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protein secretion
Machine learning-based investigation of the cancer protein secretory pathway
One of the most challenging features in diagnosing and treating cancer is its heterogeneity–the tissue of origin, gene mutation profile, patient, and local tumor environment are just a few of the many factors that can affect the pathophysiology and response to treatment of a particular cancer.
Rasool Saghaleyni
,
Azam Sheikh Muhammad
,
Pramod Bangalore
,
Jens Nielsen
,
Jonathan L. Robinson
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HumanSec
The HumanSec toolbox advances the reference human genome-scale metabolic model by integrating protein-specific reactions from our proteomics dataset. It delves into the competition for resources between host cell proteins and recombinant protein production, aiming to create tailored protein secretion models for cell lines. By analyzing metabolomics data, it identifies crucial genes and pathways influencing protein production, offering potential for targeted cell factory design. However, this progress is acknowledged cautiously due to the inherent complexities of this research area. HumanSec also explores protein production pathways in diseases and aims to contribute to understanding protein folding mechanisms in pathological conditions, acknowledging the vast unknowns in this field.
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