Unlock the full potential of your research team by building bioinformatics capabilities, leveraging Unicle’s experienced team and UniApp biomedical data analysis platform.
The challenge
Research teams have ambitious goals to accelerate their discoveries and innovations. To achieve these goals, it’s essential for researchers to efficiently handle bioinformatics tasks. However, many teams rely heavily on bioinformaticians, even for routine analyses and minor edits. This slows down the process of scientific discoveries significantly. By empowering individual researchers with bioinformatics skills, teams can enhance their workflow, boost productivity and allow bioinformaticians to focus on more complex, high-impact questions.
Our solution
- Training and Workshops. We offer hands-on training sessions and workshops tailored to your team’s needs, ensuring that researchers gain the skills required to perform basic bioinformatics analyses independently.
- UniApp platform. Our user-friendly platform enables researchers to perform a wide range of bioinformatics analyses with ease. UniApp is designed to be intuitive, reducing the learning curve and allowing researchers to quickly adapt to performing their own analyses.
- Ongoing support. Our team provides continuous support and resources, ensuring that your researchers can confidently use the tools and techniques they’ve learned. We offer consultation services for more complex issues, ensuring that your bioinformaticians can focus on high-level questions.
Real-world example
An ambitious academic research lab aimed to accelerate their research by enhancing the bioinformatics skills of their team. Recognizing the potential to advance their projects more efficiently, they partnered with Unicle to implement a series of training workshops and adopt the UniApp biomedical data analysis platform.
Researchers quickly learned to handle basic bioinformatics tasks, such as differential expression analysis and pathway enrichment. This newfound capability allowed them to make immediate progress on their projects, driving innovation and discovery.
By reducing dependency on bioinformatics experts, the lab accelerated the dry-lab part of their papers by an estimated 5 months. This shift allowed researchers to focus more on gathering insights, rather than waiting for analyses or updates of visualizations to be performed by others or figuring out how to code themselves. Moreover, bioinformaticians in the team were able to concentrate on more complex analyses and strategic research questions, further advancing the lab’s scientific goals. This proactive approach not only accelerated the lab’s research timeline but also increased overall productivity and research output. The enhanced capabilities of the researchers contributed to the successful completion of several projects and subsequent grant applications.
Typical bioinformatic analyses
Typical analyses that researchers should be able to perform using UniApp, along with formatting outputs into publication-ready figures are
- Differential expression analysis
- Analyze gene expression differences between experimental conditions
- Generate volcano plots and heatmaps for visualization
- Format results into publication-quality figures with customizable colors and annotations
- Gene Set Enrichment Analysis (GSEA) / Pathway enrichment analysis
- Evaluate whether a predefined set of genes shows statistically significant differences between experimental conditions
- Identify biological pathways enriched with differentially expressed genes.
- Visualize pathway networks and enrichment scores
- Prepare pathway enrichment plots and diagrams suitable for publications
- Data visualization and interactive exploration
- Create interactive plots for exploring data distributions
- Filter and sort data dynamically based on various criteria
- Generate scatter plots, box plots, and bar charts with customizable axes and legends
- Export plots in vector formats (e.g., SVG) for high-resolution publication figures
- Clustering analysis
- Perform clustering of samples or cells based on expression profiles
- Visualize clustering results using PCA, t-SNE or UMAP plots
- Format clustering plots with clear annotations and color schemes
- Single-cell RNA-seq analysis
- Perform dimensionality reduction (e.g., UMAP, t-SNE) for single-cell data
- Cluster cells based on gene expression profiles
- Visualize cell clusters and marker genes
- Format single-cell analysis results into comprehensive figures for publication
- Spatial transcriptomics analysis
- Analyze spatial gene expression patterns within tissue sections
- Visualize gene expression maps and spatial distribution patterns
- Prepare spatial transcriptomics plots with annotated regions and gene expression levels
- Gene-Gene interaction networks
- Construct protein-protein interaction networks based on experimental data
- Visualize networks using network diagrams
- Format interaction network plots for publication
Empower your research team with Unicle’s bioinformatics capabilities building services. Transform your workflow, enhance productivity, and enable your researchers to independently unlock the potential of your biomedical data.
Related pages
Our client stories
Learn how our clients -both academic and industry- leverage our services to rapidly create insights out of their biomedical data and vest future-proof research skills in their teams
Data analysis
We assess your analysis quickly to uncover its strengths and weaknesses with the UniApp advanced analysis capabilities
Data visualizations
We leverage our UniApp platform to explore your data with interactive and easy customizable data output visualizations
Proud to accelerate biomedical research at our clients
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