Dereck’s Projects Consulting
Software | Bioinformatics | Data Science
Welcome
I began programming at age 15 and have since developed professional expertise in software and data engineering. My formal education includes an MSc of Bioinformatics in Systems & Synthetic Biology. This combination of long-term programming experience and scientific training enables effective work at the intersection of life sciences and advanced computing.
As an American raised in France, I possess native fluency in English, French, and Spanish, with additional fluency in Italian and Russian. This linguistic capability facilitates work in international scientific contexts. My professional focus includes high-performance computing, data infrastructure development, and scientific software creation. I specialize in transforming complex scientific and financial problems into data-driven solutions.
Showcase
Dereck’s Notes
Dereck’s Notes1 began in 2017 as a personal project, an attempt to integrate and condense everything I had learned in university. I have always been a prolific note taker, and I wanted to create a platform to share my knowledge with others. The project has since evolved into a knowledge distribution platform, scientific dictionary, scientific journal, and blog.
Early versions were in PHP, version 4.0 of the project demonstrates a dern technical stack to integrate advanced features and improve maintainability. I strongly focused one a polished frontend and backend, as well as strong DevOps + CI/CD.
Key technical aspects:
- Frontend: Next.js 14 (app dir), React, TypeScript, MDX
- Backend: Express, Mongoose, Redis
- Infrastructure: Nginx, Linode, MongoDB, Redis
- CI/CD: GitHub Actions, Docker
Notable features:
- User account functionality
- Interactive commenting system
- Blog post filtering
- Dictionary search functionality
dmplot
My interest in algorithmic trading and financial data analysis originated during my Master’s degree. This academic pursuit led to a personal project: developing an algorithmic trading bot. From this, the dmplot
2 3 package emerged as a comprehensive R framework for financial and time series data analysis.
The dmplot
package addresses the need for efficient processing and analysis of large financial datasets. It achieves this by combining high-performance C++ implementations with ggplot2
for data visualisation. Key features include:
- High-performance C++ implementations of financial indicators (e.g., Bollinger Bands, EMA, MACD)
- Custom
ggplot2
stats for financial data visualisation (e.g., candlesticks, Bollinger Bands) - Monte Carlo simulation implemented in high-performance C++
Developing dmplot
significantly enhanced my skills in financial data analysis and visualisation, R package development, and C++ integration.
Research and Publications
My scientific research focuses on applying bioinformatics, statistics, and high-performance computing to address complex scientific problems. Key areas of study include rheumatoid arthritis, breast cancer, and broader investigations in genomics, metabolomics, and proteomics.
Notable publication:
- Metabolomic Rewiring Promotes Endocrine Therapy Resistance in Breast Cancer (Cancer Research, 2024)
- Inference of an integrative, executable network for rheumatoid arthritis combining data-driven machine learning approaches and a state-of-the-art mechanistic disease map (Journal of Personalized Medicine, 2021)
These publications exemplify my approach to leveraging computational methods for advancing understanding in life sciences. For a comprehensive list of my research contributions, please refer to my Google Scholar profile.