Genomics and Bioinformatics Lab

Gene Network, Single-Cell, and Long-Read Transcriptomics
Gene Network and Pathway Analysis:

Gene Co-expression Networks: Identifies relationships between genes based on their expression patterns, helping to uncover gene modules involved in biological processes.

Spatiotemporal Expression Patterns: Analyzes gene behavior across time and space to understand regulation during development, disease, and environmental response.

Functional Annotation & Enrichment Analysis: Assigns biological functions to genes and identifies enriched pathways to understand gene roles in processes like metabolism and immune response.

Single-Cell Transcriptomics:

Gene Expression at Single-Cell Level: Single-cell RNA sequencing (scRNA-seq) analyzes gene expression in individual cells, revealing cellular diversity previously undetectable in bulk RNA-seq.

Cellular Heterogeneity and Cell Type Identification: Uncovers distinct cell types and subtypes within a tissue, providing insights into development, disease, and immune responses.

Long-Read Transcriptomics:

Long-Read Sequencing Data: Technologies like PacBio and Oxford Nanopore allow the sequencing of full-length transcripts, addressing limitations of short-read sequencing.

Full-Length Transcripts & Complex Gene Structures: Enables the study of complex gene structures, alternative splicing, and novel isoforms that are crucial for understanding gene regulation in diseases like cancer.
For more detail visit : https://www.genomatics.net/services