A field guide to cultivating computational biology

Area of Science:

• Computational biology
• Bioinformatics
• Systems biology

Background:

• Computational biology has matured over 30 years, contributing to scientific knowledge and human health.
• Despite its impact, individual practitioners often face career development hurdles.
• There's a need to address the disparity between scientific progress and career progression in the field.

Purpose of the Study:

• To propose actionable solutions for advancing computational biology careers.
• To encourage broader adoption and integration of computational biology across institutions.
• To foster a more supportive environment for computational biologists.

Main Methods:

• The study outlines 10 steps for scientists, institutions, publishers, funding agencies, and educators.
• It advocates for a shift from traditional single-discipline research to multidisciplinary, data-driven team science.
• The approach emphasizes improving recognition and aligning career paths with scientific advancement.

Main Results:

• The proposed solutions aim to fully embrace computational biology.
• Implementing these steps is expected to improve career development for computational biologists.
• A move towards team science is highlighted as crucial for future breakthroughs.

Conclusions:

• Enhancing recognition and aligning career success with scientific progress are vital.
• Adopting multidisciplinary, data-driven team science is essential for the next generation of discoveries.
• Collective action from various stakeholders is needed to fully realize the potential of computational biology.