Function Annotation in Gene Networks

Bogdanov, Petko; Macropol, Kathy; Singh, Ambuj K.

doi:10.1007/978-1-4614-0320-3_3

Cited by 2 publications

(3 citation statements)

References 53 publications

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“…by adding extra drug and target pairwise similarities) may help remedy the issues that network-based methods face in predicting interactions for orphan drugs or targets to some extent. It may also be helpful to draw inspiration from previous work on generating functional linkage networks (FLNs) [93][94][95][96]. FLNs are networks of functional associations between genes, and they have been successfully used in research related to investigating gene-related functions and diseases.…”

Section: Discussionmentioning

confidence: 99%

Computational prediction of drug–target interactions using chemogenomic approaches: an empirical survey

Ezzat¹,

Wu²,

Li³

et al. 2018

Briefings in Bioinformatics

234

184

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Computational prediction of drug-target interactions (DTIs) has become an essential task in the drug discovery process. It narrows down the search space for interactions by suggesting potential interaction candidates for validation via wet-lab experiments that are well known to be expensive and time-consuming. In this article, we aim to provide a comprehensive overview and empirical evaluation on the computational DTI prediction techniques, to act as a guide and reference for our fellow researchers. Specifically, we first describe the data used in such computational DTI prediction efforts. We then categorize and elaborate the state-of-the-art methods for predicting DTIs. Next, an empirical comparison is performed to demonstrate the prediction performance of some representative methods under different scenarios. We also present interesting findings from our evaluation study, discussing the advantages and disadvantages of each method. Finally, we highlight potential avenues for further enhancement of DTI prediction performance as well as related research directions.

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Section: Discussionmentioning

confidence: 99%

Computational prediction of drug–target interactions using chemogenomic approaches: an empirical survey

Ezzat¹,

Wu²,

Li³

et al. 2018

Briefings in Bioinformatics

234

184

View full text Add to dashboard Cite

show abstract

“…Shared membership in a module is a useful annotation in and of itself. As for more standard annotations, Bogdanov et al described four basic kinds of annotation methods using networks: direct, module‐directed, probabilistic, and pattern‐based approaches. Direct methods propagate annotation information from neighbor to neighbor.…”

Section: Practical Applications Of the Network Approach To The Study mentioning

confidence: 99%

“…Bogdanov et al have found that this assumption holds truer for genes with annotations from the “biological process” or “cellular localization” domains of the Gene Otology (GO) than for the lower‐order “molecular functions” domain. Pattern‐based annotation approaches are an alternative intended to address this disparity.…”

Section: Practical Applications Of the Network Approach To The Study mentioning

confidence: 99%

Molecular network analysis enhances understanding of the biology of mental disorders

et al. 2014

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Summary We provide an introduction to network theory, evidence to support a connection between molecular network structure and neuropsychiatric disease, and examples of how network approaches can expand our knowledge of the molecular bases of these diseases. Without systematic methods to derive their biological meanings and inter-relatedness, the many molecular changes associated with neuropsychiatric disease, including genetic variants, gene expression changes and protein differences, present an impenetrably complex set of findings. Network approaches can potentially help integrate and reconcile these findings, as well as provide new insights into the molecular architecture of neuropsychiatric diseases. Network approaches to neuropsychiatric disease are still in their infancy, and we discuss what might be done to improve their prospects.

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Function Annotation in Gene Networks

Cited by 2 publications

References 53 publications

Computational prediction of drug–target interactions using chemogenomic approaches: an empirical survey

Computational prediction of drug–target interactions using chemogenomic approaches: an empirical survey

Molecular network analysis enhances understanding of the biology of mental disorders

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