In recent years, there has been a surge in new high-throughput technologies enabling profiling of multi-omics data, namely genomics, epigenomics, transcriptomics, metabolomics, proteomics, and metagenomics. Parallelly, computational algorithms and tools have been developed to mine the plethora of data generated worldwide. Integration of these multi-omic profiles has taken center stage in biomedical research as it offers a holistic view of the system under consideration.
The field of systems biomedicine emerged with a special interest and focus on integrating multi-omics data to gain condition-specific systems-level understanding. Systems biomedicine holds the key for the translation of these insights from bench to bedside. Therefore, it is imperative to highlight the potential of computational approaches in answering a broad spectrum of biomedical questions in this special issue, thereby promoting this budding and promising field.
Thus, in this Research Topic, we invite original research, perspectives, reviews, and mini-review articles, focusing on computational approaches enabling systems biomedicine. The contents covered in this collection may include but are not limited to the following:
1. diagnostics of complex diseases that manifest in multiple organs systems
2. prediction of disease onset and/or progression
3. identification of novel disease endotypes to support precision medicine
4. determination of the influence of organ systems, such as gut-microbiome, in therapeutic interventions or in maintenance of pathology off-site
5. identification of novel therapeutic purposes of existing approved drugs
6. integrative “omics” approach to explore the system in a condition-specific manner
7. models for predictions and identification of markers in complex diseases.
8. unsupervised or supervised statistical learning, network-inference, or network-based methods, as well as novel use of existing algorithms that reveal novel biomedical insights
In recent years, there has been a surge in new high-throughput technologies enabling profiling of multi-omics data, namely genomics, epigenomics, transcriptomics, metabolomics, proteomics, and metagenomics. Parallelly, computational algorithms and tools have been developed to mine the plethora of data generated worldwide. Integration of these multi-omic profiles has taken center stage in biomedical research as it offers a holistic view of the system under consideration.
The field of systems biomedicine emerged with a special interest and focus on integrating multi-omics data to gain condition-specific systems-level understanding. Systems biomedicine holds the key for the translation of these insights from bench to bedside. Therefore, it is imperative to highlight the potential of computational approaches in answering a broad spectrum of biomedical questions in this special issue, thereby promoting this budding and promising field.
Thus, in this Research Topic, we invite original research, perspectives, reviews, and mini-review articles, focusing on computational approaches enabling systems biomedicine. The contents covered in this collection may include but are not limited to the following:
1. diagnostics of complex diseases that manifest in multiple organs systems
2. prediction of disease onset and/or progression
3. identification of novel disease endotypes to support precision medicine
4. determination of the influence of organ systems, such as gut-microbiome, in therapeutic interventions or in maintenance of pathology off-site
5. identification of novel therapeutic purposes of existing approved drugs
6. integrative “omics” approach to explore the system in a condition-specific manner
7. models for predictions and identification of markers in complex diseases.
8. unsupervised or supervised statistical learning, network-inference, or network-based methods, as well as novel use of existing algorithms that reveal novel biomedical insights
