The Rising Influence of Machine Learning and Coding in Biotechnology (a Survey)
The landscape of biotechnology is rapidly evolving, with coding and machine learning becoming integral to the innovative processes. A recent industry survey by Cradle, a platform that empowers scientists to design and program proteins, and Bits in Bio, a global community dedicated to creating software for science, reveals a detailed picture of current trends within the synthetic biology sector.
Coding: An Essential Skill for Biotechnologists
According to the survey, a significant majority of biotechnologists are now adept at coding. A remarkable 87% of wet lab scientist respondents reported that they write code, with 55% scripting to automate workflows weekly and 39% programming data engineering or pipelines on a similar schedule. Most of these scientists have acquired their coding skills independently, with 74% learning on the job and 63% through formal education.
Python emerged as the most common coding language, used by 97% of respondents for data analysis in the past year. Other frequently utilized languages include Shell (Bash/Powershell), R, SQL, and HTML/CSS.
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