2024-07-12 –, Struct (1.4)
In the proposed panel for the Julia Conference, titled "Empowering Life Sciences with Julia," we aim to highlight the significant impact of the Julia programming language in advancing life sciences, encompassing fields like chemistry, physics, and biology. The panel will explore Julia's capabilities in handling complex computations, facilitating interdisciplinary research, and its application in data analysis, visualization, machine learning, and AI.
In this proposed panel for the Julia Conference, we delve into the transformative role of Julia in the life sciences - chemistry, physics, and biology. Renowned for its high performance and user-friendly syntax, Julia stands at the forefront of computational advances addressing fundamental questions in these fields. The panel aims to illuminate how Julia’s integration into research and education can catalyze breakthroughs in data analysis, visualization, and simulation, thus accelerating scientific discoveries and fostering interdisciplinary work.
Key discussion points include:
1. Julia’s Impact on Performance and Efficiency: Focusing on Julia’s adeptness in handling complex computations and large datasets, a critical requirement for life sciences research.
2. Interdisciplinary Research and Collaboration: Demonstrating Julia’s role in bridging chemistry, physics, and biology through its versatile nature and compatibility with other languages.
3. Innovations in Data Analysis and Visualization: Showcasing how Julia’s potent data processing capabilities can unlock new insights, particularly in managing large-scale biological data.
4. Machine Learning and AI in Life Sciences: Discussing the expanding role of Julia in applying AI and machine learning for predicting and modeling in biological and chemical domains.
5. Modeling and Simulation Strengths: Highlighting Julia’s capabilities in precise modeling and simulations, integral to life sciences.
6. Championing Reproducibility and Open Science: Promoting Julia’s open-source ethos to foster collaborative, transparent, and reproducible scientific research.
7. Development of Specialized Tools for Life Sciences: Exploring the potential of creating novel, Julia-based tools tailored for life science research.
8. Educational Outreach and Accessibility: Strategizing the integration of Julia into life sciences curricula to broaden access for diverse student and researcher groups.
A prime example of these efforts is the “Introduction.jl” package, developed specifically to disseminate Julia among chemists in the LatinX community. This package, created by the panelist, encompasses modules on reaction mechanisms, chemiometry, and quantum chemistry, demonstrating Julia’s practical applications in chemistry. It exemplifies how Julia can be tailored to address specific educational needs and research interests within the life sciences.
This panel seeks to unite experts and enthusiasts from various scientific areas to discuss Julia’s integration in life sciences. It will feature presentations, interactive discussions, and Q&A sessions, aiming to inspire, inform, and engage both the Julia community and life sciences professionals and students.
Systems biologist at DeepOrigin (https://www.deeporigin.com/) focussing on parameter estimation problems. Special interest in collaborative & scalable modeling.
Leticia Madureira is a PhD student in theoretical chemistry at Carnegie Mellon University. Her interests go from materials applications of molecular environments, focusing on studying conjugated systems and their quantum coherence, but also developing methods on the realm of electronic structure methods. She has been using Julia for 4 years and her goal is to answer fundamental scientific equations with high performance software engineering.
I’m a PhD candidate in systems biology for metabolic disease at the Department of Biomedical Engineering at Eindhoven University of Technology. I am working on model personalisation with scientific machine learning.