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Recent Advances in Network-based Methods for Disease Gene Prediction
[article]
2020
arXiv
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In this survey, we aim to provide a comprehensive and an up-to-date review of network-based methods for disease gene prediction. We also conduct an empirical analysis on 14 state-of-the-art methods. ...
Since molecular networks are able to capture complex interplay among molecules in diseases, they become one of the most extensively used data for disease-gene association prediction. ...
Then, we introduce various network-based diseasegene prediction methods in details in Section 'Network-based Methods for Disease Gene Prediction'. ...
arXiv:2007.10848v1
fatcat:zhrspbsj6zfpfhwa42mzjp4lvy
Advanced Systems Biology Methods in Drug Discovery and Translational Biomedicine
2013
BioMed Research International
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gene prediction. ...
In addition, important advances in drug discovery, to which systems biology makes significant contributions, are discussed, including drug-target networks, prediction of drug-target interactions, investigation ...
This new method is based on the observation that similar drugs are indicated for similar diseases and utilizes the chemical similarity of drugs and disease-disease similarity measures for the prediction ...
doi:10.1155/2013/742835
pmid:24171171
pmcid:PMC3792523
fatcat:nhsv3ig7vzgspjhnzkaj3pwypm
The Impact of Network Medicine in Gastroenterology and Hepatology
2013
Clinical Gastroenterology and Hepatology
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Figure 2 . 2 Network-based discovery of gene-disease associations in complex disease A. ...
Technological primer: Systems biology strategies for finding gene-disease associations Big data science: Cataloging the parts A number of recent advances in biomedical technologies began to tackle complexity ...
doi:10.1016/j.cgh.2013.07.033
pmid:23932906
fatcat:emuddivujvbbdbf7pbun5n64ze
A General Computational Framework for Prediction of Disease-associated Non-coding RNAs
2019
VNU Journal of Science Computer Science and Communication Engineering
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To date, many computational methods have been also proposed for prediction of disease-associated miRNAs and lncRNAs, and recently comprehensively reviewed. ...
Therefore, in this study, we propose a general computational framework for prediction of disease-associated ncRNAs. ...
Acknowledgements Funding: This research is funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under grant number 102.01-2017.14. ...
doi:10.25073/2588-1086/vnucsce.224
fatcat:6ivojgsgh5bonkasyseodx34fm
Drug Repurposing Using Biological Networks
2021
Processes
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The goal of this review is to show the usefulness of these computational methods to predict associations and to find candidate drugs for repositioning in new indications of certain diseases. ...
This allows the use of computational methods and models based on biological networks to develop new possibilities for drug repurposing. ...
In recent years, network-based methods have become a major strategy for drug repositioning [4, 9] . ...
doi:10.3390/pr9061057
fatcat:wrdrh3hi65gszjec2prg6pixn4
Biomolecular Networks for Complex Diseases
2018
Complexity
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In the paper "DriverFinder: A Gene Length-Based Network Method to Identify Cancer Driver Genes," P.-J. ...
In the paper "SDTRLS: Predicting Drug-Target Interactions for Complex Diseases Based on Chemical Substructures," C. ...
In summary, this focus issue has reported the recent progress in the studies of biomolecular networks for complex diseases. ...
doi:10.1155/2018/4210160
fatcat:2boeaxsahbdkjekgwpkv23r4be
The Emerging Paradigm of Network Medicine in the Study of Human Disease
2012
Circulation Research
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This review introduces the fundamental concepts of network medicine and explores the feasibility and potential impact of network-based methods for predicting individual manifestations of human disease ...
As methodologies evolve, network medicine has the potential to capture the molecular complexity of human disease while offering computational methods to discern how such complexity controls disease manifestations ...
Acknowledgments We thank Stephanie Tribuna for expert administrative assistance and Sol Chan for assistance with figures. ...
doi:10.1161/circresaha.111.258541
pmid:22821909
pmcid:PMC3425394
fatcat:m4zwmfv42vejrpd3kkbpx2k4h4
Computational Systems Biology
2013
The Scientific World Journal
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In this special issue, we reported the recent progress made in developing new computational methodologies to analyze the genomics data, construct gene networks, and identify disease genes. ...
In recent years, the advance of next-generation sequencing (NGS) technology makes it more easier for researchers to access and analyze genetics data and has influential effects on the biomedical research ...
