Understanding Schema Evolution as a Basis for Database Reengineering

Gobert, Maxime; Maes, Jerome; Cleve, Anthony; Weber, Jens H.

doi:10.1109/icsm.2013.75

Cited by 6 publications

(1 citation statement)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To compare the tools and techniques available in the databases, it is first required to compare the database structure and schema as the smoother access of different computational operations is based on these two factors ( 92 , 93 ). A database schema describes the structure and entire configuration of a database in a specific conceptual language, which is managed by a database management system ( 93 ). Different types of database management systems are proposed till now and out of which relational, object or relational object database management systems are widely used and well accepted to most of the database developers ( 94 ).…”

Section: Database Comparisonmentioning

confidence: 99%

Comparison of human cell signaling pathway databases—evolution, drawbacks and challenges

Chowdhury

Sarkar

2015

Database

View full text Add to dashboard Cite

Elucidating the complexities of cell signaling pathways is of immense importance to gain understanding about various biological phenomenon, such as dynamics of gene/protein expression regulation, cell fate determination, embryogenesis and disease progression. The successful completion of human genome project has also helped experimental and theoretical biologists to analyze various important pathways. To advance this study, during the past two decades, systematic collections of pathway data from experimental studies have been compiled and distributed freely by several databases, which also integrate various computational tools for further analysis. Despite significant advancements, there exist several drawbacks and challenges, such as pathway data heterogeneity, annotation, regular update and automated image reconstructions, which motivated us to perform a thorough review on popular and actively functioning 24 cell signaling databases. Based on two major characteristics, pathway information and technical details, freely accessible data from commercial and academic databases are examined to understand their evolution and enrichment. This review not only helps to identify some novel and useful features, which are not yet included in any of the databases but also highlights their current limitations and subsequently propose the reasonable solutions for future database development, which could be useful to the whole scientific community.

show abstract

Section: Database Comparisonmentioning

confidence: 99%