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A. Ayaz

dblp:35/4509 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2004
—ORCID · none

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

Applied, 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
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › systems bioinformatics › pathway analysis
cellular pathway analysis
0.012004
An ontology for collaborative construction and analysis of cellular pathways · Bioinform. 2004
Bioinformatics and computational biology › systems bioinformatics
pathway representation
0.012004
An ontology for collaborative construction and analysis of cellular pathways · Bioinform. 2004

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

pathway integration · 0.0ontology design · 0.0
YearPublicationVenuePosition
2004 An ontology for collaborative construction and analysis of cellular pathways
abstract
MOTIVATION: As the scientific curiosity in genome studies shifts toward identification of functions of the genomes in large scale, data produced about cellular processes at molecular level has been accumulating with an accelerating rate. In this regard, it is essential to be able to store, integrate, access and analyze this data effectively with the help of software tools. Clearly this requires a strong ontology that is intuitive, comprehensive and uncomplicated. RESULTS: We define an ontology for an intuitive, comprehensive and uncomplicated representation of cellular events. The ontology presented here enables integration of fragmented or incomplete pathway information via collaboration, and supports manipulation of the stored data. In addition, it facilitates concurrent modifications to the data while maintaining its validity and consistency. Furthermore, novel structures for representation of multiple levels of abstraction for pathways and homologies is provided. Lastly, our ontology supports efficient querying of large amounts of data. We have also developed a software tool named pathway analysis tool for integration and knowledge acquisition (PATIKA) providing an integrated, multi-user environment for visualizing and manipulating network of cellular events. PATIKA implements the basics of our ontology.
Emek Demir, Ozgun Babur, Ugur Dogrusoz, Attila Gürsoy, A. Ayaz, Gürcan Gülesir, Gurkan Nisanci, Rengül Çetin-Atalay
Bioinform.5