Integrative omics for health and disease.
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TLDR
The potential for combining diverse types of data and the utility of this approach in human health and disease is discussed and examples of data integration to understand, diagnose and inform treatment of diseases, including rare and common diseases as well as cancer and transplant biology.Abstract:
Advances in omics technologies - such as genomics, transcriptomics, proteomics and metabolomics - have begun to enable personalized medicine at an extraordinarily detailed molecular level. Individually, these technologies have contributed medical advances that have begun to enter clinical practice. However, each technology individually cannot capture the entire biological complexity of most human diseases. Integration of multiple technologies has emerged as an approach to provide a more comprehensive view of biology and disease. In this Review, we discuss the potential for combining diverse types of data and the utility of this approach in human health and disease. We provide examples of data integration to understand, diagnose and inform treatment of diseases, including rare and common diseases as well as cancer and transplant biology. Finally, we discuss technical and other challenges to clinical implementation of integrative omics.read more
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Integrative analysis of 111 reference human epigenomes
Anshul Kundaje,Wouter Meuleman,Jason Ernst,Angela Yen,Pouya Kheradpour,Zhizhuo Zhang,Jianrong Wang,Lucas D. Ward,Abhishek Sarkar,Gerald Quon,Matthew L. Eaton,Yi-Chieh Wu,Andreas R. Pfenning,Xinchen Wang,Melina Claussnitzer,Yaping Liu,Mukul S. Bansal,Soheil Feizi-Khankandi,Ah Ram Kim,Richard C Sallari,Nicholas A Sinnott-Armstrong,Laurie A. Boyer,Elizabeta Gjoneska,Li-Huei Tsai,Manolis Kellis +24 more
TL;DR: In this article, the authors describe the integrative analysis of 111 reference human epigenomes generated as part of the NIH Roadmap Epigenomics Consortium, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression.
Journal ArticleDOI
The growing role of precision and personalized medicine for cancer treatment
Paulina Krzyszczyk,Alison Acevedo,Erika J Davidoff,Lauren M Timmins,Ileana Marrero-Berrios,Misaal Patel,Corina White,Christopher J. Lowe,Joseph J. Sherba,Clara Hartmanshenn,Kate O'Neill,Max L. Balter,Zachary Fritz,Ioannis P. Androulakis,Rene S. Schloss,Martin L. Yarmush +15 more
TL;DR: It is clear that PPM cancer treatments can result in immense patient benefits, and companies and regulatory agencies have begun to recognize this, but broader changes to the healthcare and insurance systems must be addressed if PPM is to become part of standard cancer care.
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Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine
TL;DR: This study focused on analyzing and discussing various published artificial intelligence and machine learning solutions, approaches and perspectives, aiming to advance academic solutions in paving the way for a new data-centric era of discovery in healthcare.
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Machine Learning for Integrating Data in Biology and Medicine: Principles, Practice, and Opportunities.
Marinka Zitnik,Francis Nguyen,Francis Nguyen,Bo Wang,Jure Leskovec,Anna Goldenberg,Michael M. Hoffman +6 more
TL;DR: In this paper, the authors describe the principles of data integration and discuss current methods and available implementations, as well as current challenges in biomedical integrative methods and their perspective on the future development of the field.
Tissue-specific regulatory circuits reveal variable modular perturbations across complex diseases
TL;DR: In this article, the authors developed a comprehensive resource of 394 cell type and tissue-specific gene regulatory networks for human, each specifying the genome-wide connectivity among transcription factors, enhancers, promoters and genes.
References
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TL;DR: The aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC) provides direct evidence for the presence of widespread mutational recurrence.
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