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Chen, K. Y.

Publications and source records attributed to Chen, K. Y..

3 recordsLinked to original sources

Stochastic Simulation to Visualize Gene Expression and Error Correction in Living Cells

Stochastic simulation can make the molecular processes of cellular control more vivid than the traditional differential-equation approach by generating typical system histories instead of just statistical measures such as the mean and variance of a population. Simple simulations are now easy for students to construct from scratch, that is, without recourse to black-box packages. In some cases, their results can also be compared directly to single-molecule experimental data. After introducing the stochastic simulation algorithm, this article gives two case studies, involving gene expression and error correction, respectively. Code samples and resulting animations showing results are given in the online supplement.

biophysics

Potential Bias of Doubly Labeled Water for Measuring Energy Expenditure Differences Between Diets Varying in Carbohydrate

BackgroundVery low-carbohydrate diets have been reported to substantially increase human energy expenditure as measured by doubly labeled water (DLW) but not by respiratory chambers. Do the DLW data reflect true physiological differences that are undetected by respiratory chambers? Alternatively, are the apparent DLW energy expenditure a consequence of failure to fully account for respiratory quotient (RQ) differences between diets?\n\nObjectiveTo examine energy expenditure differences between diets varying drastically in carbohydrate and to quantitatively compare DLW data with respiratory chamber and body composition measurements within an energy balance framework.\n\nDesignDLW measurements were obtained during the final two weeks of month-long baseline (BD; 50% carbohydrate, 35% fat, 15% protein) and isocaloric ketogenic diets (KD; 5% carbohydrate, 80% fat, 15% protein) in 17 men with BMI 25-35 kg/m2. Subjects resided 2d/week in respiratory chambers to measure energy expenditure (EEchamber). DLW expenditure was calculated using chamber-determined respiratory quotients (RQ) either unadjusted (EEDLW) or adjusted (EEDLW{Delta}RQ) for net energy imbalance using diet-specific coefficients. Accelerometers measured physical activity. Body composition changes were measured by dual-energy X-ray absorptiometry which were combined with energy intake measurements to calculate energy expenditure by balance (EEbal).\n\nResultsAfter transitioning from BD to KD, neither EEchamber nor EEbal were significantly changed ({triangleup}EEchamber=24{+/-}30 kcal/d; p=0.43 and {triangleup}EEbal=-141{+/-}118 kcal/d; p=0.25). Similarly, physical activity (-5.1{+/-}4.8%; p=0.3) and exercise efficiency (-1.6{+/-}2.4%; p=0.52) were not significantly changed. However, EEDLW was 209{+/-}83 kcal/d higher during the KD (p=0.023) but was not significantly increased when adjusted for energy balance (EEDLW{Delta}RQ =139{+/-}89 kcal/d; p=0.14). After removing 2 outliers whose EEDLW were incompatible with other data, EEDLW and EEDLW{triangleup}RQ were marginally increased during the KD by 126{+/-}62 kcal/d (p=0.063) and 46{+/-}65 kcal/d (p=0.49), respectively.\n\nConclusionsDLW calculations failing to account for diet-specific energy imbalance effects on RQ erroneously suggest that very low carbohydrate diets substantially increase energy expenditure.

physiology

Millstone: Software for Multiplex Microbial Genome Analysis and Engineering

Inexpensive DNA sequencing and advances in genome editing have made computational analysis a major rate-limiting step in adaptive laboratory evolution and microbial genome engineering. We describe Millstone, a web-based platform which automates genotype comparison and visualization for projects with up to hundreds of genomic samples. To enable iterative genome engineering, Millstone allows users to design oligonucleotide libraries and create successive versions of reference genomes. Millstone is open source and easily deployable to a cloud platform, local cluster, or desktop, making it a scalable solution for any lab.

synthetic biology