Yu Chen , Johan Gustafsson , Jingyu Yang , Jens Nielsen , Eduard J Kerkhoven
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引用次数: 0
Abstract
Single-cell technologies have been widely used in biological studies and generated a plethora of single-cell data to be interpreted. Due to the inclusion of the priori metabolic network knowledge as well as gene–protein–reaction associations, genome-scale metabolic models (GEMs) have been a powerful tool to integrate and thereby interpret various omics data mostly from bulk samples. Here, we first review two common ways to leverage bulk omics data with GEMs and then discuss advances on integrative analysis of single-cell omics data with GEMs. We end by presenting our views on current challenges and perspectives in this field.
期刊介绍：
Current Opinion in Biotechnology (COBIOT) is renowned for publishing authoritative, comprehensive, and systematic reviews. By offering clear and readable syntheses of current advances in biotechnology, COBIOT assists specialists in staying updated on the latest developments in the field. Expert authors annotate the most noteworthy papers from the vast array of information available today, providing readers with valuable insights and saving them time.
As part of the Current Opinion and Research (CO+RE) suite of journals, COBIOT is accompanied by the open-access primary research journal, Current Research in Biotechnology (CRBIOT). Leveraging the editorial excellence, high impact, and global reach of the Current Opinion legacy, CO+RE journals ensure they are widely read resources integral to scientists' workflows.
COBIOT is organized into themed sections, each reviewed once a year. These themes cover various areas of biotechnology, including analytical biotechnology, plant biotechnology, food biotechnology, energy biotechnology, environmental biotechnology, systems biology, nanobiotechnology, tissue, cell, and pathway engineering, chemical biotechnology, and pharmaceutical biotechnology.
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