Reactome: a knowledgebase of biological pathways

Geeta, Joshi-Tope; Gillespie, Marc; Västrik, Imre; D’Eustachio, Peter; Schmidt, Esther; Bono, Bernard de; Jassal, Bijay; Gopinath, Gopal; Wu, Guanming; Matthews, Lisa; Lewis, Stephen E.; Birney, Ewan; Stein, Lincoln

doi:10.1093/nar/gki072

Cited by 1,113 publications

(775 citation statements)

References 12 publications

(9 reference statements)

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“…We applied seven prediction algorithms to the HDF data in the context of a human PPI network integrated from seven public databases [16,17,18,19,20,21,22] (see ''Data and Algorithms''). The algorithms were the SinkSource algorithm; a variant called SinkSource+ that does not need negative examples; the commonly-used guilt-by-association approach, both with and without negative examples (called Local and Local+ in this work); a method based on Hopfield networks [13]; the FunctionalFlow algorithm [14]; and another flow-based approach called PRINCE [15].…”

Section: Resultsmentioning

confidence: 99%

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Network-Based Prediction and Analysis of HIV Dependency Factors

Murali

Dyer²,

Badger

et al. 2012

Lecture Notes in Computer Science

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HIV Dependency Factors (HDFs) are a class of human proteins that are essential for HIV replication, but are not lethal to the host cell when silenced. Three previous genome-wide RNAi experiments identified HDF sets with little overlap. We combine data from these three studies with a human protein interaction network to predict new HDFs, using an intuitive algorithm called SinkSource and four other algorithms published in the literature. Our algorithm achieves high precision and recall upon cross validation, as do the other methods. A number of HDFs that we predict are known to interact with HIV proteins. They belong to multiple protein complexes and biological processes that are known to be manipulated by HIV. We also demonstrate that many predicted HDF genes show significantly different programs of expression in early response to SIV infection in two non-human primate species that differ in AIDS progression. Our results suggest that many HDFs are yet to be discovered and that they have potential value as prognostic markers to determine pathological outcome and the likelihood of AIDS development. More generally, if multiple genome-wide gene-level studies have been performed at independent labs to study the same biological system or phenomenon, our methodology is applicable to interpret these studies simultaneously in the context of molecular interaction networks and to ask if they reinforce or contradict each other.

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Section: Resultsmentioning

confidence: 99%

“…We gathered human proteinprotein interaction data from seven public databases, BIND, DIP, HPRD, IntAct, MINT, MIPS, and Reactome [16,17,18,19,20,21,22]. After removing duplicate interactions and selfinteractions, we obtained a total of 71,461 interactions involving 9,595 proteins.…”

Section: Datasets Usedmentioning

confidence: 99%

Network-Based Prediction and Analysis of HIV Dependency Factors

Murali

Dyer²,

Badger

et al. 2012

Lecture Notes in Computer Science

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“…However, even category (5) contains signalogs for which at least one novel signaling pathway membership is predicted. Additionally, to check the novelty of the predicted signaling pathway memberships, we compared the list of signalogs and their predicted pathway memberships to known pathway membership annotations from Reactome and KEGG [33,34]. We next applied interologs to verify the novelty of our ortholog predictions (an interolog is a pair of proteins predicted to interact based on the interaction of the two proteins' orthologs in at least one other organism) [7].…”

Section: Defining the Novelty Of Signaling Protein Predictions Basedmentioning

confidence: 99%

Uniform Curation Protocol of Metazoan Signaling Pathways to Predict Novel Signaling Components

Pálfy

Farkas

Vellai

et al. 2013

Methods in Molecular Biology

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A relatively large number of signaling databases available today have strongly contributed to our understanding of signaling pathway properties. However, pathway comparisons both within and across databases are currently severely hampered by the large variety of data sources and the different levels of detail of their information content (on proteins and interactions). In this chapter, we present a protocol for a uniform curation method of signaling pathways, which intends to overcome this insufficiency. This uniformly curated database called SignaLink (http://signalink.org) allows us to systematically transfer pathway annotations between different species, based on orthology, and thereby to predict novel signaling pathway components. Thus, this method enables the compilation of a comprehensive signaling map of a given species and identification of new potential drug targets in humans.We strongly believe that the strict curation protocol we have established to compile a signaling pathway database can also be applied for the compilation of other (e.g., metabolic) databases. Similarly, the detailed guide to the orthology-based prediction of novel signaling components across species may also be utilized for predicting components of other biological processes.

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“…The very basic unit in Reactome is the reaction and these reactions are grouped together to form the normal pathways. It allows the possibility of qualitative framework that allows superimposition of quantitative data (Joshi-Tope, 2005).…”

Section: Pathway Databasesmentioning

confidence: 99%

BioSilicoSystems - A Multipronged Approach Towards Analysis and Representation of Biological Data (PhD Thesis)

Hariharaputran

2010

Nat Prec

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The rising field of integrative bioinformatics provides the vital methods to integrate, manage and also to analyze the diverse data and allows gaining new and deeper insights and a clear understanding of the intricate biological systems. The difficulty is not only to facilitate the study of heterogeneous data within the biological context, but it also more fundamental, how to represent and make the available knowledge accessible. Moreover, adding valuable information and functions that persuade the user to discover the interesting relations hidden within the data is, in itself, a great challenge. Also, the cumulative information can provide greater biological insight than is possible with individual information sources. Furthermore, the rapidly growing number of databases and data types poses the challenge of integrating the heterogeneous data types, especially in biology. This rapid increase in the volume and number of data resources drive for providing polymorphic views of the same data and often overlap in multiple resources.In this thesis a multi-pronged approach is proposed that deals with various methods for the analysis and representation of the diverse biological data which are present in different data sources. This is an effort to explain and emphasize on different concepts which are developed for the analysis of molecular data and also to explain its biological significance. The hypotheses proposed are in context with various other results and findings published in the past. The approach demonstrated also explains different ways to integrate the molecular data from various sources along with the need for a comprehensive understanding and clear projection of the concept or the algorithm and its results, but with simple means and methods. The multifarious approach proposed in this work comprises of different tools or methods spanning significant areas of bioinformatics research such as data integration, data visualization, biological network construction / reconstruction and alignment of biological pathways. Each tool deals with a unique approach to utilize the molecular data for different areas of biological research and is built based on the kernel of the thesis. Furthermore these methods are combined with graphical representation that make things simple and comprehensible and also helps to understand with ease the underlying biological complexity. Moreover the human eye is often used to and it is more comfortable with the visual representation of the facts.

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Reactome: a knowledgebase of biological pathways

Cited by 1,113 publications

References 12 publications

Network-Based Prediction and Analysis of HIV Dependency Factors

Network-Based Prediction and Analysis of HIV Dependency Factors

Uniform Curation Protocol of Metazoan Signaling Pathways to Predict Novel Signaling Components

BioSilicoSystems - A Multipronged Approach Towards Analysis and Representation of Biological Data (PhD Thesis)

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