Increasing the final titer of a multi-gene metabolic pathway can be viewed as a multivariate optimization problem. While numerous multivariate optimization algorithms exist, few are specifically designed to accommodate the constraints posed by genetic engineering workflows. We present a strategy for optimizing expression levels across an arbitrary number of genes that requires few design-build-test iterations. We compare the performance of several optimization algorithms on a series of simulated expression landscapes. We show that optimal experimental design parameters depend on the degree of landscape ruggedness. This work provides a theoretical framework for designing and executing numerical optimization on multi-gene systems.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5835107 | PMC |
| http://dx.doi.org/10.3389/fmicb.2018.00313 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Accelerometer-measured physical activity timing with incident dementia.
Alzheimers Dement
January 2025
Innovation Center for Neurological Disorders, Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.
Introduction: Moderate to vigorous physical activity (MVPA) is linked to lower dementia risk, though the optimal timing remains unclear.
Methods: Using accelerometer-measured MVPA data from 90,329 dementia-free UK Biobank participants with at least 2 years of follow-up, we assessed associations between MVPA patterns (morning, afternoon, evening, mixed, inactive) and dementia risk via multivariable-adjusted Cox proportional hazards models.
Results: Compared to the inactive group, participants with a tendency of morning MVPA had a lower risk of all-cause dementia (hazard ratio [HR]: 0.
Modeling dosimetric benefits from daily adaptive RT for gynecological cancer patients with and without knowledge-based dose prediction.
J Appl Clin Med Phys
January 2025
Department of Radiation Medicine and Applied Sciences, UC San Diego Health, La Jolla, California, USA.
Purpose: Daily online adaptive radiotherapy (ART) improves dose metrics for gynecological cancer patients, but the on-treatment process is resource-intensive requiring longer appointments and additional time from the entire adaptive team. To optimize resource allocation, we propose a model to identify high-priority patients.
Methods: For 49 retrospective cervical and endometrial cancer patients, we calculated two initial plans: the treated standard-of-care (Initial) and a reduced margin initial plan (Initial) for adapting with the Ethos treatment planning system.
Comprehensive Sepsis Risk Prediction in Leukemia Using a Random Forest Model and Restricted Cubic Spline Analysis.
J Inflamm Res
January 2025
Department of Hematology, The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, Henan Province, People's Republic of China.
Background: Sepsis is a severe complication in leukemia patients, contributing to high mortality rates. Identifying early predictors of sepsis is crucial for timely intervention. This study aimed to develop and validate a predictive model for sepsis risk in leukemia patients using machine learning techniques.
View Article and Find Full Text PDFExploring using HBsAg to predict interferon treatment course to achieve clinical cure in chronic hepatitis B patients: a clinical study.
Front Immunol
January 2025
Department of Gastroenterology and Hepatology, Tianjin Third Central Hospital, Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Institute of Hepatobiliary Disease, Tianjin, China.
Objective: Although pegylated interferon α-2b (PEG-IFN α-2b) therapy for chronic hepatitis B has received increasing attention, determining the optimal treatment course remains challenging. This research aimed to develop an efficient model for predicting interferon (IFN) treatment course.
Methods: Patients with chronic hepatitis B, undergoing PEG-IFN α-2b monotherapy or combined with NAs (Nucleoside Analogs), were recruited from January 2018 to December 2023 at Tianjin Third Central Hospital.
Impact of pre-pregnancy maternal body mass index on neonatal outcomes in twin delivery: A retrospective cohort study.
Pak J Med Sci
January 2025
Lin Lin Department of Obstetrics and Gynecology, Fujian Maternity and Child Health Hospital College of Clinical, Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, Fujian Province 350001, China.
Objective: This study examined the potential link between maternal pre-pregnancy body mass index (PPBMI) with neonatal outcomes in twin pregnancies.
Methods: This retrospective analysis records of 1,270 women with twin pregnancies, delivered at the Fujian Maternity and Child Health Hospital between 2019 and 2021, were retrospectively analysed. Women were diagnosed as underweight, normal BMI, and overweight/obese according to their PPBMI.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!