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A convex optimization approach for identification of human tissue-specific interactomes
Shahin Mohammadi1, Ananth Grama1
1Department of Computer Sciences, Purdue University, West Lafayette, IN 47907, USA.
Motivation:
Analysis of organism-specific interactomes has yielded novel insights into cellular function and coordination, understanding of pathology, and identification of markers and drug targets. Genes, however, can exhibit varying levels of cell type specificity in their expression, and their coordinated expression manifests in tissue-specific function and pathology. Tissue-specific/tissue-selective interaction mechanisms have significant applications in drug discovery, as they are more likely to reveal drug targets. Furthermore, tissue-specific transcription factors (tsTFs) are significantly implicated in human disease, including cancers. Finally, disease genes and protein complexes have the tendency to be differentially expressed in tissues in which defects cause pathology. These observations motivate the construction of refined tissue-specific interactomes from organism-specific interactomes.
Results:
We present a novel technique for constructing human tissue-specific interactomes. Using a variety of validation tests (Edge Set Enrichment Analysis, Gene Ontology Enrichment, Disease-Gene Subnetwork Compactness), we show that our proposed approach significantly outperforms state-of-the-art techniques. Finally, using case studies of Alzheimer's and Parkinson's diseases, we show that tissue-specific interactomes derived from our study can be used to construct pathways implicated in pathology and demonstrate the use of these pathways in identifying novel targets.
Availability And Implementation:
http://www.cs.purdue.edu/homes/mohammas/projects/ActPro.html
Contact:
mohammadi@purdue.edu.
Insights
We developed a new method to create tissue-specific interactomes, improving the identification of disease pathways and potential drug targets. This approach enhances understanding of cellular function and disease mechanisms.
Area of Science:
- Bioinformatics
- Systems Biology
- Genomics
Background:
- Organism-specific interactomes offer insights into cellular functions and disease mechanisms.
- Gene expression varies by cell type, influencing tissue-specific functions and pathologies.
- Tissue-specific interactions are crucial for identifying drug targets and understanding disease-related transcription factors.
Purpose of the Study:
- To develop a novel technique for constructing human tissue-specific interactomes.
- To validate the proposed method against state-of-the-art techniques.
- To demonstrate the application of tissue-specific interactomes in identifying disease pathways and drug targets.
Main Methods:
- Construction of human tissue-specific interactomes.
- Validation using Edge Set Enrichment Analysis, Gene Ontology Enrichment, and Disease-Gene Subnetwork Compactness.
- Case studies on Alzheimer's and Parkinson's diseases.
Main Results:
- The novel technique significantly outperforms existing methods.
- Tissue-specific interactomes were successfully constructed.
- Derived interactomes facilitated the construction of pathology-implicated pathways and identification of novel targets.
Conclusions:
- The developed method provides a powerful tool for generating refined tissue-specific interactomes.
- Tissue-specific interactomes are valuable for understanding disease mechanisms and discovering therapeutic targets.
- This approach has significant implications for drug discovery and personalized medicine.
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