic instability. Understanding their origin and evolution is of fundamental importance for genome studies. The identification of repeats and their units helps in deducing the intra-genomic dynamics as an important feature of comparative genomics. A major difficulty in identification of repeats arises from the fact that the repeat units can be either exact or imperfect, in tandem or dispersed, and of unspecified length. RESULTS: The Spectral Repeat Finder program circumvents these problems by using a discrete Fourier transformation to identify significant periodicities present in a sequence. The specific regions of the sequence that contribute to a given periodicity are located through a sliding window analysis, and an exact search method is then used to find the repetitive units. Efficient and complete detection of repeats is provided together with interactive and detailed visualization of the spectral analysis of input sequence. We demonstrate the utility of our method with various examples that contain previously unannotated repeats. A Web server has been developed for convenient access to the automated program. AVAILABILITY: The Web server is available at http://www.imtech.res.in/raghava/srf and http://www2.imtech.res.in/raghava/srf
Biju Issac 0002, Gajendra P. S. Raghava, Ramakrishna Ramaswamy
Bioinform.4
1997 Prediction of probable genes by Fourier analysis of genomic sequences
abstract
MOTIVATION: The major signal in coding regions of genomic sequences is a three-base periodicity. Our aim is to use Fourier techniques to analyse this periodicity, and thereby to develop a tool to recognize coding regions in genomic DNA. RESULT: The three-base periodicity in the nucleotide arrangement is evidenced as a sharp peak at frequency f = 1/3 in the Fourier (or power) spectrum. From extensive spectral analysis of DNA sequences of total length over 5.5 million base pairs from a wide variety or organisms (including the human genome), and by separately examining coding and non-coding sequences, we find that the relative-height of the peak at f = 1/3 in the Fourier spectrum is a good discriminator of coding potential. This feature is utilized by us to detect probable coding regions in DNA sequences, by examining the local signal-to-noise ratio of the peak within a sliding window. While the overall accuracy is comparable to that of other techniques currently in use, the measure that is presently proposed is independent of training sets or existing database information, and can thus find general application. AVAILABILITY: A computer program GeneScan which locates coding open reading frames and exonic regions in genomic sequences has been developed, and is available on request.
Alok Bhattacharya, Ramakrishna Ramaswamy
Comput. Appl. Biosci.5