Bioinformatics

Effective experimental design is crucial for maximizing the potential of your bioinformatics research. 

We provide meticulous planning to ensure your experiments are structured to yield the most significant results. From grant proposals to power calculations, our expert guidance helps you optimise your experimental setup. 

We focus on understanding your research goals and aligning our strategies to achieve them, ensuring that every step of your sequencing experiments is thoughtfully planned and executed.

The field of DNA sequencing offers unparalleled opportunities to explore genetic data. 

Our team harnesses the latest advancements in bioinformatics to provide high-resolution genetic snapshots of organisms. By exploiting both new and existing genetic data, we uncover novel insights that drive your research forward. 

Our services in DNA sequencing include: 

• 16s Ribosomal Sequencing: Identify and classify microorganisms with precision.
• Polymorphism Detection: Discover genetic variations that impact traits and diseases.
• Genome Assembly: Construct complete genome sequences from fragmented data.
• Genome Annotation: Assign functional information to genomic elements.
• BLAST Analysis: Compare your sequences against a comprehensive database.
• Transposon Element Analysis: Investigate mobile genetic elements within genomes.
• Source Analysis of Metagenome Findings: Determine the origins and functions of metagenomic data.

RNA sequencing (RNAseq) is a powerful tool for understanding gene expression and regulation. 

Our team has conducted hundreds of RNAseq analyses across various applications, helping researchers reveal how samples dynamically respond to treatments. 

Our RNA sequencing services include: 

At InSilico Consulting, we specialise in advanced data visualisation techniques to make your data comprehensible and actionable. Whether you have specific graphical strategies in mind or are open to exploring new methods, we provide solutions tailored to your needs. 

Our visualisation services include: 

• GNUPlot: Create high-quality plots and graphs.
• RStudio: Utilise advanced statistical tools for data analysis.
• Gene Ontology: Visualise functional categories of genes.
• Gene Set Enrichment Analysis: Identify significantly enriched gene sets.
• Clustering Analysis: Group similar data points to identify patterns.
• Pathway Analysis: Map interactions and pathways within your data.