Omic techniques have become key tools in the development of systems biology. As the holistic approaches underlying the practice of traditional Chinese medicine (TCM) and new tendencies in Western medicine towards personalised medicine require in-depth knowledge of mechanisms of action and active compounds, the use of omic techniques is crucial for understanding and interpretation of TCM development, especially in view of its expansion in Western countries. In this short review, omic applications in TCM research are reviewed which has allowed some speculation regarding future perspectives for these approaches in TCM modernisation and standardisation. Guidelines for good practice for the application of omics in TCM research are also proposed.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.jep.2012.01.055 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Systems-level liquid biopsy in advanced prostate cancer.
Endocr Relat Cancer
January 2025
S Dehm, Masonic Cancer Center, University of Minnesota, Minneapolis, United States.
Treatment for castration-resistant prostate cancer (CRPC) primarily involves the suppression of androgen receptor (AR) activity using androgen receptor signaling inhibitors (ARSIs). While ARSIs have extended patient survival, resistance inevitably develops. Mechanisms of resistance include genomic aberrations at the AR locus that reactivate AR signaling, or lineage plasticity that drives emergence of AR-independent phenotypes.
View Article and Find Full Text PDFBackground: There is currently an unmet need for novel accessible biomarkers that capture the complex and heterogenous pathophysiology of Alzheimer's disease (AD). Over the past decade, the systems-based multi-omic approaches employed by the Accelerating Medicines Partnership in AD (AMP-AD) have resulted in the identification of promising peripheral markers of disease heterogeneity. This scientific review will highlight these advances with a particular focus on the consortium's successes in peripheral protein biomarker discovery in cerebrospinal fluid (CSF) and plasma.
View Article and Find Full Text PDFBasic Science and Pathogenesis.
Alzheimers Dement
December 2024
Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Background: The FunGen-xQTL project has significantly advanced genetics by developing and exploring novel quantitative trait loci (QTL) types in human brains, enriching our understanding of complex neurological disease etiology. We broadened the scope of epigenomic QTL analysis, integrating histone acetylation QTLs (haQTLs) and methylation QTLs (mQTLs) that affect multiple histone acetylation peaks or methylation CpG sites spatially. Additionally, we investigated a new category of splicing QTLs (sQTLs) implicated in nonsense-mediated decay (NMD).
View Article and Find Full Text PDFBasic Science and Pathogenesis.
Alzheimers Dement
December 2024
Stanford University, Palo Alto, CA, USA.
Background: Genome-wide association studies (GWAS) have identified thousands of genomic regions associated with complex diseases but understanding the underlying causal mechanisms remains a significant challenge. The FunGen-xQTL project has addressed this by generating and harmonizing molecular quantitative trait loci (xQTL) across multiple layers of molecular traits in human brains, cerebrospinal fluid, and blood-derived cells relevant to neurodegenerative disorders. Existing approaches for integrating xQTL data with GWAS have typically focused on individual molecular traits in individual QTL layers.
View Article and Find Full Text PDFMulti-omic biomarker panel in pancreatic cyst fluid and serum predicts patients at a high risk of pancreatic cancer development.
Sci Rep
January 2025
Department of Surgery, Trinity St. James's Cancer Institute, Trinity Translational Medicine Institute, Trinity College Dublin, St. James's Hospital, Dublin 8, Ireland.
Integration of multi-omic data for the purposes of biomarker discovery can provide novel and robust panels across multiple biological compartments. Appropriate analytical methods are key to ensuring accurate and meaningful outputs in the multi-omic setting. Here, we extensively profile the proteome and transcriptome of patient pancreatic cyst fluid (PCF) (n = 32) and serum (n = 68), before integrating matched omic and biofluid data, to identify biomarkers of pancreatic cancer risk.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!