Bioinformatics & Computational Biology
What We Do:
WCTS handles technical and project management tasks needed to develop and optimize computational methods for data and database exploitation. Using a variety of methods, software, and programming languages, our team possesses the capability to manage, process, and analyze genomic and molecular data.
Our computational exploitation provides critical information for federal and state agencies to bolster their operations. These scientific and technical practices are used to support the Department of Defense for technical exploitation.
How We Do It:
We perform several bioinformatic analyses with a variety of computational tools and pipelines to yield high impact results.
- Develop pipelines, packages, tools, and Docker containers for data analysis.
- Implementation of computational tools and methods to interpret biological meaning from data.
- Analyze genomic data using available programs or by developing new ones to fulfill the requirements.
- Create/maintain databases of biological information.
- Perform extensive literature review to obtain needed background information regarding product output.
![Face with DNA concept](https://ww-cts.com/wp-content/uploads/2023/06/Screenshot-2023-06-18-211934.png)
Computational Proficiency:
We routinely utilize state-of-the-art computational methods to analyze and interpret a multitude of data types; including but not limited to next generation sequencing, microarray, flow cytometry, microscopy, and other publicly available data. We exploit open-source data found within NCBI, Ensembl, UniProt, and PDB. We have experience in programing languages and software such as R/RStudio, Python, UNIX/Linux, Docker and CLC Genomics Workbench. Our R/RStudio capabilities include R Shiny app development, R package development, and commonly used packages such as plotly, ggplot2, and tidyverse.
Who we have supported:
- Intelligence Community
Capabilities
- Database engineering and management
- Data visualization and statistical analysis
- Biological data science
- Genetics
- Genomics
- Epigenomics
- Transcriptomics
- Proteomics
- NextGen sequencing
- Single cell ‘omics
- Biological image analysis
- High-throughput screening data analysis
- High performance computing environments
- High security computing environments
- Clinical and research data management
- Grant and regulatory affair submissions
Languages/Software
- R/RStudio
- Python
- UNIX/Linux
- Docker, Singularity
- Git
- Microsoft Office Suites
- GraphPad Prism
- CLC Genomics Workbench
- Adobe Suite