AIMC Topic: Recombinant Proteins
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Evaluation of the False Discovery Rate in Library-Free Search by DIA-NN Using Human Proteome.
Journal of proteome research
Jul 18, 2025
Recently, deep-learning-based spectral libraries have gained increasing attention. Several data-independent acquisition (DIA) software tools have integrated this feature, known as a library-free search, thereby making DIA analysis more accessible. H...
Construction and evaluation of a height prediction model for children with growth disorders treated with recombinant human growth hormone.
BMC endocrine disorders
Jul 9, 2025
BACKGROUND: Height gain in children with growth disorders undergoing recombinant human growth hormone (rhGH) therapy shows considerable variability. Predicting treatment outcomes is essential for optimizing individualized treatment strategies.
Modeling and Optimization of Recombinant Tocilizumab Production From Pichia pastoris Using Response Surface Methodology and Artificial Neural Network.
Biotechnology and bioengineering
May 15, 2025
This study has demonstrated the optimization of the defined medium that significantly enhanced the production of recombinant monoclonal antibody (mAb) Tocilizumab (TCZ) as full-length and Fab fragment from Pichia pastoris. Out of the four tested defi...
Estimation and validation of solubility of recombinant protein in E. coli strains via various advanced machine learning models.
Scientific reports
Apr 14, 2025
This study presents a comprehensive approach to predicting solubility of recombinant protein in four E. coli samples by employing machine learning techniques and optimization algorithms. Various models, including AdaBoost, Decision Tree Regression (D...
Machine Learning-Powered Optimization of a CHO Cell Cultivation Process.
Biotechnology and bioengineering
Jan 31, 2025
Chinese Hamster Ovary (CHO) cells are the most widely used cell lines to produce recombinant therapeutic proteins such as monoclonal antibodies (mAbs). However, the optimization of the CHO cell culture process is very complex and influenced by variou...
Interpreting IGF-1 in children treated with recombinant growth hormone: challenges during early puberty.
Frontiers in endocrinology
Jan 21, 2025
OBJECTIVE: It can be challenging to determine the correct dosage of recombinant growth hormone (GH) in children with GH deficiency, leading to highly variable treatment responses. Insulin-like growth factor-1 (IGF-1) is a tool for monitoring GH treat...
Machine learning models to further identify advantaged populations that can achieve functional cure of chronic hepatitis B virus infection after receiving Peg-IFN alpha treatment.
International journal of medical informatics
Oct 22, 2024
OBJECTIVE: Functional cure is currently the highest goal of hepatitis B virus(HBV) treatment.Pegylated interferon(Peg-IFN) alpha is an important drug for this purpose,but even in the hepatitis B e antigen(HBeAg)-negative population,there is still a p...
Identifying potential targets for preventing cancer progression through the PLA2G1B recombinant protein using bioinformatics and machine learning methods.
International journal of biological macromolecules
Jul 15, 2024
Lung cancer is the deadliest and most aggressive malignancy in the world. Preventing cancer is crucial. Therefore, the new molecular targets have laid the foundation for molecular diagnosis and targeted therapy of lung cancer. PLA2G1B plays a key rol...
Optimizing recombinant antibody fragment production: A comparison of artificial intelligence and statistical modeling.
Biotechnology and applied biochemistry
May 19, 2024
Maximizing the recombinant protein yield necessitates optimizing the production medium. This can be done using a variety of methods, including the conventional "one-factor-at-a-time" approach and more recent statistical and mathematical methods such ...
Genetic algorithm-based semisupervised convolutional neural network for real-time monitoring of Escherichia coli fermentation of recombinant protein production using a Raman sensor.
Biotechnology and bioengineering
Jan 22, 2024
As a non-destructive sensing technique, Raman spectroscopy is often combined with regression models for real-time detection of key components in microbial cultivation processes. However, achieving accurate model predictions often requires a large amo...
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