Drug target prioritization by perturbed gene expression and network information

Işık, Zerrin; Baldow, Christoph; Cannistraci, Carlo Vittorio; Schroeder, Michael

doi:10.1038/srep17417

Cited by 118 publications

(138 citation statements)

References 39 publications

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“…The most affected proteins are not the direct target proteins of the given drugs, since they placed in the lower levels, most commonly in the 3 rd level, of the tree. This result was also found in recent studies [9], [10]. These proteins have activities in the distant parts of signaling pathways and showed the most remarkable reactions in this pathway after the application of drug treatments.…”

Section: Resultssupporting

confidence: 85%

“…Therefore, signaling pathway and interaction network analysis became more attractive to give a new perspective for the classic analysis of gene expression data [14]- [16]. New algorithms have started to highlight important regulator proteins and International Journal of Bioscience, Biochemistry and Bioinformatics cellular processes in pathways; such results had not been found by applying naive differentially expression analysis [9], [17]- [20].…”

Section: Resultsmentioning

confidence: 99%

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Estimation of Drug Treatment Effects on the Signaling Pathways

Erce¹,

Işık²

2017

IJBBB

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Developing a computational method to observe cell behaviors can help to understand the expected outcome of a drug treatment even before doing the wet-lab experiments. The main goal of this research is computing the effects of a drug treatment in the signaling level for a better understanding of cellular responses after a drug treatment. The proposed algorithm can work on various biological networks to quantitatively evaluate the effects of a drug treatment in the cell by using gene expression data. The method was applied on the integrated KEGG signaling pathway and the most effected proteins were identified after the application of 14 different drugs on lymphoma cells. The results showed that the most affected proteins are not the direct target proteins of the given drugs. Indeed, the protein activities in the distant parts of signaling pathways are highly changed upon drug treatments. The literature validation showed that some of the proteins, which are commonly effected by the treatment of several drugs, have cancer related cellular activities as well.

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Section: Resultssupporting

confidence: 85%

Section: Resultsmentioning

confidence: 99%

Estimation of Drug Treatment Effects on the Signaling Pathways

Erce¹,

Işık²

2017

IJBBB

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“…However, these methods are built ad hoc to solve a specific problem. Many of these approaches have been proposed for the identification of novel gene-disease potential associations [10] or drug-disease associations for drug repositioning [11]. These methods usually focus more on the data sources integrated into the network than on the algorithm used to propagate the information within and/or accross networks, or they provide an algorithm that is tightly coupled to the data sources in use.…”

Section: Resultsmentioning

confidence: 99%

ProphTools: general prioritization tools for heterogeneous biological networks

et al. 2017

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BackgroundNetworks have been proven effective representations for the analysis of biological data. As such, there exist multiple methods to extract knowledge from biological networks. However, these approaches usually limit their scope to a single biological entity type of interest or they lack the flexibility to analyze user-defined data.ResultsWe developed ProphTools, a flexible open-source command-line tool that performs prioritization on a heterogeneous network. ProphTools prioritization combines a Flow Propagation algorithm similar to a Random Walk with Restarts and a weighted propagation method. A flexible model for the representation of a heterogeneous network allows the user to define a prioritization problem involving an arbitrary number of entity types and their interconnections. Furthermore, ProphTools provides functionality to perform cross-validation tests, allowing users to select the best network configuration for a given problem. ProphTools core prioritization methodology has already been proven effective in gene-disease prioritization and drug repositioning. Here we make ProphTools available to the scientific community as flexible, open-source software and perform a new proof-of-concept case study on long noncoding RNAs (lncRNAs) to disease prioritization.ConclusionsProphTools is robust prioritization software that provides the flexibility not present in other state-of-the-art network analysis approaches, enabling researchers to perform prioritization tasks on any user-defined heterogeneous network. Furthermore, the application to lncRNA-disease prioritization shows that ProphTools can reach the performance levels of ad hoc prioritization tools without losing its generality.

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“…Therefore, the data predicted in in silico approaches would be recorded into HEDD, such as molecular docking, virtual screening, pharmacophore modeling, molecular dynamics and similarity searching. As a resource to study the potential roles of epigenetic drugs in remodeling epigenetic modification, HEDD could be extended with utilities for the identification and confirmation of targets (genes and pathways) related to epigenetic drugs from large-scale high-throughput data (such as gene expression) (42, 43). Since mice are very important for modeling diseases and testing drugs, we would extend the research scope and integrate high-throughput data for mice treated with epigenetic drugs into HEDD.…”

Section: Database Use and Accessmentioning

confidence: 99%

HEDD: the human epigenetic drug database

Qi¹,

Wang²,

Wang³

et al. 2016

Database

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Epigenetic drugs are chemical compounds that target disordered post-translational modification of histone proteins and DNA through enzymes, and the recognition of these changes by adaptor proteins. Epigenetic drug-related experimental data such as gene expression probed by high-throughput sequencing, co-crystal structure probed by X-RAY diffraction and binding constants probed by bio-assay have become widely available. The mining and integration of multiple kinds of data can be beneficial to drug discovery and drug repurposing. HEMD and other epigenetic databases store comprehensively epigenetic data where users can acquire segmental information of epigenetic drugs. However, some data types such as high-throughput datasets are not provide by these databases and they do not support flexible queries for epigenetic drug-related experimental data. Therefore, in reference to HEMD and other epigenetic databases, we developed a relatively comprehensive database for human epigenetic drugs. The human epigenetic drug database (HEDD) focuses on the storage and integration of epigenetic drug datasets obtained from laboratory experiments and manually curated information. The latest release of HEDD incorporates five kinds of datasets: (i) drug, (ii) target, (iii) disease, (vi) high-throughput and (v) complex. In order to facilitate data extraction, flexible search options were built in HEDD, which allowed an unlimited condition query for specific kinds of datasets using drug names, diseases and experiment types.Database URL: http://hedds.org/

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Drug target prioritization by perturbed gene expression and network information

Cited by 118 publications

References 39 publications

Estimation of Drug Treatment Effects on the Signaling Pathways

Estimation of Drug Treatment Effects on the Signaling Pathways

ProphTools: general prioritization tools for heterogeneous biological networks

HEDD: the human epigenetic drug database

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