A5015802526- Probiotics and Fermented Foods
- Gut microbiota and health
- Identification and Quantification in Food
- Biosensors and Analytical Detection
- Genomics and Phylogenetic Studies
- Molecular Biology Techniques and Applications
- Gene expression and cancer classification
- Enterobacteriaceae and Cronobacter Research
- Vibrio bacteria research studies
IBM Research - Almaden
2019-2024
New York State College of Agriculture & Life Sciences
2022
Cornell University
2022
In this work, we hypothesized that shifts in the food microbiome can be used as an indicator of unexpected contaminants or environmental changes. To test hypothesis, sequenced total RNA 31 high protein powder (HPP) samples poultry meal pet ingredients. We developed a analysis pipeline employing key eukaryotic matrix filtering step improved microbe detection specificity to >99.96% during silico validation. The identified 119 microbial genera per HPP sample on average with 65 present all...
Tracking the bacterial communities present in our food has potential to inform safety and product origin. To do so, entire genetic material a sample is extracted using chemical methods or commercially available kits sequenced next-generation platforms provide snapshot of microbial composition.
Learning associations of traits with the microbial composition a set samples is fundamental goal in microbiome studies. Recently, machine learning methods have been explored for this goal, some promise. However, comparison to other fields, data are high-dimensional and not abundant; leading low-sample-size under-determined system. Moreover, often unbalanced biased. Given such training data, fail perform classification task sufficient accuracy. Lack signal especially problematic when classes...
ABSTRACT The increasing knowledge of microbial ecology in food products relating to quality and safety the established usefulness machine learning algorithms for anomaly detection multiple scenarios suggests that application microbiome data production systems could be a valuable approach used systems. These methods identify ingredients deviate from their typical composition, which indicate fraud or issues. objective this study was assess feasibility using shotgun sequencing as input into...
ABSTRACT In this work, we hypothesized that shifts in the food microbiome can be used as an indicator of unexpected contaminants or environmental changes. To test hypothesis, sequenced total RNA 31 high protein powder (HPP) samples poultry meal pet ingredients. We developed a analysis pipeline employing key eukaryotic matrix filtering step improved microbe detection specificity to >99.96% during silico validation. The identified 119 microbial genera per HPP sample on average with 65...
ABSTRACT Untargeted sequencing of nucleic acids present in food can inform the detection safety and origin, as well product tampering mislabeling issues. The application such technologies to analysis could reveal valuable insights that are simply unobtainable by targeted testing, leading efforts applying industry. However, before these approaches be applied, it is imperative verify most appropriate methods used at every step process: gathering primary material, laboratory methods, data...
The increasing knowledge of microbial ecology in food products relating to quality and safety the established usefulness machine learning algorithms for anomaly detection multiple scenarios suggests that application microbiome data production systems could be a valuable approach used systems. These methods identify ingredients deviate from their typical composition, which indicate fraud or issues. objective this study was assess feasibility using shotgun sequencing as input into fluid milk...