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The SIDER database of drugs and side effects
2015
Nucleic Acids Research
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To this end, we have created the SIDER ('Side Effect Resource', http://sideeffects.embl.de) database of drugs and ADRs. ...
Unwanted side effects of drugs are a burden on patients and a severe impediment in the development of new drugs. ...
We present here a new release of the SIDER database with over 40% more drugs, ADRs and drug-ADR pairs compared to the previous version and more than 2-fold as many drug-ADR pairs as the published version ...
doi:10.1093/nar/gkv1075
pmid:26481350
pmcid:PMC4702794
fatcat:4vassewagbbvvdsr2gkygugzg4
Investigating Side Effect Modules in the Interactome and Their Use in Drug Adverse Effect Discovery
[chapter]
2017
Complex Networks VIII
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We find that drug targets are closer in the interactome to the proteins inducing the known side effects of the drug compared to the proteins associated with the rest of the side effects. ...
In this study, we investigate the role of network topology in explaining observed side effects of drugs. ...
Acknowledgements The author is grateful to Dr. Patrick Aloy for providing computational resources for this study and the members of the lab for fruitful discussions. ...
doi:10.1007/978-3-319-54241-6_21
fatcat:l25vqid43bba3cawvbklkvl7fi
Leveraging graph topology and semantic context for pharmacovigilance through twitter-streams
2016
BMC Bioinformatics
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Methods: We use a bipartite graph-theoretic representation called a drug-effect graph (DEG) for modeling drug and side effect relationships by representing the drugs and side effects as vertices. ...
The first DEG is constructed from the drug-effect relationships found in FDA package inserts as recorded in the SIDER database. The second DEG is constructed by mining the history of Twitter users. ...
Availability of data and material The data files to construct DEG Sider are available through the SIDER website: http://sideeffects.embl.de/download/. ...
doi:10.1186/s12859-016-1220-5
pmid:27766937
pmcid:PMC5073861
fatcat:dg4ym374kjeznkuo63ycftagty
Investigating side effect modules in the interactome and their use in drug adverse effect discovery
[article]
2016
bioRxiv
pre-print
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We find that drug targets are closer in the interactome to the proteins inducing the known side effects of the drug compared to the proteins associated with the rest of the side effects. ...
In this study, we investigate the role of network topology in explaining observed side effects of drugs. ...
Acknowledgements The author is grateful to Dr. Patrick Aloy for providing computational resources for this study and the members of the lab for fruitful discussions. ...
doi:10.1101/089730
fatcat:3dmlc5qixrg2pelmm6upqea3vi
Network-based method to infer the contributions of proteins to the etiology of drug side effects
2015
Quantitative Biology
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We applied this method to a wide range of side effects and validated the results using cross-validation and records from the Side Effect Resource database. ...
Studying the molecular mechanisms that underlie the relationship between drugs and the side effects they produce is critical for drug discovery and drug development. ...
(SIDER2) versions of SIDER, a database recording drug-side effect relationships. ...
doi:10.1007/s40484-015-0051-0
fatcat:6yqvednb5jeo5pmhjfabpx3y3m
Comparing a knowledge-driven approach to a supervised machine learning approach in large-scale extraction of drug-side effect relationships from free-text biomedical literature
2015
BMC Bioinformatics
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Systems approaches to studying drug-side-effect (drug-SE) associations are emerging as an active research area for both drug target discovery and drug repositioning. ...
Results: On average, the KD approach has achieved a precision of 0.335, a recall of 0.509, and an F1 of 0.392, which is significantly better than a SVM-based machine learning approach (precision: 0.135 ...
The overall performance depends on the accuracy and comprehensiveness of the SIDER database. ...
doi:10.1186/1471-2105-16-s5-s6
pmid:25860223
pmcid:PMC4402591
fatcat:7jhupjq57jhz5ial7js5rvgmbi
GraphSAW: A web-based system for graphical analysis of drug interactions and side effects using pharmaceutical and molecular data
2015
BMC Medical Informatics and Decision Making
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The concordance of drug interactions was about 12% and 9% of drug side effects. ...
The results of the data analysis give an overview of all theoretically possible drug interactions and side effects. The evaluation shows a mismatch between pharmaceutical and molecular databases. ...
The project was funded by the Federal Ministry of Economics and Technology (BMWi) and European Social Fund (ESF). ...
doi:10.1186/s12911-015-0139-5
pmid:25881043
pmcid:PMC4350865
fatcat:injitezth5fetdeptjulot7sxe
An ensemble approach for drug side effect prediction
2013
2013 IEEE International Conference on Bioinformatics and Biomedicine
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We applied our approach to 1385 side-effects in the SIDER database for 888 drugs. Results show that our approach outperformed previously published approaches and standard classifiers. ...
Furthermore, we applied our method to a number of uncharacterized drug molecules in DrugBank database and predict their side-effect profiles for future usage. ...
