Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Periannan Senapathy

dblp:14/6428 · DBLP profile ↗
← Back
2ranked-venue papers
0as first author
0since 2021 · last 2007
—ORCID · none

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

Systems, architecture and hardware · 1Applied, interdisciplinary, general and emerging computing · 1

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%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Parallel and multicore computing · 77% High-performance computing · 23%

Topics — the 8 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › transcriptomics
alternative splicing analysis
0.112007
EuSplice: a unified resource for the analysis of splice signals and alternative splicing in eukaryotic genes · Bioinform. 2007
Bioinformatics and computational biology
biological database
0.112007
EuSplice: a unified resource for the analysis of splice signals and alternative splicing in eukaryotic genes · Bioinform. 2007
Bioinformatics and computational biology
genome annotation
0.112007
EuSplice: a unified resource for the analysis of splice signals and alternative splicing in eukaryotic genes · Bioinform. 2007
Bioinformatics and computational biology
comparative genomics
0.012007
EuSplice: a unified resource for the analysis of splice signals and alternative splicing in eukaryotic genes · Bioinform. 2007
Bioinformatics and computational biology › genome annotation
gene prediction
0.011994
Design and Implementation of Parallel Algorithms for Gene-Finding · HPDC 1994
Bioinformatics and computational biology
genomics
0.011994
Design and Implementation of Parallel Algorithms for Gene-Finding · HPDC 1994
Parallel and multicore computing › parallel algorithms
parallel algorithm design
0.011994
Design and Implementation of Parallel Algorithms for Gene-Finding · HPDC 1994
High-performance computing
scientific computing systems
0.011994
Design and Implementation of Parallel Algorithms for Gene-Finding · HPDC 1994

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

data mining · 0.1parallel algorithm design · 0.0PVM · 0.0
YearPublicationVenuePosition
2007 EuSplice: a unified resource for the analysis of splice signals and alternative splicing in eukaryotic genes
abstract
MOTIVATION: Despite increased availability of genome annotation data, a comprehensive resource for in-depth analysis of splice signal distributions and alternative splicing (AS) patterns in eukaryote genomes is still lacking. To meet this need, we have developed EuSplice--a unique splice-centric database which provides reliable splice signal and AS information for 23 eukaryotes. RESULTS: The EuSplice database contains 95,822 AS events and 2.1 million splice signals associated with over 270,000 protein-coding genes. The intuitive, user-friendly EuSplice web interface has powerful data mining and graphics capabilities for inter-genomic comparative analysis of splice signals, putative cryptic splice sites and AS events. Moreover, the seamless integration of splicing data to extensive gene-specific annotations, such as homolog annotations, functional information, mutations and sequence details makes EuSplice a powerful one-stop information resource for investigating the molecular mechanisms of complex splicing events, disease associations and the evolution of splicing in eukaryotes. AVAILABILITY: http://66.170.16.154/EuSplice. SUPPLEMENTARY INFORMATION: Supplementary tables and figures at Bioinfo online.
Ashwini Bhasi, Ram Vinay Pandey, Suriya Prabha Utharasamy, Periannan Senapathy
Bioinform.4
1994 Design and Implementation of Parallel Algorithms for Gene-Finding
abstract
Finding genes unequivocally in DNA sequences is one of the key goals of the Human Genome project. The human genome is a 3 billion character long DNA sequence and is estimated to contain about 100000 genes. It has been shown by several biologists that genes in a DNA sequence satisfy certain special properties. We use a combination of these properties to design a serial algorithm for gene-finding. To speed up the process of finding genes in long DNA sequences (of the order of /spl ges/100000 characters), we design a parallel algorithm for gene-finding. We have implemented the parallel gene-finding algorithm on the CM-5 multicomputer as well as on a network of HP Apollo workstations under Parallel Virtual Machine software package. Experimental results indicate that our algorithms predict genes with reasonable accuracy.>
James Puthukattukaran, Suresh Chalasani, Periannan Senapathy
HPDC3