machine learning
Research Article | Host-Microbe BiologyMachine Learning Reveals Time-Varying Microbial Predictors with Complex Effects on Glucose RegulationRecent studies have shown a clear link between gut microbiota and type 2 diabetes. However, current results are based on cross-sectional studies that aim to determine the microbial dysbiosis when the disease is already prevalent.
Research Article | Applied and Environmental ScienceAssessing Biodegradability of Chemical Compounds from Microbial Community Growth Using Flow CytometryThe manifold effects of potentially toxic compounds on microbial communities are often difficult to discern. Some compounds may be transformed or completely degraded by few or multiple strains in the community, whereas others may present inhibitory effects.
Research Article | Molecular Biology and PhysiologyHarnessing Machine Learning To Unravel Protein Degradation in Escherichia coliBacteria use protein degradation to control proliferation, dispose of misfolded proteins, and adapt to physiological and environmental shifts, but the factors that dictate which proteins are prone to degradation are mostly unknown. In this study, we have used a combined computational-experimental approach to explore protein degradation in E. coli.
Research Article | Host-Microbe BiologyHuman Gene Functional Network-Informed Prediction of HIV-1 Host Dependency FactorsIdentification of HIV-1 HDFs remains a crucial step to understand the complicated relationships between human and HIV-1. To complement the experimental identification of HDFs, we have implemented an existing network-based gene discovery strategy to predict HDFs from the human genome. The core idea of the proposed method is that the rich information deposited in host gene functional networks can be effectively utilized to infer the...
Sponsored Content Minireview | Clinical Science and EpidemiologyThe Gut Microbiome and Individual-Specific Responses to DietNutritional content and timing are increasingly appreciated to constitute important human variables collectively impacting all aspects of human physiology and disease. However, person-specific mechanisms driving nutritional impacts on the human host remain incompletely understood, while current dietary recommendations remain empirical and nonpersonalized. Precision nutrition aims to harness individualized bodies of data, including the...
Research Article | Molecular Biology and PhysiologyGenome-Wide Analysis of RNA Decay in the Cyanobacterium Synechococcus sp. Strain PCC 7002RNA degradation is an important process that affects the final concentration of individual mRNAs, affecting protein expression and cellular physiology. Studies of how RNA is degraded increase our knowledge of this fundamental process as well as enable the creation of genetic tools to manipulate RNA stability. By studying global transcript turnover, we searched for sequence elements that correlated with transcript (in)stability and used...
Research Article | Host-Microbe BiologyT3SEpp: an Integrated Prediction Pipeline for Bacterial Type III Secreted EffectorsType III secreted effector (T3SE) prediction remains a big computational challenge. In practical applications, current software tools often suffer problems of high false-positive rates. One of the causal factors could be the relatively unitary type of biological features used for the design and training of the models. In this research, we made a comprehensive survey on the sequence-based features of T3SEs, including signal sequences,...
Research Article | Therapeutics and PreventionPredicting Phenotypic Polymyxin Resistance in Klebsiella pneumoniae through Machine Learning Analysis of Genomic DataPolymyxins are last-resort antibiotics used to treat highly resistant Gram-negative bacteria. There are increasing reports of polymyxin resistance emerging, raising concerns of a postantibiotic era. Polymyxin resistance is therefore a significant public health threat, but current phenotypic methods for detection are difficult and time-consuming to perform. There have been increasing efforts to use whole-genome sequencing for detection...
Research Article | Host-Microbe BiologyInterpretable Log Contrasts for the Classification of Health Biomarkers: a New Approach to Balance SelectionHigh-throughput sequencing provides an easy and cost-effective way to measure the relative abundance of bacteria in any environmental or biological sample. When these samples come from humans, the microbiome signatures can act as biomarkers for disease prediction. However, because bacterial abundance is measured as a composition, the data have unique properties that make conventional analyses inappropriate. To overcome this, analysts...
Research Article | Clinical Science and EpidemiologyPrediction of Acquired Antimicrobial Resistance for Multiple Bacterial Species Using Neural NetworksMachine learning is a proven method to predict AMR; however, the performance of any machine learning model depends on the quality of the input data. Therefore, we evaluated different methods of representing information about mutations as well as mobilizable genes, so that the information can serve as input for a robust model. We combined data from multiple bacterial species in order to develop species-independent machine learning models...