用大数据解释疾病:你的途径有多有效?

Bas Stringer, Maurits J. J. Dijkstra, K. Feenstra, Sanne Abeln, J. Heringa
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引用次数: 1

摘要

设计解决当前人类健康、医疗保健和营养方面的社会挑战,以及食品、饲料和能源的可持续生产,需要基于最广泛意义上的生命科学研发的学术创新和工业活动。正在进行的项目的多样性表明,这些部门的公私合作正在增加。仅在荷兰就有几个例子,包括荷兰生命科学技术中心(DTL)、CTMM-TraIT (TransMart、Open Clinica)、NFU Data 4生命科学倡议、Onco-XL、Parelsnoer、个性化癌症治疗中心(CPCT)和飞利浦在生命科学与健康领域的Health- suite数字平台;食品育种与农业食品中的TIFN植物育种虚拟实验室、种子谷与园艺“双谷数字”以及生物经济领域的BeBasic。设置文本样式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Explaining disease using big data: How valid is your pathway?
The design of solutions to current societal challenges in human health, healthcare and nutrition, and to the sustainable production of food, feed and energy, requires academic innovations and industrial activity based on life science R&D in its broadest sense. The diversity of on-going programs shows that public-private collaboration is increasing in each of these sectors. A few examples in The Netherlands alone include the Dutch Techcenter for Life Sciences (DTL), CTMM-TraIT (TransMart, Open Clinica), NFU Data 4 Lifesciences initiative, Onco-XL, Parelsnoer, Centre for Personalized Cancer Treatment (CPCT) and Philips' Health-Suite Digital Platform in the Life Science & Health sector; Breed4Food and TIFN in Agri&Food; Virtual Lab for Plant Breeding, Seed Valley and “Tuinbouw Digitaal” in Horticulture; and BeBasic in Biobased Economy.style the text.
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