System alterations across multiple levels are responsible for the initiation and progression of complex diseases, e.g. cancer, cardiovascular diseases, infections by drug-resistant bacteria, etc. These pathological processes occur at various omics levels. Therefore, multiple omics technologies are to be taken to analyze the biological systems across the genome, epigenome, transcriptome, translatome, proteome, and metabolome levels. Systematic or integrated analyses of multiple-omics data will more effectively reveal the mechanism of complex diseases.
The major obstacles of utilizing omics for deepened insights of complex diseases lay on:
1) The accuracy, robustness, and reproducibility are insufficient for the demands expected by research and clinical standards;
2) Research focused on specific gene or protein have provided precise knowledge in isolation, but not across all systems level. Inhibition of specific gene or protein may lead to the system compensation via other pathways, which counteract the outcome;
3) Heterogenicity of cells in complex diseases needs to be resolved deeper;
4) Some omics levels, the translatome and protein post-translational modifications, for example, are not well recognized and studied;
5) Current studies mainly focus on one omics level.
The integration of multiple omics levels is insufficient. Novel ideas and approaches of multi-omics integration on the pathogenesis and progression of complex diseases are lacking. This Research Topic welcomes Original Research, Review, and Method articles covering, but not limited to:
• Accurate and efficient tools processing large-scale omics and/or integrating multi-omics data;
• Integration of multiple-omics data, from tissue and/or single-cell levels, to reveal system alterations and mechanisms that drives the occurrence and progression of complex diseases.
Conflict of Interest statement: Topic editor Loh Yuin-Han Jonathan is the Founder and Director of Zhong Qiao Biotechnology Pte Ltd. All other Topic Editors declare no competing interests with regards to the Research Topic subject
System alterations across multiple levels are responsible for the initiation and progression of complex diseases, e.g. cancer, cardiovascular diseases, infections by drug-resistant bacteria, etc. These pathological processes occur at various omics levels. Therefore, multiple omics technologies are to be taken to analyze the biological systems across the genome, epigenome, transcriptome, translatome, proteome, and metabolome levels. Systematic or integrated analyses of multiple-omics data will more effectively reveal the mechanism of complex diseases.
The major obstacles of utilizing omics for deepened insights of complex diseases lay on:
1) The accuracy, robustness, and reproducibility are insufficient for the demands expected by research and clinical standards;
2) Research focused on specific gene or protein have provided precise knowledge in isolation, but not across all systems level. Inhibition of specific gene or protein may lead to the system compensation via other pathways, which counteract the outcome;
3) Heterogenicity of cells in complex diseases needs to be resolved deeper;
4) Some omics levels, the translatome and protein post-translational modifications, for example, are not well recognized and studied;
5) Current studies mainly focus on one omics level.
The integration of multiple omics levels is insufficient. Novel ideas and approaches of multi-omics integration on the pathogenesis and progression of complex diseases are lacking. This Research Topic welcomes Original Research, Review, and Method articles covering, but not limited to:
• Accurate and efficient tools processing large-scale omics and/or integrating multi-omics data;
• Integration of multiple-omics data, from tissue and/or single-cell levels, to reveal system alterations and mechanisms that drives the occurrence and progression of complex diseases.
Conflict of Interest statement: Topic editor Loh Yuin-Han Jonathan is the Founder and Director of Zhong Qiao Biotechnology Pte Ltd. All other Topic Editors declare no competing interests with regards to the Research Topic subject
