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Integrated biomedical data analysis utilizing various types of data for biomarkers identification

Ping Zhang, Amanda Cox, Allan Cripps, Nicholas West
2017 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)  
Realising the nature of the data in biomedical research and translational biomedicine, we developed a data analysis pipeline with a set of computational functions and an integrated method that can serve  ...  Biomarkers discovery research requires the integrated analyses of a variety of the data across multiple domains, including clinical data, pathology data, gene expression, epigenetic data.  ...  The data analysis pipeline can serve as a template for different biomarker studies that require analysis of various types of data.  ... 
doi:10.1109/bibm.2017.8217879 dblp:conf/bibm/ZhangCCW17 fatcat:rtzgdrttyvcyrmjsbjt4qacgmm

Incorporating Machine Learning into Established Bioinformatics Frameworks

Noam Auslander, Ayal B. Gussow, Eugene V. Koonin
2021 International Journal of Molecular Sciences  
The exponential growth of biomedical data in recent years has urged the application of numerous machine learning techniques to address emerging problems in biology and clinical research.  ...  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  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/ijms22062903 pmid:33809353 pmcid:PMC8000113 fatcat:ssfoobbtcjhidbaffbkakqbwfe

MOGONET integrates multi-omics data using graph convolutional networks allowing patient classification and biomarker identification

Tongxin Wang, Wei Shao, Zhi Huang, Haixu Tang, Jie Zhang, Zhengming Ding, Kun Huang
2021 Nature Communications  
AbstractTo fully utilize the advances in omics technologies and achieve a more comprehensive understanding of human diseases, novel computational methods are required for integrative analysis of multiple  ...  types of omics data.  ...  Acknowledgements This work was supported by National Institutes of Health grants R01EB025018 (K.H., T.W.) and U54AG065181 (K.H., J.Z., W.S.); and Indiana University Precision Health Initiative (J.Z.).  ... 
doi:10.1038/s41467-021-23774-w pmid:34103512 fatcat:oqecgz3igra3jgzmxue7f6afiy

Identification of Biomarkers Associated with Cancer Using Integrated Bioinformatic Analysis [chapter]

Arpana Parihar, Shivani Malviya, Raju Khan
2021 Biomedical engineering  
This chapter deals with various types of biomarkers associated with different types of cancer and their identification using integrated bioinformatic analysis.  ...  Besides, a brief insight on integrated bioinformatics analysis tools and databases have also been discussed.  ...  Integrated bioinformatics analysis tools and databases Various integrated bioinformatics databases have been utilized for the identification of prognostic biomarkers in the treatment of various kinds of  ... 
doi:10.5772/intechopen.101432 fatcat:tui5ux4e55fahhragxzlrvhbla

Omics Biomarkers for Monitoring Tuberculosis Treatment: A Mini-Review of Recent Insights and Future Approaches

Pitaloka DAE, Syamsunarno MRAA, Abdulah R, Chaidir L
2022 Infection and Drug Resistance  
sensitivity of sputum conversion for monitoring tuberculosis (TB) treatment that makes identification of a non-sputum-based biomarker is urgently needed.  ...  We also discuss how integrative multi-omics data will provide further understanding and effective TB treatment, such as revealing the interrelationships at multiple molecular levels, facilitating the identification  ...  Diverse and heterogeneous forms of biomarkers are identified which require different types of clinical specimen and utilized diverse techniques and laboratory assays for identification.  ... 
doaj:25b2a36812f84df5ba809129e520d06b fatcat:ofvy6jgiinafnkb6nkmjnthfdi

–Omic and Electronic Health Record Big Data Analytics for Precision Medicine

2017 IEEE Transactions on Biomedical Engineering  
These voluminous complex data contain abundant information for precision medicine, and big data analytics can extract such knowledge to improve the quality of healthcare.  ...  Conclusion: Big data analytics is able to address -omic and EHR data challenges for paradigm shift toward precision medicine.  ...  Key types of biomedical big data for precision medicine. system.  ... 
doi:10.1109/tbme.2016.2573285 pmid:27740470 pmcid:PMC5859562 fatcat:4twn52g7ujfvhomx2mw5apmbcy

MORONET: Multi-omics Integration via Graph Convolutional Networks for Biomedical Data Classification [article]

Tongxin Wang, Wei Shao, Zhi Huang, Haixu Tang, Zhengming Ding, Kun Huang
2020 bioRxiv   pre-print
To fully utilize the advances in omics technologies and achieve a more comprehensive understanding of human diseases, novel computational methods are required for integrative analysis for multiple types  ...  We demonstrate that MORONET outperforms other state-of-the-art supervised multi-omics integrative analysis approaches from a wide range of biomedical classification applications using mRNA expression data  ...  Acknowledgements This work was supported by Indiana University Precision Health Initiative and National Institute of Biomedical Imaging and Bioengineering (R01EB025018).  ... 
doi:10.1101/2020.07.02.184705 fatcat:lemnficphncsxdkayxyruligbm

Bioinformatic-driven search for metabolic biomarkers in disease

Christian Baumgartner, Melanie Osl, Michael Netzer, Daniela Baumgartner
2011 Journal of Clinical Bioinformatics  
In particular, data mining tools suitable for the application to omic data gathered from most frequently-used type of experimental designs, such as case-control or longitudinal biomarker cohort studies  ...  The search and validation of novel disease biomarkers requires the complementary power of professional study planning and execution, modern profiling technologies and related bioinformatics tools for data  ...  Acknowledgements The authors gratefully acknowledge support from the Austrian Genome Research Program GEN-AU and its "Bioinformatics Integration Network (BIN III)" project.  ... 
doi:10.1186/2043-9113-1-2 pmid:21884622 pmcid:PMC3143899 fatcat:cji7s2zn3vbz5p5irjb45xykqu