Acknowledgments We would like to thank all reviewers for their invaluable contributions to the peer review process which have made this special issue possible. ...
doi:10.1155/2013/350358
pmid:23576901
pmcid:PMC3612478
fatcat:2y33vzm44vcrpb6puwiunlwt7e
Editorial: Graph Embedding Methods for Multiple-Omics Data Analysis
2021
Frontiers in Genetics
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Pan et al. presented an embedding-based method for predicting the subcellular localization of proteins. ...
Recently, machine learning methods especially graph embedding have shown powerful capability in analyzing multiple-omics data. ...
National Natural Science Foundation of China (Nos. 62072124, 61963004, and 61972185), the Natural Science Foundation of Guangxi (Nos. 2021GXNSFAA075041 and 2018GXNSFBA281193), the Science and Technology Base ...
doi:10.3389/fgene.2021.762274
pmid:34616440
pmcid:PMC8488216
fatcat:msr5ycebtned3hz27dieediyiu
Incorporating Machine Learning into Established Bioinformatics Frameworks
2021
International Journal of Molecular Sciences
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Here, we review recently developed methods that incorporate machine learning within the same framework with techniques from molecular evolution, protein structure analysis, systems biology, and disease ...
We outline the challenges posed for machine learning, and, in particular, deep learning in biomedicine, and suggest unique opportunities for machine learning techniques integrated with established bioinformatics ...
These methods primarily exploit recent advances in deep learning architectures to enhance the prediction of PPI networks [93] . ...
doi:10.3390/ijms22062903
pmid:33809353
pmcid:PMC8000113
fatcat:ssfoobbtcjhidbaffbkakqbwfe
Review of Biological Network Data and Its Applications
2013
Genomics & Informatics
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Accordingly, this paper covers two major topics in network biology: reconstruction of gene regulatory networks and network-based applications, including protein function prediction, disease gene prioritization ...
In this review, we focus on network-based approaches that help in understanding biological systems and identifying biological functions. ...
The methods are summarized in
Table 3 [10, 11, 13-16, 59-83].
Table 4 . 4 Network-based disease gene prioritization methods
. ...
doi:10.5808/gi.2013.11.4.200
pmid:24465231
pmcid:PMC3897847
fatcat:v72gan3nara6xfqwbxwwljzouq
An outlook on metabolic pathway engineering in crop plants
2020
Archives of Agriculture and Environmental Science
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Mathematical and statistical models to scale and map the genome for integrative metabolic pathway activity, signal transduction mechanism in the genome, gene regulation and the networks of protein-protein ...
Recently, artificial intelligence concept and approaches are experimentally applied for efficient and accurate metabolic engineering in plants. ...
DeepEc (Ryu et al., 2019) is another convolutional neural networks-based method with homology analysis for predicting enzyme using protein sequences as inputs. ...
doi:10.26832/24566632.2020.0503027
fatcat:qml5yxl54vhh3hpyqsgbboasfa
Network biology methods integrating biological data for translational science
2012
Briefings in Bioinformatics
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In this review, recent advances in network biology approaches and results are identified. ...
can be jointly analyzed to understand and predict disease phenotypes. ...
Acknowledgements The authors would like to acknowledge James Eddy for making ...
doi:10.1093/bib/bbr075
pmid:22390873
pmcid:PMC3404396
fatcat:cdfuoph3o5b5bcpdkfgop4fzpy
Identification of aberrant pathways and network activities from high-throughput data
2012
Briefings in Bioinformatics
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Many complex diseases such as cancer are associated with changes in biological pathways and molecular networks rather than being caused by single gene alterations. ...
This review presents recent progress in using high-throughput biological assays to decipher aberrant pathways and network activities. ...
Rhoda Perozzi for her kindness in performing a thorough review and edit. We thank the anonymous reviewers for their suggestions for improving the manuscript. ...
doi:10.1093/bib/bbs001
pmid:22287794
pmcid:PMC3404398
fatcat:woielqwwtbc6bhdoub3hycnu6a
A survey of current trends in computational drug repositioning
2015
Briefings in Bioinformatics
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In this review, we show recent advancements in the critical areas of computational drug repositioning from multiple aspects. ...
Third, we discuss validation strategies for repositioning studies, including both computational and experimental methods. ...
Acknowledgment The authors would like to thank Dr Pankaj Agarwal for his helpful discussion. ...
doi:10.1093/bib/bbv020
pmid:25832646
pmcid:PMC4719067
fatcat:aogwknlldvhtxfct5wwmorqtk4
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