Transcriptomics & Gene Expression
Unlocking the Language of Genes.
RNA-Seq Analysis
Comprehensive analysis of RNA sequencing data to quantify gene expression, identify differentially expressed genes, and discover novel transcripts.
Single-Cell RNA-Seq
High-resolution analysis of gene expression at the single-cell level to study cellular heterogeneity, differentiation trajectories, and rare cell populations.
Long-Read Transcriptomics
Utilize long-read sequencing technologies (e.g., PacBio, Oxford Nanopore) for full-length transcript sequencing, enabling the discovery of novel isoforms and complex splicing events.
Small RNA and miRNA Analysis
Identify and quantify small RNAs and microRNAs to understand their role in gene regulation and disease.
Alternative Splicing Analysis
Detect and analyze alternative splicing events to uncover their impact on gene function and disease mechanisms.
Gene Co-Expression Network Analysis
Construct and analyze gene co-expression networks to identify functional modules and key regulatory genes.
Spatial Transcriptomics
Integrate spatial information with gene expression data to study tissue architecture and cellular interactions in situ.
Time-Series Transcriptomics
Analyze time-series gene expression data to study dynamic biological processes and temporal regulation of genes.
Transcriptome Assembly and Annotation
De novo assembly and annotation of transcriptomes for non-model organisms, enabling comprehensive gene expression studies.
Differential Gene Expression Analysis
Identify differentially expressed genes across conditions, treatments, or disease states using advanced statistical methods.
Functional Enrichment Analysis
Perform gene set enrichment analysis to uncover biological pathways, processes, and functions associated with gene expression changes.
Integration with Other Omics Data
Combine transcriptomics data with genomics, proteomics, and metabolomics data for a systems-level understanding of biological processes.
Custom Transcriptomics Pipelines
Develop tailored bioinformatics pipelines for the analysis and interpretation of transcriptomics data, addressing specific research questions.
Real-Time Gene Expression Analysis
Provide real-time analysis of gene expression data, enabling rapid insights and decision-making for time-sensitive research.
Interactive Data Visualization
Offer advanced visualization tools to explore and interpret transcriptomics data through interactive and customizable visualizations.
Genoma Bioinformatics 