A5000882828- Microbial Metabolic Engineering and Bioproduction
- Probiotics and Fermented Foods
- Protein Structure and Dynamics
- Biofuel production and bioconversion
- Machine Learning in Bioinformatics
- Genomics and Phylogenetic Studies
- Microbial Metabolites in Food Biotechnology
- Bacterial Genetics and Biotechnology
- Advanced Chemical Sensor Technologies
- RNA and protein synthesis mechanisms
- Microbial Metabolism and Applications
- Metabolomics and Mass Spectrometry Studies
- Viral Infectious Diseases and Gene Expression in Insects
- Isotope Analysis in Ecology
- Spectroscopy and Chemometric Analyses
- Enzyme Catalysis and Immobilization
- Plant Virus Research Studies
- Groundwater and Isotope Geochemistry
- Fungal Biology and Applications
- Food Quality and Safety Studies
- Enzyme Structure and Function
- Cancer, Lipids, and Metabolism
- Meat and Animal Product Quality
- Medicinal Plants and Neuroprotection
- Genetics, Aging, and Longevity in Model Organisms
University of Oxford
2023-2025
China Agricultural University
2025
Hangzhou Normal University
2024
Beijing Technology and Business University
2023-2024
University of California, San Diego
2022-2024
Science Oxford
2023-2024
Changsha University of Science and Technology
2022
La Jolla Bioengineering Institute
2022
Abstract The enzyme turnover rate, ${k}_{cat}$, quantifies kinetics by indicating the maximum efficiency of catalysis. Despite its importance, ${k}_{cat}$ values remain scarce in databases for most organisms, primarily because cost experimental measurements. To predict and account strong temperature dependence, DLTKcat was developed this study demonstrated superior performance (log10-scale root mean squared error = 0.88, R-squared 0.66) than previously published models. Through two case...
Soybean aphid (Aphis glycines) is one of the main pests on soybeans, which causes serious damage to soybean worldwide. The current genome quite fragmented, has impeded scientific research some extent. In this study, we assembled a chromosome-level using MGI short reads, PacBio HiFi long reads and Hi-C reads. sequence was anchored four pseudo-chromosomes, with total length 324 Mb scaffold N50 88.85 Mb. We evaluated based insecta_odb10 results show it completeness 97.2%. A 20,781...
Abstract An accurate deep learning predictor is needed for enzyme optimal temperature (${T}_{opt}$), which quantitatively describes how affects the catalytic activity. In comparison with existing models, a new model developed in this study, Seq2Topt, reached superior accuracy on ${T}_{opt}$ prediction just using protein sequences (RMSE = 12.26°C and R2 0.57), could capture key regions multi-head attention residues. Through case studies thermophilic selection predicting shifts caused by point...
Abstract Genome‐scale metabolic models and flux balance analysis (FBA) have been extensively used for modeling designing bacterial fermentation. However, FBA‐based that accurately simulate the dynamics of coculture are still rare, especially lactic acid bacteria in yogurt To investigate interactions starter culture Streptococcus thermophilus Lactobacillus delbrueckii subsp. bulgaricus , this study built a dynamic metagenome‐scale model which integrated constrained proteome allocation. The...
The transcriptional regulatory network (TRN) of E . coli consists thousands interactions between regulators and DNA sequences. Regulons are typically determined either from resource-intensive experimental measurement functional binding sites, or inferred analysis high-throughput gene expression datasets. Recently, independent component (ICA) RNA-seq compendia has shown to be a powerful method for inferring bacterial regulons. However, it remains unclear what extent regulons predicted by ICA...
Lactiplantibacillus plantarum is a probiotic bacterium widely used in food and health industries, but its gene regulatory information limited existing databases, which impedes the research of physiology applications. To obtain better understanding transcriptional network L. plantarum, independent component analysis transcriptomes was to derive 45 sets independently modulated genes (iModulons). Those iModulons were annotated for associated transcription factors functional pathways, active...
Abstract An accurate deep learning predictor is needed for enzyme optimal temperature ( T opt ), which quantitatively describes how affects the catalytic activity. Seq2Topt, developed in this study, reached a superior accuracy on prediction just using protein sequences (RMSE = 13.3℃ and R2=0.48) comparison with existing models, could capture key regions multi-head attention residues. Through case studies thermophilic selection predicting shifts caused by point mutations, Seq2Topt was...
Abstract The enzyme turnover rate, k cat , quantifies kinetics by indicating the maximum efficiency of catalysis. Despite its importance, values remain scarce in databases for most organisms, primarily due to cost experimental measurements. To predict and account strong temperature dependence, DLTKcat was developed this study demonstrated superior performance (log10-scale RMSE = 0.88, R2 0.66) than previously published models. Through two case studies, showed ability effect protein sequence...
Abstract The transcriptional regulatory network (TRN) of E. coli consists thousands interactions between regulators and DNA sequences. Inherently the sequence is primary determinant TRN; however, it well established that presence a binding motif does not guarantee functional protein site. Thus, extent to which TRN architecture can be predicted by genome alone remains unclear. Here, we developed machine learning models predict structure based on sequence. Models were constructed successfully...
Abstract The exopolysaccharide (EPS) produced by Lactiplantibacillus plantarum is a high-value bioproduct in food and health industries, its biosynthesis has been found as secondary metabolic pathway to mediate acid stress. To quantitatively investigate stress response L. model EPS production, this study measured metabolomics, proteomics growth data for HMX2 cultured at 4 different pH values. metabolomics showed that under stress, the production flux was evidently enhanced while glycolysis...
Abstract An accurate deep learning predictor of enzyme optimal pH is essential to quantitatively describe how influences the catalytic activity. Seq2pHopt-2.0, developed in this study, outperformed existing predictors (RMSE=0.833 and R2=0.479), could provide good interpretability with informative residue attention weights. The classification acidic alkaline enzymes showcased potential Seq2pHopt-2.0 as a useful mining tool for identifying candidate specific preferences. Furthermore, single...
Traditional sensory evaluation, relying on human assessors, is vulnerable to subjective error and lacks automation. Nonetheless, the complexity of sensation makes it challenging develop a computational method in place evaluation. To tackle this challenge, study constructed logistic regression classification models that could predict yogurt aroma types based aroma-active compound concentrations with high accuracy (AUC ROC > 0.8). Furthermore, indicator compounds discovered from feature...
This thesis considers the field of high frequency 5G technology as main subject its study. After years development in many countries, downlink speed networks low and medium bands has been able to meet needs most consumers industries, but for some industries with particularly demand uplink bandwidth, capacity is still insufficient. In research wireless communication technology, band transmission not only one key technologies, also an important direction, density will become primary means...
Genome-scale metabolic models (GSMMs) and flux balance analysis (FBA) have been extensively used to model design bacterial fermentation. However, FBA-based designed for simulating the dynamics of co-culture with quantitative accuracy are still uncommon, which is particularly true lactic acid bacteria (LAB) yogurt To investigate interactions in starter culture Streptococcus thermophilus (ST) Lactobacillus delbrueckii subsp. bulgaricus (LB), this study built a dynamic community-level GSMM...
Abstract Lactobacillus plantarum is a probiotic bacteria widely used in food and health industries, but its gene regulatory information limited existing databases, which impedes the research of physiology applications. To obtain better understanding transcriptional network L. , independent component analysis (ICA) transcriptomes was to derive 45 sets independently modulated genes (iModulons). Those iModulons were annotated for associated transcription factors (TFs) functional pathways,...