Who we are
Insilicode is an ambitious bioinformatics and computational biology company with over 15 years of experience in the field. Our PhD scientists employ the most advanced methods and standards to develop sophisticated solutions that enable scientists to make informed decisions.
We deeply understand the latest bioinformatics methods and standards and are committed to providing our customers with the best achievable solutions.
We possess a comprehensive understanding of biology (biochemistry, immunology, evolutionary biology, cell biology, etc) as well as computer science, enabling us to offer our clients a diverse range of services, including data analysis, experimental design, and result interpretation.
We are a UK-based company, but we work globally and adjust our working hours to accommodate our clients. This means that we are available to work with clients in different time zones and can provide support around the clock. We are committed to providing our clients with the best possible service, and we believe that this flexible approach is essential for meeting their needs.
Quality, not quantity
When data is analysed poorly, it can lead to inaccurate or misleading conclusions. This can have severe consequences for science, as it can, for example, lead to the development of faulty theories and the implementation of ineffective policies.
Good analysis requires a deep understanding of the data, identifying and addressing potential biases, and using appropriate methods.
We use multiple methods to ensure the robustness of our analysis. This means that we use various techniques to analyse the data and compare the results to ensure they are consistent. We also use statistical methods to assess the uncertainty of our results. Our multi-method approach is essential for ensuring the accuracy and reliability of our results. By using multiple techniques, we can identify and correct any errors or biases that may be present in the data. We can also assess the uncertainty of our results, allowing us to make more informed decisions about interpreting our findings.
In addition to our rigorous analytical approach, we also provide comprehensive reports written in Quarto (a successor of R Markdown). This enables us to share our results and make them easily reproducible. Our reports can be generated in various formats, including PDF, HTML, DOCX, and ODT.
This makes us unique.
Our goals
- To provide robust, correct, and comprehensive results that are understandable for everyone interested, regardless of the client’s budget.
- To provide researchers with the tools and knowledge to design better experiments, collect high-quality data, and analyse their results effectively.
- To ensure experiment reproducibility, correctness and compliance with all best practices.
- We are committed to continuous improvement, serving researchers and the world better.
Our core values
Accessibility
Everyone should have the tools and knowledge they need to conduct meaningful research, regardless of their background or financial resources.
Accuracy
The results of bioinformatics analyses must be accurate to be helpful to researchers. This means using the correct methods and tools, and ensuring that the data is appropriately processed and analysed.
Quality
We are committed to providing our customers with high-quality products and services that meet their needs and align with the highest standards.
Innovation
We continually seek new ways to enhance our products and services, making them more accessible to researchers.
Transparency
Researchers should be able to understand how the analyses were conducted and how the results were produced. This means being transparent about the methods used, the data analysed, and the assumptions made.
Excellence
We strive for excellence in everything we do, from the quality of our analyses to how we interact with our clients. We continually seek ways to enhance our services and deliver the best possible outcomes for our clients.
Reproducibility
The results of bioinformatics and computational biology analyses should be reproducible by other researchers. This means that the same results should be obtained if the same methods are used on the same data.
Collaboration
The analysis results should be interpretable and usable to answer biological questions.
Ethics
Bioinformatics and computational biology analyses often involve the use of sensitive data, such as patient medical records. It is essential to use this data ethically and responsibly.
