Antibody Glycan Quality Predicted from CHO Cell Culture Media Markers and Machine Learning

IF 4.4 2区生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY

Computational and structural biotechnology journal Pub Date : 2024-06-01 DOI:10.1016/j.csbj.2024.05.046

Meiyappan Lakshmanan, Sean Chia, K. Pang, L. C. Sim, Gavin Teo, S. Mak, Shuwen Chen, Hsueh Lee Lim, Alison P. Lee, Farouq Bin Mahfut, Say Kong Ng, Yuansheng Yang, Annie Soh, Andy Hee-Meng Tan, Andre Choo, Ying Swan Ho, Terry Nguyen-Khuong, Ian Walsh

引用次数: 0

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通过 CHO 细胞培养基标记物和机器学习预测抗体聚糖质量

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Computational and structural biotechnology journal Biochemistry, Genetics and Molecular Biology-Biophysics

CiteScore

9.30

自引率

3.30%

发文量

540

审稿时长

6 weeks

期刊介绍： Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to: Structure and function of proteins, nucleic acids and other macromolecules Structure and function of multi-component complexes Protein folding, processing and degradation Enzymology Computational and structural studies of plant systems Microbial Informatics Genomics Proteomics Metabolomics Algorithms and Hypothesis in Bioinformatics Mathematical and Theoretical Biology Computational Chemistry and Drug Discovery Microscopy and Molecular Imaging Nanotechnology Systems and Synthetic Biology