A roadmap towards personalized immunology

Sylvie Delhalle, Sebastian F. N. Bode, Rudi Balling, Markus Ollert, Feng Q. He
2018 npj Systems Biology and Applications  
Here, we discuss the recent advances and successful applications in "Omics" data utilization and network analysis on patients' samples of clinical trials and studies, as well as the major challenges and  ...  We provide a roadmap and highlight experimental, clinical, computational analysis, data management, ethical and regulatory issues to accelerate the implementation of personalized immunology.  ...  of big biomedical data.  ... 
doi:10.1038/s41540-017-0045-9 pmid:29423275 pmcid:PMC5802799 fatcat:mrh4gptkrbemxf3ykewsa5b3j4

Reviewing the Role of Artificial Intelligence in Cancer

Shankargouda Patil, Ibtisam Hussain Moafa, Mona Mosa Alfaifi, Abrar Mohammed Abdu, Mohammed Abdurabu Jafer, Lizbeth Raju K, A. Thirumal Raj, Sadiq M. Sait
2020 Asian Pacific Journal of Cancer Biology  
The integration of Artificial intelligence into cancer research is being actively carried out and has provided very promising results.  ...  The present review aims as delving into literature and enlisting the applications of artificial intelligence in various commonly occurring cancers.  ...  Acknowledgements Authors' contributions All authors contributed equally Availability of data and material The reviews was based on published articles  ... 
doi:10.31557/apjcb.2020.5.4.189-199 fatcat:t7i4ownqhbduln4tjbqmcoz5xy

Editorial: Single cell intelligence and tissue engineering

Jiaofang Shao, Yangzi Jiang, Zhaoyuan Fang
2022 Frontiers in Bioengineering and Biotechnology  
The integration of existing bulk transcriptomic datasets is one of the issues that deserve attention and discussion in data mining.  ...  Li et al. trained several classifiers and obtained optimal models from in vitro cultured human hepatocyte single-cell RNA data, and identified biomarkers for distinct differentiated hepatic cell types.  ...  Author contributions All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.  ... 
doi:10.3389/fbioe.2022.1019929 pmid:36147525 pmcid:PMC9486296 fatcat:q7coawhpmrhrdlo7c3wnfwbovy

Dry computational approaches for wet medical problems

Frank Emmert-Streib, Shu-Dong Zhang, Peter Hamilton
2014 Journal of Translational Medicine  
The aim of the conference was to bring together leading experts from a variety of different areas that are key for Systems Medicine to exchange novel findings and promote interdisciplinary ideas and collaborations  ...  Finally, we thank all speakers and participants of the conference for their invaluable contribution.  ...  We are very grateful to Sinead Cassidy, Katie Stewart and Beryl Graham for the flawless administration of the conference.  ... 
doi:10.1186/1479-5876-12-26 pmid:24460894 pmcid:PMC3905162 fatcat:dhqp44jv3fdulnwtolgxamujh4

Disease proteomics

2008 Genomic Medicine  
This study indicates that quantitative proteomic profiling of tumor tissue versus non-cancerous tissue is a promising approach for the identification of potential biomarkers for HCC.  ...  The objective of our study was to identify altered protein expression or glycosylation for use as biomarkers in HCC.  ...  This investigation can lead to the development of potential biomarker that may have clinical utility in discovering biomarkers of breast cancer. 029: Development of Novel Biomarkers for Breast Cancer  ... 
doi:10.1007/s11568-009-9091-8 pmid:19444648 pmcid:PMC2694876 fatcat:fqidbx6kjzcvtmbhqhy5n7mozq

Challenges and opportunities for oncology biomarker discovery

Avisek Deyati, Erfan Younesi, Martin Hofmann-Apitius, Natalia Novac
2013 Drug Discovery Today  
based on combining data and knowledge as an integrative model.  ...  TeaserCrisis of pharmaceutical industry prompts Research and Development (R&D) focus from blockbusters to niche busters; its clinical success depends on successful prediction of stratification biomarkers  ...  entity recognition process of identification of biological entity names such as disease or gene names in running text Integrative modeling linking heterogenous data types across different levels of a  ... 
doi:10.1016/j.drudis.2012.12.011 pmid:23280501 fatcat:efrzfpjpxbaa5pon6i4jmq5vg4

Alzheimer's disease biomarker discovery using in silico literature mining and clinical validation

Ines Greco, Nicola Day, Joanna Riddoch-Contreras, Jane Reed, Hilkka Soininen, Iwona Kłoszewska, Magda Tsolaki, Bruno Vellas, Christian Spenger, Patrizia Mecocci, Lars-Olof Wahlund, Andrew Simmons (+2 others)
2012 Journal of Translational Medicine  
Substantial international efforts are being made to discover and validate biomarkers for AD using candidate analytes and various data-driven 'omics' approaches.  ...  Conclusions: These data support as a proof of concept the use of data mining and in silico analyses to derive valid biomarker candidates for AD and, by extension, for other disorders.  ...  Acknowledgements We are grateful for funding to the AddNeuroMed/InnoMed, (Innovative Medicines in Europe) an Integrated Project funded by the European Union of the Sixth Framework program priority FP6-  ... 
doi:10.1186/1479-5876-10-217 pmid:23113945 pmcid:PMC3508881 fatcat:zbkmkyfoffdd3b5oith57zrawm
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