Bioinformatics is a multidisciplinary field that combines biology and computer science to manage, analyze, distribute, and store biological data, including large-scale data generated from systems biology analyses such as metabolomics and proteomics. It initially emerged to address the need for managing substantial amounts of data produced by DNA, RNA, and peptide sequencing. With the development of additional systems biology platforms, including proteomics and metabolomics, bioinformatics has expanded and become more sophisticated and essential than ever.

At Nelson Scientific Labs, our team consists of consultants with decades of experience in utilizing bioinformatic tools, synthesizing data, and implementing a broad range of techniques and strategies to analyze extensive datasets. Navigating omics data can feel like searching for a needle in a haystack. However, our team can significantly optimize your time and effort by streamlining your data analysis process with the tools we offer. Additionally, we can assist you in interpreting and communicating your findings, as well as discussing logical next steps for your long-term research.

One notable achievement in our repertoire is the successful development of ShinyLink, a web application built on R Shiny that simplifies data de-duplication and record linkage processes. ShinyLink provides a user-friendly graphical interface, guiding users through an intuitive workflow that allows for seamless data management and analysis. The application is designed to handle large datasets while maintaining the flexibility and adaptability necessary for diverse research fields.

Our Bioinformatics Services

1. Sequence analysis: We offer tools for DNA, RNA, and peptide sequence alignment, annotation, and comparison, as well as functional and structural prediction.
2. Genomic and transcriptomic data analysis: We provide support for analyzing genomic and transcriptomic data, including differential gene expression, alternative splicing, and gene fusion identification.
3. Proteomic and metabolomic data analysis: We can help you analyze proteomic and metabolomic data, including protein-protein interactions, metabolic pathway reconstruction, and biomarker identification.
4. Comparative genomics: We offer assistance in comparative genomics, including multiple sequence alignment, phylogenetic analysis, and genome synteny studies.
5. Machine learning and statistical modeling: Our team can assist in developing machine learning and statistical models to analyze and predict biological phenomena based on large-scale data.
6. Data visualization: We can help you create interactive and informative visualizations of your data, enabling you to better understand and communicate your results.
7. Data integration and network analysis: We can guide you in integrating various types of biological data and conducting network analysis to reveal complex relationships between genes, proteins, and metabolites.
8. Custom software and pipeline development: Our team can develop custom software and pipelines tailored to your specific research needs, ensuring efficient and accurate data analysis.