This research was supported in part by the National Science Foundation (1IS-1218201), National Institutes of Health (SC3GM086305, U54CAl13001, G12MD007591 (Computational Systems Biology Core)), and a UTSA ...
doi:10.1109/bibm.2013.6732532
pmid:25327524
pmcid:PMC4197807
fatcat:26dltwwqabfzfjg5yhqiq6cjxy
Targets of drugs are generally and targets of drugs having side effects are specifically good spreaders of human interactome perturbations
2015
Scientific Reports
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Our main question in this paper was whether the efficiency of drug target proteins to spread perturbations in the human interactome is larger if the binding drugs have side effects, as compared to those ...
Our results showed that in general, drug targets were better spreaders of perturbations than non-target proteins, and in particular, targets of drugs with side effects were also better spreaders of perturbations ...
T.K. was a grantee of the János Bolyai Scholarship of the Hungarian Academy of Sciences, and is supported by a fellowship in computational biology at The Genome Analysis Centre, in partnership with the ...
doi:10.1038/srep10182
pmid:25960144
pmcid:PMC4426692
fatcat:jgzn2aalrbdlzeylumbucmb7m4
Data-Driven Prediction of Drug Effects and Interactions
2012
Science Translational Medicine
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We also present a comprehensive database of drug effects (OFFSIDES) and a database of drug-drug interaction side effects (TWOSIDES). ...
We conclude that confounding effects from covariates in observational clinical data can be controlled in data analyses and thus improve the detection and prediction of adverse drug effects and interactions ...
Oliver, and D. Ludwig for useful comments and discussion. ...
doi:10.1126/scitranslmed.3003377
pmid:22422992
pmcid:PMC3382018
fatcat:mp3qniumxnhqnlh7wcyfearjum
Integrative relational machine-learning for understanding drug side-effect profiles
2013
BMC Bioinformatics
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Results: In this work, drug annotations are collected from SIDER and DrugBank databases. ...
Improving our ability to understand drug side effects is necessary to reduce attrition rates during drug development as well as the risk of discovering novel side effects in available drugs. ...
Thanks to Dave Ritchie and Anisah Ghoorah for their careful reading of the paper.
Author details ...
doi:10.1186/1471-2105-14-207
pmid:23802887
pmcid:PMC3710241
fatcat:ieydyhshfjfspmofazziubge5m
Drug-disease Graph: Predicting Adverse Drug Reaction Signals via Graph Neural Network with Clinical Data
[article]
2020
arXiv
pre-print
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We apply Graph Neural Network to predict ADR signals, using labels from the Side Effect Resource database. ...
The model shows improved AUROC and AUPRC performance of 0.795 and 0.775, compared to other algorithms, showing that it successfully learns node representations expressive of those relationships. ...
registered in the SIDER database respectively, and E SIDER is the set of drug-disease pairs that are known to have side effect relation according to the SIDER database. ...
arXiv:2004.00407v1
fatcat:on4dvs2n7zen5jh3jk7xooo3pq
Drug target prediction using adverse event report systems: a pharmacogenomic approach
2012
Bioinformatics
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drug-target interactions on a large scale from the integration of pharmacological similarity of drugs and genomic sequence similarity of target proteins in the framework of a pharmacogenomic approach. ...
The proposed method was applicable to a large number of drugs and it was useful especially for predicting unknown drug-target interactions that could not be expected from drug chemical structures. ...
Side effect keywords for drugs were obtained from the SIDER database [http://sideeffects.embl.de/] which contains information about marketed medicines and their recorded side effects or adverse drug reactions ...
doi:10.1093/bioinformatics/bts413
pmid:22962489
pmcid:PMC3436840
fatcat:rpqkm3xpvzeofp7bnvrciymwwa
Using Drug Similarities for Discovery of Possible Adverse Reactions
2017
AMIA Annual Symposium Proceedings
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We implemented the proposed method in the form of a software prototype and evaluated our approach by discarding known drug-side effect links from our data and checking whether our prototype is able to ...
side effects. ...
The materials contain pre-processed versions of DrugBank and SIDER data sets from Bio2RDF v4.0, including fixing of a few syntax errors and a simple documentation. ...
pmid:28269889
pmcid:PMC5333276
fatcat:lhteztt2wjcodiyhrtvlgw3ul4
Translating Clinical Findings into Knowledge in Drug Safety Evaluation - Drug Induced Liver Injury Prediction System (DILIps)
2011
PLoS Computational Biology
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We hypothesized that the DILI types (hepatotoxic side effects) seen in the clinic can be translated into the development of predictive in silico models for use in the drug discovery phase. ...
We identified 13 hepatotoxic side effects with high accuracy for classifying marketed drugs for their DILI potential. ...
We used the SIDER database [12] to identify drugs and associated side effects. ...
doi:10.1371/journal.pcbi.1002310
pmid:22194678
pmcid:PMC3240589
fatcat:hrz7snb57vetxen47y5kheamci
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