计算机科学
灵活性(工程)
兴旺的
数据科学
可读性
关系(数据库)
系统生物学
计算模型
软件工程
人工智能
程序设计语言
生物信息学
生物
数据挖掘
统计
数学
社会科学
社会学
作者
Elisabeth Roesch,Joe G Greener,Adam L. MacLean,Huda Nassar,Chris Rackauckas,Timothy E. Holy,Michael Stumpf
出处
期刊:Nature Methods
[Springer Nature]
日期:2023-04-06
卷期号:20 (5): 655-664
被引量:3
标识
DOI:10.1038/s41592-023-01832-z
摘要
Major computational challenges exist in relation to the collection, curation, processing and analysis of large genomic and imaging datasets, as well as the simulation of larger and more realistic models in systems biology. Here we discuss how a relative newcomer among programming languages-Julia-is poised to meet the current and emerging demands in the computational biosciences and beyond. Speed, flexibility, a thriving package ecosystem and readability are major factors that make high-performance computing and data analysis available to an unprecedented degree. We highlight how Julia's design is already enabling new ways of analyzing biological data and systems, and we provide a list of resources that can facilitate the transition into Julian computing.
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