Functional Annotation and Pathway Analysis Service for Obesity Risk Prediction
InquiryOverview of Functional Annotation and Pathway Analysis
At Protheragen, our functional annotation and pathway analysis service for obesity risk prediction uses cutting-edge multi-omics technologies to explore the complex biological functions and pathways associated with obesity. Multi-omics approaches involve integrating data from several molecular layers, including genomics, transcriptomics, proteomics, metabolomics, and epigenomics, to provide a comprehensive understanding of the factors contributing to obesity. By examining the interplay between genes, proteins, metabolites, and epigenetic modifications, this technology enables the identification of key molecular drivers of obesity and related metabolic disorders.
Epigenomics
Unlock the Pathways to Better Health - Predict and Manage Obesity Risk with Precision
Functional annotation refers to the process of assigning biological meaning to genes, proteins, and metabolites by linking them to known cellular processes, pathways, or disease states. In the context of obesity, functional annotation helps in identifying specific genes or proteins that play a critical role in fat accumulation, energy metabolism, or insulin resistance. Pathway analysis, on the other hand, involves mapping the functional elements identified through annotation into biological pathways to understand how these elements interact in networks. By leveraging advanced bioinformatics tools, researchers gain insights into how different genes and proteins regulate metabolic processes like lipid metabolism, inflammation, and insulin signaling, all of which are closely associated with obesity.
Fig.1 Circos plot demonstrating the genes associated with type-1 diabetes (T1D), type-2 diabetes (T2D), and maturity-onset diabetes of the young (MODY). (Rajan, et al., 2020)
Workflow
Our service begins with the collection of multi-omics data from biological samples of individuals who are at risk of obesity or are experiencing metabolic abnormalities. Once the data is gathered, bioinformatics tools are used for functional annotation and pathway analysis. Key genes, proteins, and metabolites are mapped to biological pathways, revealing the critical molecular mechanisms driving obesity.
Data Generation
Using technologies such as RNA sequencing, proteomics (liquid chromatography-mass spectrometry), metabolomics (gas chromatography-mass spectrometry), and other omics methods, data is collected and processed from biological samples.
Functional Annotation
Bioinformatics tools are used to annotate genes, proteins, and metabolites to understand their roles in specific biological functions related to obesity. Databases such as GO, KEGG, and Reactome are employed to classify the data.
Pathway Enrichment Analysis
Pathways associated with obesity, such as insulin signaling, lipid metabolism, and inflammation, are identified. This involves examining overrepresented pathways to understand how certain genes or metabolites influence obesity risk.
Protein-protein Interaction (PPI) Networks
The service constructs PPI networks to explore how obesity-related proteins interact within cellular systems. This aids in identifying key regulatory hubs or druggable targets.
Applications
- Our service can be used to identify the molecular mechanisms and metabolic pathways contributing to obesity, enabling more accurate predictions of an individual's risk of developing obesity and related metabolic conditions.
- Our service can be used to help discover druggable targets by identifying proteins or genes involved in key obesity-related pathways, leading to the development of targeted therapies for obesity and its complications.
- Our service can be used to assist healthcare providers in designing customized treatment and prevention strategies based on an individual's unique metabolic and genetic profile, including dietary recommendations and lifestyle changes.
- Our service can be used to enable researchers to explore the pathways linking obesity with other diseases, such as diabetes, cancer, and cardiovascular conditions, offering insights into comorbidities and the broader health impacts of obesity.
Advantages
- By integrating data from genomics, transcriptomics, proteomics, metabolomics, and epigenomics, the service provides a full picture of the biological processes that drive obesity, uncovering critical molecular pathways.
- Through functional annotation and pathway analysis, our service identifies key proteins and genes that are targeted in therapeutic development, paving the way for personalized treatment options.
- By analyzing biological pathways associated with metabolic dysregulation, the service allows for early detection of obesity-related risks, enabling preventive measures before the condition worsens.
- Our service is valuable not only for individual health management but also for research in obesity-related diseases, contributing to scientific discovery.
Functional Annotation and Pathway Analysis Service Used for Therapy Development
Pathway analysis enhances therapy development by identifying critical functional pathways and targets.
Functional Annotation and Pathway Analysis Service Used for Preclinical Studies
Functional annotation and pathway analysis are essential in preclinical stages to ensure relevant model development and assessment metrics.
Publication Data
Technology: Gene compilation, PPI network, Cytoscape and MCODE, Circos plot, Venn diagram
Journal: Genes
IF: 2.8
Published: 2020
Results: This study explores the genetic links between obesity and diabetes, particularly focusing on the molecular pathways associated with diabesity, a condition where diabetes occurs in the context of obesity. The research identified 546 genes that are associated with T1D, T2D, and MODY, and analyzed their interactions using protein-protein interaction networks. Key pathways involved in diabesity include FOXO-mediated transcription, insulin signaling, and lipolysis regulation. The findings suggest that understanding these molecular mechanisms can aid in discovering potential therapeutic targets for diabesity.
Fig.2 The top three clusters derived from the PPI network using MCODE. (Rajan, et al., 2020)
Frequently Asked Questions
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What is functional annotation and pathway analysis for obesity risk prediction?
It is a service that analyzes genes, proteins, and metabolites involved in obesity to understand how biological functions and pathways contribute to obesity risk, enabling more precise predictions and interventions.
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How are biological samples collected for analysis?
Blood, tissue, or other biological samples are collected from individuals, which are then processed using advanced multi-omics technologies to generate data for analysis.
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How accurate is the obesity risk prediction?
This service uses state-of-the-art bioinformatics and statistical tools, ensuring highly accurate predictions based on integrated multi-omics data. Personalized risk profiles are developed with precision.
At Protheragen, our functional annotation and pathway analysis service for obesity risk prediction provides an innovative solution for individuals and healthcare providers aiming to uncover the molecular mechanisms behind obesity. To learn more about how this service can benefit you, please don't hesitate to contact us and discover further details!
Reference
- Rajan, B.; et al. Involvement of essential signaling cascades and analysis of gene networks in diabesity. Genes. 2020, 11(11): 1256. (CC BY 4.0)
All of our services and products are intended for preclinical research use only and cannot be used to diagnose, treat or manage patients.