Website Review: pathway databases

Wixon, Jo

doi:10.1002/cfg.123

Cited by 6 publications

(3 citation statements)

References 14 publications

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“…However, several reviews on the biochemical pathway databases are published in the literatures focusing on the analysis of cell signaling pathways and are found to be more vocal toward the discussions of the challenges that have been faced by the authors while collating and normalizing the pathway data from various resources. Meanwhile, few review articles, dedicatedly focusing on the metabolic pathway databases, are also published by highlighting their pros and cons, whereas a very few discuss on both metabolic and signaling pathway databases ( 22–27 ). Besides these reviews, the benefits, limitations and the challenges of few signaling pathway databases, mainly KEGG ( 1 ), REACTOME ( 28 ), PANTHER ( 29 ), NCI-PID ( 30 ), WikiPathways ( 31 ) and associated tools in the context of data collation for developing dynamic or quantitative model of signaling pathways are also reviewed ( 14 ).…”

Section: Introductionmentioning

confidence: 99%

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

Chowdhury

Sarkar

2015

Database

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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.

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Section: Introductionmentioning

confidence: 99%

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

Chowdhury

Sarkar

2015

Database

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“…In 2001, only 18 pathway Web sites were active. 48 Today, PathGuide.org references more than 290 pathway resources categorized by availability, data access methods, tools, organisms, network category, and contents. More than 30 million molecular interactions are accessible via the Internet.…”

Section: Introductionmentioning

confidence: 99%

“…50 More than 1400 curated, experimentally determined, metabolic pathways and enzyme data for microbial, plant, and vertebrate metabolism are available from the freely accessible MetaCyc database. 51 There are commercial and publicly available databases of molecular interactions, 52 biological pathways, 48,53,54 and genomic correlates. 55 The Signal Transduction Knowledge Environment lists 49 canonical pathways with 1084 component molecules and 33 pathways specific to a particular organism, tissue, or cell type with 718 components.…”

Section: Introductionmentioning

confidence: 99%

Computational Approaches for Translational Clinical Research in Disease Progression

McGuire

Iyengar

Mercer

2011

Journal of Investigative Medicine

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Today, there is an ever-increasing amount of biological and clinical data available that could be used to enhance a systems-based understanding of disease progression through innovative computational analysis. In this paper we review a selection of published research regarding computational methodologies, primarily from systems biology, that support translational research from the molecular level to the bedside, with a focus on applications in trauma and critical care. Trauma is the leading cause of mortality in Americans under 45 years of age, and its rapid progression offers both opportunities and challenges for computational analysis of trends in molecular patterns associated with outcomes and therapeutic interventions.This review presents methods and domain-specific examples that may inspire the development of new algorithms and computational methods that utilize both molecular and clinical data for diagnosis, prognosis and therapy in disease progression.

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Databases and Visualization for Metabolomics

Brazhnik

Kamal

et al. 2003

Metabolic Profiling: Its Role in Biomarker Discovery and Gene Function Analysis

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Website Review: pathway databases

Cited by 6 publications

References 14 publications

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

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

Computational Approaches for Translational Clinical Research in Disease Progression

Databases and Visualization for Metabolomics

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